SOTA Work Handoff

This page hands the pre-registered SOTA audit work to the next agent. It covers:

• where each sensor pair stands;
• how an audit is run, and the rules that keep it honest;
• which data is already spent;
• the pitfalls met so far;
• the next candidates.

Read AGENTS.md and the SOTA leaderboard first. State as of 2026-10-22; the INS-LiDAR audit evaluated merged main at e2ac3e20.

Goal and the one rule

Calibrex may call a method state of the art only for a claim that a frozen, pre-registered audit marks supported. Five things follow from that:

• Evaluation data is never seen first. The claim, the evaluation data, the scoring code and the thresholds are committed before any method reads that data.
• Each evaluation runs once, from the frozen code. A refuted or incomplete audit is published like a supported one, and stays on the leaderboard.
• Verdicts are never changed. An analysis after the verdict is labelled post hoc, and it may only explain the verdict.
• Data is spent once a method has read it. It can be used for development, never again for evaluation.
• The reference is not ground truth. A dataset's own calibration (KITTI, Kalibr, LI-Init) is the reference, and pages say so.

Standings

Pair	Standing	Audits	Page
imu-lidar	supported	rotation+clock (4/4), full extrinsic v2 (4/4); full extrinsic v1 refuted (0/8)	MID360
lidar-vehicle	supported	KITTI motion-only rotation, 8 drives (3/3)	KITTI lidar-vehicle
camera-imu	supported	Hilti v3 per-axis verdicts (7/7); v1 (6/7) and v2 (5/7) refuted; TUM-VI check audit v1 refuted (4/5: passed 4 of 30 2 deg turns, all about an unchecked pitch); v2 with --fail-on partial supported (5/5: flagged all 30, failed 28 on the turned axis; Kalibr fully passed 8 of 10)	Hilti camera-IMU
camera-lidar	refuted	KITTI check v1 (5/9), v2 (8/9)	v2, v1
camera-camera	refuted	Hilti (4/6): accurate, but a 1 deg turn was flagged in only 70 % of trials	Hilti camera SOTA
lidar-lidar	refuted	NTU VIRAL (2/4): accurate, but does not beat scan-to-scan; cross-recording consistency 1.143 against 1.0	NTU VIRAL
ins-lidar	refuted	KITTI + Boreas rotation v1 (6/8); one recording has no observable rotation	INS-LiDAR rotation
camera-lidar (checkerboard)	refuted	KITTI calibration recordings (0/5 days): no estimate on any day (stereo time bound, board fragments)	board camera-LiDAR
lidar-wheel_odometry	refuted	NCLT, 5 unseen sessions: accuracy 0/5 (roll and pitch 0.1-2.4 deg off; yaw within 0.43 deg); check honesty supported (never failed NCLT's calibration)	LiDAR-wheel odometry
camera (focal)	supported	TUM-VI check honesty and detection (5/5): never failed Kalibr's focal lengths (6/10 judged); passed none of 20 3 %-wrong cases, failed 6; half inconclusive, no accuracy claim	camera-focal
gnss-imu, imu-vehicle	no claim	native methods exist; no audit yet	estimate on real data

How an audit is run

The KITTI camera-lidar v2 audit is the most complete worked example (PRs #230 and #231). Its files are the templates:

Piece	Example
Driver: fetch, convert, run every check once, record every command	tools/kitti_camera_lidar_v2_evaluate.py, tools/kitti_camera_lidar_sota_run.py
Partial download of large zip archives (HTTP range, If-Match on the pinned ETag, CRC-32 checked)	tools/kitti_drive_fetch.py, tools/kitti_drive_metadata.py
Scorer: frozen metrics, gates and verdict as module constants	tools/score_kitti_camera_lidar_v2.py
Audit builder: benchmarks, protocol and audit for calibrex sota audit	tools/build_kitti_camera_lidar_v2_audit.py
Pre-registration	docs/benchmarks/kitti_camera_lidar_v2_preregistration.yaml
Tests	tests/unit/test_score_kitti_camera_lidar_v2.py, test_build_kitti_camera_lidar_v2_audit.py, test_kitti_camera_lidar_v2_preregistration.py, test_kitti_drive_fetch.py, test_kitti_camera_lidar_v2_evaluate.py
Results	docs/assets/kitti_camera_lidar_v2/evaluation/ (runs, logs, scores, benchmarks, protocol, audit)

Steps

1. Claim. Write what is claimed, against which reference, and with which gates. An honest per-axis claim gates only the axes the method judges and adds a coverage gate. This is what turned camera-imu from refuted (v1, v2) to supported (v3).
2. Spent data. Before choosing evaluation data, find every recording any method has read:
3. grep the repository and its history (git log --all -S<id>);
4. for KITTI Odometry, map sequence numbers to raw drives.

Choose the evaluation set by a rule applied to metadata only: archive file lists, sizes, ETags. The exposure field of the pre-registration says what was fetched. 3. Development. Work only on spent data. Commit the development scores. Any change made after looking at results is written down as such. 4. Thresholds. Derive them from the development values, by the rules used so far: - error gate: 1.5 times the worst development value, rounded up to the next 0.25 deg; - coverage floor: the development rate divided by 1.5, rounded down to the next 0.25 (whole items, rounded down, for counts); - miss-rate allowance: the one-sided 95 % upper bound of the development miss rate (exact binomial; the rule of three when nothing is missed), rounded up to the next 0.05. 5. Freeze. - Commit the code. This is frozen_code_commit: everything in src/ and tools/ that the evaluation uses. - Then commit the pre-registration in a docs-only commit. It pins every archive (size, ETag) and every calibration file (SHA-256). - Add a test that loads the real pre-registration and checks it against the frozen tools: claim text, pins, recipe, thresholds. - Open a PR and merge it. 6. Run once from main: - first check that git diff <frozen> HEAD -- src tools is empty; - repeat a run only under the pre-registered rerun policy (a failed download, OOM, a killed process), with the same command; - keep the failed attempt's record. 7. Score and publish. - Score with the frozen scorer, build the audit, then run calibrex sota audit protocol.yaml --output audit.yaml. It exits 0 only for supported, so exit 2 means refuted, not an error. - Regenerate the leaderboard (command below). - Update the audit page's results section, sota_leaderboard.md, the README SOTA table, docs/index.md and CHANGELOG.md. - Open a PR and merge it.

calibrex sota leaderboard \
  docs/assets/hilti2022_camera_sota/camera_camera/hilti_camera_camera_sota_audit.yaml \
  docs/assets/hilti_camera_imu_sota_audit.yaml \
  docs/assets/hilti2022_camera_sota/camera_imu_v2/hilti_camera_imu_v2_sota_audit.yaml \
  docs/assets/hilti2022_camera_imu_v3/hilti_camera_imu_v3_sota_audit.yaml \
  docs/assets/kitti_camera_lidar/evaluation/kitti_camera_lidar_sota_audit.yaml \
  docs/assets/kitti_camera_lidar_v2/evaluation/kitti_camera_lidar_v2_sota_audit.yaml \
  docs/assets/kitti_board_camera_lidar/audit/kitti-board-camera-lidar-v1_sota_audit.yaml \
  docs/assets/mid360_imu_lidar_extrinsic_sota_audit.yaml \
  docs/assets/mid360_imu_lidar_extrinsic_v2_sota_audit.yaml \
  docs/assets/mid360_imu_lidar_sota_audit.yaml \
  docs/assets/ntu_viral_lidar_lidar_sota_audit.yaml \
  docs/assets/kitti_lidar_vehicle_sota_audit.yaml \
  docs/assets/ins_lidar_sota_readiness/evaluation/audit/ins_lidar_sota_audit.yaml \
  docs/assets/nclt_lidar_wheel/audit/nclt-lidar-wheel-odometry-v1_sota_audit.yaml \
  docs/assets/tumvi_camera_focal/audit/tumvi-camera-focal-check-v1_sota_audit.yaml \
  docs/assets/tumvi_camera_imu/audit/tumvi-camera-imu-check-v1_sota_audit.yaml \
  docs/assets/tumvi_camera_imu_v2/audit/tumvi-camera-imu-check-v2_sota_audit.yaml \
  --output docs/assets/sota_leaderboard.json \
  --target-pair camera-lidar --target-pair lidar-lidar --target-pair imu-lidar \
  --target-pair camera-imu --target-pair camera --target-pair camera-camera \
  --target-pair gnss-imu --target-pair ins-lidar --target-pair lidar-vehicle \
  --target-pair imu-vehicle --target-pair lidar-wheel_odometry \
  --markdown standings.md   # paste its tables into docs/benchmarks/sota_leaderboard.md

Checks before every push:

• .venv/bin/python -m pytest;
• ruff check .;
• uvx --isolated --with-requirements tools/typecheck-requirements.txt mypy src/calibrex (what CI runs);
• mkdocs build --strict.

The repository's own checks and PR template (.github/PULL_REQUEST_TEMPLATE.md) apply.

Spent data

A recording listed here has been read by the named pair's methods. It may be used for development; it is not evaluation data for that pair again. Reading by another pair's method is disclosed in exposure; it does not by itself spend the data for a new pair. The camera-imu v3 audit did exactly this with the camera-camera runs.

Dataset	Spent for	Recordings
KITTI raw	camera-lidar	All synced drives with at least 125 frames: the 36 of 2011_09_26, 2011_09_30_0018 and the 18 of v2 (2011_09_28, 2011_09_29, 2011_09_30, 2011_10_03). Shorter drives were never eligible.
KITTI raw	lidar-vehicle	2011_09_26 0005, 0009, 0014, 0015, 0022 (dev); 0027, 0028, 0035, 0039, 0046, 0051, 0057, 0059 (evaluation)
KITTI raw	ins-lidar, lidar-wheel_odometry, imu-vehicle	2011_09_26 0005, 0009, 0014, 0015, 0022 (tool runs, including the 0015 round trip; no audit)
KITTI raw	ins-lidar	2011_09_30_0018 OXTS, read by the generated-motion trajectory hand-eye performance controls; not independent calibration evidence
KITTI raw	ins-lidar evaluation v1	2011_09_29_0071, 2011_09_30_0020, 2011_09_30_0027 (first 600 scans and matching OXTS; alias 06 = 0020, alias 07 = 0027)
Boreas	ins-lidar development	boreas-2020-11-26-13-58 (INS prefix/calibration inspected and first-600-scan development acquisition; see the audit plan)
Boreas	ins-lidar evaluation v1	boreas-2020-12-01-13-26 (first 600 scans, full gps_post_process.csv and calibration; only the fixed +/-1 s reference window enters fitting)
KITTI-360	camera-LiDAR research	2013_05_28_drive_0000, 0002 and 0003 (the research plan records the materialized 0003 development capture; it was omitted from the original handoff)
KITTI-360	camera-lidar development	0000 and 0002 (22 segments), and 0004–0007, 0009, 0010 (41 of 42 segments; the owner could not rule out earlier reads, so these were never unread)
Hilti 2022	camera-imu	exp01-07, exp11, exp14-16, exp18, exp21, exp23 (parts 0-2); exp09 and exp10 never run (size)
Hilti 2022	camera-camera	exp05, exp06, exp09, exp10, exp11, exp14, exp15, exp16, exp18, exp23 parts 0-2 (first 5 GB of each), plus development on exp01 and exp21
MID360	imu-lidar	RTK-SLAM stadtgarten_seq1, stadtgarten_seq2, construction_seq1, construction_seq2 (every RTK-SLAM recording) and the Zenodo vehicle recording of the rotation audit
NTU VIRAL	lidar-lidar	rtp_01, spms_01, tnp_02 (evaluation), tnp_01 (development)
FAST-LIVO (Hugging Face MCAP)	camera-lidar, imu-lidar, camera-imu (tool validation, no audit)	hku1, hku2 (calibrex check runs recorded in the check tutorial), and the two halves of hku2
Newer College 2021	camera-camera, camera-lidar, imu-lidar, camera-imu, camera-focal (tool validation, no audit)	collection 3 math-easy part 1 (calibrex check run recorded in the check tutorial)
KITTI raw	board-based camera-lidar evaluation (refuted)	the five calibration recordings 2011_09_26_0119, 2011_09_28_0225, 2011_09_29_0108, 2011_09_30_0072, 2011_10_03_0058 (extract archives: grey stereo images, Velodyne scans and OXTS read by the frozen harness; the cameras' timestamp files read again afterwards for the diagnosis)
ACSC sample (Livox Horizon + checkerboard)	board-based camera-lidar development	the whole sample (21 board poses; board camera-LiDAR)
TUM-VI	camera-focal and camera-imu development	room1 (512_16 calibrated bag; camera-imu also with T_cam_imu turned 2 deg)
TUM-VI	camera-focal evaluation (supported; camera-imu ran with it, now camera-imu development)	room2, room3, room4, room5, room6 (read once by the frozen harness; pre-registration)
TUM-VI	camera-imu check evaluation (honesty supported, detection refuted)	corridor1, corridor2, corridor3, corridor4, corridor5 (read once by the frozen harness; pre-registration)
TUM-VI	camera-imu check v2 evaluation (--fail-on partial, supported)	slides1, slides2, slides3, magistrale3, magistrale5 (read once by the frozen harness; pre-registration); room1 read again for the harness's development run
NCLT	lidar-wheel_odometry development	2012-01-08 (from 60 s: 2, 10, 20 and 30 minutes; its ground truth read to find the converter's scan-period error)
NCLT	lidar-wheel_odometry evaluation (refuted)	2012-02-02, 2012-05-11, 2012-08-04, 2012-11-04, 2013-02-23 (one hour each from 60 s, read once by the frozen harness; pre-registration); afterwards development data for the within- and between-session analysis

The v2 camera-lidar runs also read the Velodyne and OXTS of the first 600 frames of its 18 drives. A lidar-vehicle or ins-lidar audit on those drives must disclose that.

Pitfalls met so far

• YAML 1.1 reads unquoted IDs as numbers.
• 2011_09_28 becomes the integer 20110928, and 0027 the octal 23. The v2 driver would have found no calibration pin and refused to run; a test caught it.
• Quote every ID, and test the loaded pre-registration's types.
• kitti_lidar_vehicle_preregistration.yaml has unquoted drive IDs. It is binding and must not be edited; read its IDs as written.
• Never edit src/ while a run imports it.
• Run long jobs from a separate git worktree with PYTHONPATH=<worktree>/src. The editable install is a .pth path entry, so PYTHONPATH wins.
• Check with python -c "import calibrex; print(calibrex.__file__)".
• Pickled option objects keep the defaults of the day they were pickled. When you replay saved estimator inputs, pass the current defaults explicitly.
• Disk. About 24-29 GB is free. Fetch only what the method reads; for KITTI that is the first 600 frames, because calibrex check reads at most 48 scans 1 s apart from the start. Delete each recording after its run.
• Zip archives.
• A zip64 archive can scatter one stream's frames across the file (2011_09_30_0018: 835 ranges for 600 frames); tools/kitti_drive_fetch.py handles it.
• Network drops do happen (curl exit 18). The pre-registered rerun policy covers a failed fetch.
• A near miss is still a miss. v2 failed one gate by 0.003 deg. Thresholds are not revisited after a run; a new version with new evaluation data is the only way on.

Next candidates

Development restart, 2026-10-27

The training-only initialization work reproduces all twelve archived audit verdicts from their stored scores and adds an opt-in, per-fold training-only initialization mode to the camera–LiDAR profile probe. It removes the pooled conditional-start dependency; synthetic tests are not real-data accuracy evidence. The fixed fourteen-input paired comparison has since been run on reacquired, separately identified captures (the original NPZ arrays were not recoverable): no overall improvement, and the research mode stays off by default (status). What remains open is research, not a pending run: why independently fitted folds select distant basins. No new evaluation data, audit verdict, threshold or estimator default changes; capture remains 2/55.

Follow-up recovery reacquired the two spent raw archives and matched their member inventories/CRCs and calibration SHA-256 pins. All fourteen native captures completed, with matching options/frame metadata, but all NPZ hashes differ. Native evidence has small objective/control-statistic differences exceeding the existing 1e-9 parity tolerance; transforms and discrete decisions match under that rule. The linked development page retains every difference and the failed download-cap attempt. Inputs now exist under /workspace/work/camera-lidar-recovery-20261027/capture/; resolve numerical parity before interpreting the initialization ablation. No new SOTA evidence is claimed.

The subsequent same-input code control at 78eeeae6 matches archived/current pooled profile evidence on all fourteen reacquired inputs at the unchanged 1e-9 tolerance. Historical cross-capture profile parity still fails on all fourteen. A separately scoped training-only comparison completes all arms and changes detected controls from 20/42 to 19/42: only 0005 roll +3's yaw control is lost, with two training-fold fits in distant yaw basins. Both arms retain zero detections on 0002, including missed pitch +3. Results and every fold are linked from the development page. Do not promote or retune thresholds from this result; investigate fold/basin stability and nuisance ambiguity next. Capture remains 2/55 and the historical numerical drift remains unresolved.

The control-seeded baseline ablation then removes the targeted pitch fold’s training-search deficit but still misses pitch +3 (t 0.774 to 0.848). Detected controls rise 19/42 to 26/42 while the worst active-axis training-fold reference disagreement among detected controls rises 0.350 to 8.165 deg. Reject promotion; investigate correspondence quality rather than spending another iteration on search or thresholds. All fourteen inputs and both arms are retained; no fresh evaluation or default change.

The local boundary tangent ablation uses PCA of depth-discontinuity points rather than the previous azimuth proxy. All fourteen original-arm parity checks pass; detected controls stay 19/42, but worst active-axis fold reference disagreement among detected controls rises 0.350 to 6.547 deg. Target pitch +3 still fails (t 1.298). Reject promotion; local direction penalties alone do not resolve correspondence ambiguity. All paired outcomes and the interrupted scheduling-only run are retained.

The bounded nearest-ridge distance ablation then replaces the scalar image response with a truncated distance reward. All fourteen original-arm parity checks pass, but controls decrease 19/42 to 13/42 (eight lost, two gained), with 0002 still 0/21. Worst detected fold reference disagreement decreases 0.350 to 0.246 deg, while target pitch +3 still fails (t -1.764) despite fitted pitch errors within 0.052 deg. Reject promotion; inspect actual wrong-pose image matches and temporal persistence before another objective variant. No new evaluation or default change.

The fixed-pose match diagnostic replays all six pitch folds on all eleven existing prepared frames. Small pitch errors hid baseline full rotation disagreements of 0.638–4.717 deg. At least one saved wrong control beats the reference in 5/6 pooled folds and 10/11 frames. Overlays show displaced points matching different road-side and vehicle contours. No fitting or threshold change: investigate boundary identity/structure, and report full rotation error in future ablations. Temporal score persistence alone cannot reject the repeated wrong-pose advantages observed here.

The local contour-coherence screen links mutual 3D neighbors and rewards their agreement on one image ridge component. It covers 93.05% of prepared points, but saved wrong controls still beat the reference in 5/6 pooled folds (frames improve 10/11 to 8/11). Reject integration before spending a full optimization batch. All six folds and eleven frames are retained. Component identity alone does not enforce neighboring-match geometry; direction, separation and collapse remain untested structural hypotheses.

The neighbor match geometry experiment adds direction/spacing preservation to the contour graph. Its fixed-pose screen reduces wrong-control wins from 5/6 to 1/6 folds. The frozen full fourteen-input paired search retains 19/42 detections (two gained, two lost); 0002 remains 0/21. Target pitch +3 worst full rotation error decreases 2.803 to 0.354 deg, but its control t=1.539 remains below 2.5. All-fold worst full rotation error is still 12.067 deg and computation is substantially higher. Retain experimentally, do not promote. All original-arm parity checks pass; future reports include full rotation vectors/norms to avoid hiding nuisance-axis errors.

The geometry failure cross-scoring finds explicit training-search deficits in the two lost 0005 controls: roll fold 1 and yaw fold 5 have roughly 2 deg baseline errors while saved scalar fits score about 0.092 higher under the geometry training objective. Their own profiled controls also beat the baseline on training frames. The 0002 pitch miss has no such deficit among inspected candidates; it remains a held-out ranking ambiguity. Next test bounded training-only control-seeded baseline restarts under the geometry objective; recovery is not established by cross-scoring alone.

The deficit-gated geometry restart experiment recovers both lost 0005 controls: 19/42 to 21/42, with all original nineteen retained and detected-fold full rotation disagreement unchanged at 0.296 deg. All fourteen geometry-control parity checks pass. 0002 remains 0/21; its targeted pitch t stays 1.539. Fifty axis-fold baselines change (two on 0005, 48 on 0002), and all-fold worst full rotation disagreement worsens 12.067 to 13.568 deg. Retain experimentally; no native default promotion or SOTA claim. The search regression is recovered, while difficult-scene correspondence ambiguity remains.

Camera–LiDAR priority reset (2026-10-28)

The external comparison reset supersedes further two-drive local tuning. Freeze the rotation-checker experiment at 308885cd (results 6b6379a9). Official Koide preprocessing and six-DoF calibration now execute on a three-frame spent-0005 smoke; exit 0, but reference rotation disagreement worsens 1.503 to 2.227 degrees and point-time warnings remain. This is execution evidence, not a fair comparison or successful recovery. Next deliverable: a shared spent-data six-DoF native-versus-Koide comparison, then required development coverage and learned-baseline execution. The fresh-data protocol remains a blocked draft; no fresh sensor payload was read. Existing 55-drive, exposure and independent-family requirements remain in force.

The shared-bundle follow-up now adapts the point-time origin while preserving acquisition times, and runs Koide and existing native Pandey MI on the same preprocessed cloud/image and seed. Rotation reference disagreements are 0.645 and 1.281 deg respectively (initial 1.503 deg); neither meets the scoped recovery event. This is an optimizer-only hybrid-pipeline diagnostic, not a D2D or independent end-to-end comparison. Next resolve cloud/camera reference-time alignment and independent image-depth input for the D2D release candidate, then expand spent-data coverage. Do not tune on the single shared bundle. Fresh evaluation data remains unread.

The motion-aligned stereo D2D execution now uses OXTS/IMU–LiDAR motion to express a scan at image time without the target camera–LiDAR reference, and stereo-only depth. On fixed spent-0005 frame 1, D2D has 1.110 deg / 0.274 m disagreement and Koide 1.374 deg / 0.195 m; both fail the scoped event. This is an assisted-input track, not an equal-information monocular comparison or the integrated-r5 release protocol. Next freeze a multi-interval, multi-drive development matrix; do not tune or repeat single-frame variants. Monocular depth/provider exposure, 55-drive coverage and learned baselines remain pending. Fresh evaluation payloads remain unread.

The frozen assisted-input matrix executed all 12 cases (two spent drives, three fixed temporal positions, two seed signs) from precommitted plan 6a1ff93d. D2D recovers 5/12, Koide 0/12; every execution completes with valid output. D2D improves rotation 12/12 but worsens translation 10/12. Unequal stereo input and custom OXTS preprocessing prevent a monocular-superiority claim. Next test joint estimation over the three frames per drive with unchanged inputs/seeds/gates, keeping this single-frame baseline. Do not tune thresholds or select successful cases. Development coverage is still 2/55; independent-family/learned-baseline/fresh-audit requirements remain unmet.

The joint three-frame experiment was frozen at 752c1f11 and completed all four drive/seed cases for both methods. D2D recovers 3/4 and Koide 0/4, with all three native frames supported. However, the predeclared translation comparison improves over the matching single-frame median only 1/4 and worsens 3/4: joint fitting did not establish translation stability. Do not compare 3/4 directly with the earlier 5/12 denominator. Retain experimentally, freeze settings, and broaden spent-drive coverage; no default promotion, seed cherry-picking or another two-drive parameter sweep. All existing 55-drive/learned-baseline/independent-family/fresh-audit requirements remain unmet.

The additional-drive joint experiment extends the fixed configuration to spent 2011-09-26 0009 and 0011, three fixed frames each. A preparation-only timestamp-gap bug was fixed and re-frozen at 9053ed48 before any calibration; original logs remain. All four new cases complete with all frames: D2D 1/4, Koide 1/4. D2D improves rotation 4/4 but worsens translation 4/4. Across four recordings/eight joint cases, D2D is 4/8 with translation improvement only 1/8; Koide is 1/8. Thus the translation regression persists outside the original pair. Retain failures and settings; next assess metric translation constraints together with depth/motion validity, not threshold relaxation or favorable-seed selection. Coverage remains only 4/55 with unequal stereo input; no superiority, independent-family or fresh-audit claim.

The metric stereo translation experiment adds opt-in, ROS-independent translation-only point-to-plane refinement, with D2D rotation fixed and no target reference in the fitter. Plan/source 9d01486a ran all eight joint initializers: all hit 15 outer iterations; none is accepted. Returned pipeline recovery stays 4/8 by exact D2D fallback, and new-stage success is 0/8. Raw candidates improve translation 5/8 and worsen 3/8, including 0011 positive from 0.136 to 0.340 m. All inner fits succeed and retain 2,000 matches per frame, so sparse support/rank checks do not establish reliability. Retain this negative result; do not relax criteria or promote the module. Next diagnose association stability and stereo-surface validity before further method claims.

INS-LiDAR after the first audit

The first two-family, two-platform rotation audit is refuted, 6/8. All eight estimated rotation axes agree within 0.286 deg and all eight observed controls pass, but KITTI 0071 has no observable rotation. Its zero-axis case is a failed scorable recording and gets the frozen worst-case control fraction of one. Do not reinterpret recording_completion=1.0 in the descriptive scorer as nonempty rotation availability: all four artifacts completed, but only three provide any calibrated rotation.

Post hoc inspection finds uncertainties of 0.378/0.226/1.225 deg against the 0.1 deg ceiling. The unobserved pitch/yaw differ by 0.558/1.976 deg; promoting them would not establish reliable calibration. The physical cause is not yet isolated. Use these spent windows to study informative motion, registration stability and a declared data-sufficiency policy. A new claim needs new held-out recordings and a new registration; no v1 gate or verdict may be relaxed.

The post hoc registration-quality comparison excludes four motions crossing the two unconverged scan registrations in 0071. It still observes zero rotation axes; uncertainty changes are small. The new exclude_failed_registrations option remains opt-in (default false), and this negative development result does not revise the v1 audit. Study errors in the remaining motions and block stability next; do not treat this filter as a demonstrated calibration improvement. The follow-up reproduces all nine native jackknife fits: omitting block 7 (35-40 s) changes the yaw component by 0.811 deg, although block 3 has the largest rotation residual. Residual ranking alone is not a justified block rejection policy; no such rule has been adopted. The subsequent two-arm translation-noise comparison reduces the unobserved yaw reference difference from 1.976 to 0.239 deg, but still has 1.056 deg uncertainty and fails the yaw control. Defaults are unchanged. An OXTS-only development acquisition of all 1059 samples finds the same 16.510 deg heading range as the first 600; no additional point clouds were acquired. These reference-only proxies do not decide observability or rule out a benefit from more samples. The complete 0071 OXTS recording is spent development data.

The published protocol replays the six achieved and two contradicted gates without sensor data. No calibration rerun is needed to reproduce the verdict.

1. camera-lidar v3 (closest to supported)

What failed in v2. The far-optimum mechanism. On 2011_09_28_0002, four turned runs took an optimum from the profile-maxima search start that:

• observed roll and pitch, against the candidate optimum's pitch alone;
• had roll's held-out control at t 2.58-2.65, just above the 2.5 bound;
• judged roll 1.45-1.50 deg off the day's calibration.

This is post hoc (v2 results). v1 failed the same way, one notch lower.

A rule to try. An optimum from a far start must clear its axes' controls with a margin well above the bound (for example t >= 3.5), or agree with the candidate optimum on the axes both observe. Weigh coverage: v2 already judges about 80 % of axes.

Development data. Every KITTI raw drive (55, all spent). The existing tools/kitti_camera_lidar_v3_replay.py captures seven real checks per drive and compares both rules on identical saved inputs. The 2026-10-23 native pilot completed 0005 with exact replay parity and no difference between rules. The 0002 comparison reduces maximum judged turned-run error from 1.503 to 0.100 deg, but loses the only counted 3 deg detection (1/1 to 0/1). Preselected yaw +3 and post hoc pitch +3 native checks both confirm the proposed replay's inconclusive result with no judged rotation axes. Do not describe this as an overall improvement or promote 3.5 from these data. 2/55 is incomplete; 53 remain. The original rounded-calibration guard failure is retained and its tolerance unchanged. Inspect the detection/coverage cost, including on spent 0034, and preserve the all-55 denominator and local NPZ inputs. Check free space before batches.

The post hoc start trace reproduces both selected controls under both rules with full evidence parity. Each has an unobservable candidate-start fit, a rejected one-observed-axis profile fit, then a two-observed-axis fit. The latter's minimum control t is 2.6211 for pitch +3 versus 2.6493 for yaw +3: a scalar margin retaining the former also admits the latter's erroneous roll. The pitch fit also has an erroneous roll; keeping detection alone does not fix accuracy. Develop a different start/axis evidence rule on cached spent inputs before spending disk and bandwidth on the remaining batch. Do not simply relax the two-axis requirement: the earlier 0056 single-axis false estimate motivated that guard.

The conditional-axis probe then ran all 14 cached inputs (42 one-axis fits). It recovers pitch +3 on 0002 with +0.15 deg active-axis reference error and t=3.3036, but a conditional std of 0.0417 deg hides a 7.8 deg nuisance-sweep span. All 18 fits meeting the ordinary conditional evidence conditions have active-axis error at most 0.15 deg, yet these separate fits are not joint observability, native verdicts or a promoted method. The tool and byte-bound batch are available for research; account for uncertain nuisance axes before adoption. No fresh data was read; capture progress stays 2/55 and 53 remain.

The training-only nuisance-profiled controls use committed source 7a6ea534 and all 14 cached inputs. At the same refitted fold poses, direct/profiled controls detect 25/42 versus 21/42 axes (control outcomes only, no std/coverage/verdict gate). Four 0002 pitch controls lose detection, but its roll +3 still passes with profiled t=3.158 and about 1.5 deg maximum absolute roll reference error among the saved fold fits. This is not an accurate-calibration guarantee or a promoted method. Probe broader nuisance basins before setting new gates. All outputs and this counterexample are retained; the pooled conditional initialization means these are not nested validation folds.

The follow-up opt-in --multi-start uses source 24543be7, fixed before all 14 cached inputs were re-run. Training-only nuisance profiles plus their individual/combined starts retain the original local optimum on ties. Paired baseline/direct evidence matches within 1e-9. The only changed detection is the known 0002 roll +3 false control: t falls from 3.158 to 1.732 and fails the unchanged 2.5 threshold. All 0005 flags stay unchanged. Profiled controls now detect 20/42 instead of 21/42, with zero on 0002 and pitch +3 still missed. This exposes a selected ambiguity; it does not correct the saved fits, provide native verdicts, recover useful coverage, or justify promotion. Both batches and their source capsules are preserved. Capture progress remains 2/55.

The fixed 2x2 spatial-weight ablation preserves frame totals and candidate-outside support, but does not restore 0002 pitch detection. Detected multiple-start controls fall from 20/42 to 12/42 (0005: 20 to 12; 0002: zero in both). Do not adopt it or relax thresholds from this negative result. Source 50c77d37 first failed on all 14 inputs because it rejected the intentionally retained image margin; that attempt is preserved. The fix at 67ff8c5d was frozen before the complete fourteen-input retry, which binds the original failed report and unchanged inputs/settings. This is control evidence, not a native coverage or accuracy claim; 53 drives and the separate pre-registration remain pending.

The projected-azimuth orientation proxy was frozen at c237f78d before six selected inputs (baseline, pitch +3 and roll +3 on each cached drive), using two independent workers. It compares image gradients to a scan-direction proxy, not actual boundary normals. Scalar/proxy controls detect 8/18 versus 0/18; 0002 pitch stays missed. Do not adopt or tune this proxy from the result. All six outputs and a separate default scalar-mode replay are retained; the latter matches previous numerical evidence excluding provenance within 1e-9. No new drive, fresh evaluation, SOTA gate or default changes; capture progress remains 2/55.

Evaluation candidates. KITTI-360 (another car, sensor set and calibration) is the natural choice: sequences 0004-0007, 0009 and 0010, subject to completing the exposure audit. Sequence 0003 is spent: the research plan already records a development capture. The original handoff's claim that it was unread was incorrect.

Access update, 2026-10-23. The local recheck verified exact official metadata ranges for 21 archives; the earlier cloud 403 remains historical evidence. Published-pose and explicit raw-OXTS conversion both passed three-frame checks on spent 0000 and 0002. OXTS uses its own clock and recorded origin without consuming optimized published poses. Provisional candidate sensor contents remain unread; exposure auditing is incomplete and no evaluation has started. This is converter readiness, not accuracy evidence.

Work needed first.

• ~~Capture and compare all 55 spent KITTI raw drives using the existing tools/kitti_camera_lidar_v3_replay.py~~ done 2026-10-31 (see the last entry); a selected new rule still needs confirmation via the real driver.
• ~~Complete exposure auditing~~ done in git history 2026-10-31. On 2026-11-01 the owner answered that work outside git opened candidate sensor data or may have, and does not know which sequences. All of KITTI-360 0004–0010 are treated as possibly exposed: development use only. A v3 camera-LiDAR claim needs unread recordings from elsewhere. The independent-platform requirement remains: KITTI-360 sequences alone do not add dataset families or rigs, so a KITTI-360 v3 claim is scoped to that rig.
• ~~KITTI-360 has few, long sequences: pre-register several disjoint 60 s segments per sequence, chosen by a rule from metadata~~ fixed 2026-10-31: 42 evaluation and 22 development segments (exposure audit and segments).
• ~~Run the check on the 22 spent 0000/0002 segments and derive gates~~ done 2026-11-01: the default rule flags the vendor calibration on 0002-s04 (yaw −0.60°, std 0.042°) against a gate allowing none. Cause (post hoc, spent data): a yaw bias of about 0.6° that lasts the whole minute on hedge-lined, turning residential streets; the block jackknife cannot see a shared bias. Sync and deskew were checked and are fine. No threshold was changed. Next: find unread recordings outside KITTI-360 for a v3 claim, and give any claim a vendor-flag allowance set before evaluation.
• Unread-data candidates for a v4 claim (survey), 2026-11-01: Argoverse 2 (primary) and Boreas (second family). Both can be listed anonymously. The owner cannot confirm exposure outside git and chose to use them with that disclosed.
• Multi-window check (protocol and result), 2026-11-01: median of disjoint 60 s windows, tolerance from their spread. On the 42 former candidate segments all six criteria held, but 0009-s07 could not run (official OXTS archive lacks frame 8849), so it is not carried forward. Post hoc: it removes single-window errors up to 4.75° and the 1° judged-right cases. Single windows flagged no vendor calibration there either. All KITTI-360 data are now spent.

2. ins-lidar follow-up

Audit update, 2026-10-22. The first rotation audit is refuted (6/8), as described above. Boreas 2020-12-01 and KITTI 0071/0020/0027 are now spent evaluation recordings, not unread candidates. The audit plan retains the independent-Applanix adapter and failure-aware scoring. A follow-up needs development on spent recordings, new held-out data and a new pre-registration. Preserve two dataset families and two platforms; different dates of one rig are not independent rigs. Clock accuracy was outside the first rotation claim.

The native trajectory hand-eye on KITTI 0005+0009 constrains roll, pitch and the clock offset, but not yaw or translation (KITTI INS-LiDAR). A per-axis honest claim, as camera-imu v3, could gate what is judged plus coverage. KITTI drives of the other days are unread by INS-LiDAR methods; disclose the v2 camera-lidar reads.

3. The refuted pairs

• camera-camera needs better 1 deg detection on Hilti before a new round.
• lidar-lidar needs cross-recording consistency, and a comparison with scan-to-scan that the method wins.
• camera-imu check (TUM-VI): v1 passed a 2 deg turn whenever the turned axis was unchecked. --fail-on partial (v2, supported) flags such a pass. The remaining unseen TUM-VI sequences (magistrale1, 2, 4, 6 and outdoors1-8) are 11-31 GB each.

4. Lower priority

• imu-vehicle: no axis was constrained on KITTI; it needs data with excitation.
• lidar-wheel_odometry: needs real wheel odometry.
• gnss-imu: only composed from other pairs so far.

Open work not in this handoff

Draft PRs #202, #205, #206, #208, #211 and #213 (CUDA, B-spline and LiDAR-IMU performance) are being consolidated by another session. Leave them to it.

Stereo translation diagnostic follow-up (2026-10-29)

Post-hoc replay of all eight rejected trajectories reproduced 120 saved inner costs. In each case's last five updates, selected-pair retention averaged only 6.8–16.2%; 40.1–75.5% of previously selected exact pairs were still eligible but excluded by uniform-index resampling. This establishes sampling churn, not its causal share of non-convergence or calibration error. The next controlled spent-data comparison is deterministic point-identity sampling with all other settings fixed, across all eight cases. Original acceptance remains 0/8. See the replay evidence.

Fixed point-priority comparison (2026-10-29)

Eight-case controlled comparison, frozen at c003dae8: changing only the sampling rule raises late-update selected-pair retention to 49.1–97.3%, and eligible-but-unsampled losses fall below 0.3%. Acceptance rises to 1/8, but that case worsens reference translation by 3.24 cm; returned-pipeline recovery stays 4/8. Seven still fail convergence. Keep the uniform default and rejection gates. Sampling stabilization alone is insufficient; next investigate surface/depth consistency and frozen-rotation sensitivity.

Reference-assisted consistency controls (2026-10-29)

Diagnostic controls, frozen at 84e87282: substituting reference rotation yields only 1/8 converged. Starting at the full reference pose drifts 3–13 cm on all four distinct recordings (three reach the iteration limit). All 12 distinct frames have negative median LiDAR-minus-stereo z residuals at reference, −0.119 to −0.056 m on gated pairs. This rules out fixed D2D rotation as a sufficient explanation, but does not isolate stereo bias. Next audit depth generation, camera/reference coordinate conventions and temporal alignment before another solver variation. Reference-assisted controls are not deployable calibration scores; earlier verdicts remain unchanged.

Stereo projection conversion fix (2026-10-29)

Projection audit found a concrete frontend bug: fx*baseline/disparity omitted the right-pixel term for unequal camera z offsets. Corrected full-projection depth conversion is tested with known geometry. On existing pairs it changes 0002 depth by −3.25 to −3.59 cm at the median, but other drives by less than 0.34 mm. All residual medians remain negative. Reference transforms and source stereo timestamp identities agree; physical point timing has not been independently validated. Median predicted vertical stereo mismatch is 0.133–0.288 px; next compare proper stereo rectification before more solver changes. No historical arrays, calibration verdicts or gates were modified.

Stereo re-rectification comparison (2026-10-29)

Frozen comparison at bae08665: 12 frames, two frontends, eight unchanged D2D initializers. Re-rectification reduces gated median z residual magnitude in 11/12 frames, but valid pixels drop in all frames. Both it and the corrected-projection control reject all eight translation fits for max iterations; returned recovery stays 4/8. Raw candidates improve in five and worsen in three relative to control. No promotion or verdict change. Next inspect stereo correspondence consistency and disparity-dependent residuals, retaining support and downstream calibration as required outcomes.

Independent stereo round-trip diagnostic (2026-10-29)

Diagnostic, frozen at ae87b4f0: all 12 forward depth arrays reproduced exactly. Of 183,329 projected stereo-supported points, 90.5% satisfy independent 1 px reverse consistency, 1.6% contradict and 7.9% lack reverse support. Consistent populations have lower absolute-z p90 in all frames, but all retain negative median residuals. At <8 px disparity, per-frame consistent median z residuals are −6.71 to −3.53 m without a depth gate; visibility/timing/reference effects remain unresolved. Next test the frozen reverse-consistency mask across all eight fits without fitting range cutoffs to these results. No optimizer rerun, production change or accuracy claim this step.

Fixed stereo round-trip mask comparison (2026-10-29)

Eight-case comparison, frozen at 0bb89aa4: the 1 px mask retains 84.4–89.1% of depth pixels and 83.7–88.9% of surface pixels. All eight fits still reach max iterations, despite 2,000 matches per frame at every update. Raw candidates improve in five/worsen in three versus unmasked; 0011-positive worsens from 0.3244 to 0.4546 m. Accepted stage 0/8, returned recovery 4/8 via exact D2D fallback. Do not promote the mask or relax convergence. Close this sequence of frontend tweaks: next broaden to other spent recordings and compare an alternative measurement model before further tuning. The projection formula fix remains valid, but downstream benefit of later frontend variants has not been established.

Broader six-DoF measurement-model comparison (2026-10-29)

0013/0015 comparison, frozen at fa09ba7e: two additional spent drives, three metadata-selected frames each, two unchanged seeds, eight completed/converged solver runs. D2D recovers 1/4, improves rotation in 4/4 but worsens translation in 4/4. Native Pandey recovers 0/4; its 0015-negative solution has 17.4007-degree reference rotation difference despite convergence. No defaults/gates promoted. Sparse assisted-input comparison coverage is now six recordings, not completion of all-55 capture/replay. Next prioritize independently validated full-pose quality/rejection, preserving both coverage and false-acceptance evidence; convergence alone is demonstrably unsafe as an accuracy criterion. No held-out audit or SOTA claim.

Joint inverse-depth pose estimator (2026-10-29)

Six-drive/twelve-case experiment, frozen at 517c4eb6: a new experimental ROS-independent six-DoF solver uses bilinear pixel-scaled inverse-depth residuals and fixed LiDAR populations. Synthetic known planes recover all axes; unobservable/missing-depth tests reject. Real recovery is 1/12 versus matched-input D2D 5/12. Eight new fits lose required support; four pass numerical checks, but three of those fail reference accuracy gates. Do not promote, relax retention or call SOTA. Next address explicit visibility and missing-depth boundary continuity, with controlled hole/occlusion tests and independent full-pose validation. Preserve the negative result and original inputs.

Continuous support weighting result (2026-10-29)

Controlled twelve-case test, frozen at c9f24ea1: continuous sin/cos measurement/missing-support blend passes synthetic hole/step continuity and known-plane recovery tests, but real recovery falls to 0/12 (hard mode 1/12, matched D2D 5/12). Five numerical accepts all fail accuracy gates; remaining statuses are three lost-support, two budget exhaustion and two bounds. Do not promote or relax gates. Stop extending this image-support penalty approximation; next require independently supported correspondences and actual geometry recovery through controlled holes/occlusions, not continuity alone. Historical outputs remain unchanged; no fresh data or SOTA claim.

Surface-registration comparison (2026-10-29)

Single-frame ICP/D2D comparison, frozen at 464279c5: existing Chen–Medioni tangent-plane ICP with mutual matches, trimming and spatial holdout passes five geometric hole/occlusion/overlap tests, but recovers 0/12 on central real frames versus matched single-frame D2D 3/12. Seven ICP fits converge inaccurately; five reach the iteration limit. All have rank six and 0.0317–0.0712 m holdout plane RMSE. Same-stereo-surface holdout is not independent calibration validation. No defaults/gates promoted. Next challenge the shared stereo reconstruction using an independently specified measurement source, not another association/penalty variant on these same depths. Historical joint D2D 5/12 remains a separate three-frame result.

Independent image matcher comparison (2026-10-29)

ZNCC/SGBM comparison, frozen at ae028fc7: same six central frames, re-rectification, twelve seeds and D2D settings. All 24 fits converge; full-pose recovery is SGBM 2/12 versus ZNCC 1/12. On exact common projected points, ZNCC improves median residual magnitude in 5/6 but worsens absolute p90 in 5/6 and loses substantial depth coverage everywhere. Do not promote. Negative common-point medians persist in both; causality remains unresolved. Next establish a published modern stereo/cross-modal model's pinned code/checkpoint/license/training exposure/runtime before further comparisons. Do not continue classical matcher/penalty tweaks as a substitute for SOTA evidence. No new held-out data or historical verdict change.

Published learned stereo runtime (2026-10-29)

UniMatch runtime, protocol frozen at 3a9d60e8: official SceneFlow GMStereo-scale2-regrefine3 checkpoint and source commit pinned; MIT source license and separate checkpoint-license uncertainty documented. Strict weights-only loading and native-resolution spent 0005/frame-76 CPU smoke succeeded: 17.24 s, 1242×375 output, all finite. This establishes runtime readiness, not depth accuracy, calibration recovery or contemporary SOTA. Next freeze and complete the same six-central-frame/twelve-seed D2D comparison against re-rectified SGBM (2/12), disclosing RGB versus grayscale inputs and preserving failures. No new data, thresholds or production defaults changed.

Learned stereo full-pose comparison (2026-10-29)

UniMatch/SGBM comparison, frozen at 2f73c756: six native-resolution image pairs, twelve matched single-frame D2D cases, all 24 converged. Recovery remains 2/12 versus 2/12; UniMatch gains 0009-negative and loses 0002-positive. Translation improves 10/12 (median 0.2771 → 0.2131 m), rotation only 6/12 (median 0.7135 → 0.7565 deg). More valid depth everywhere does not establish calibration success. All twelve recomputed SGBM outputs exactly reproduce the prior control. No default promotion or SOTA. Next pre-register matched three-frame joint learned/SGBM comparison using only the archived frames; recompute both frontends and preserve all seeds/failures. Do not compare against historical three-frame 5/12 as if inputs were identical.

Three-frame joint learned stereo result (2026-10-29)

Joint comparison, frozen at 1948a499: 18 pairs and 24 completed/converged fits. Matched re-rectified SGBM recovers 6/12, UniMatch 5/12. Translation improves 8/12 (median 0.2190 → 0.1834 m), rotation only 2/12 (median 0.3096 → 0.3684 deg). UniMatch has more valid depth in all 18 frames but no full-pose advantage. Six central-frame depth pairs exactly reproduce the prior experiment. Do not promote, relax the 0.2043 m near miss, or confuse this matched SGBM 6/12 with historical differently processed 5/12. Close matcher/aggregation trials. Next use independently generated known camera and LiDAR geometry to test the same joint solver with exact and perturbed depth, non-planar surfaces and controlled visibility before choosing another algorithmic change. Such a control is diagnostic only, not new real-world/SOTA evidence.

Independent known-geometry control (2026-10-29)

Results, frozen at 9ffd9aee: analytic camera/LiDAR raycasts from distinct origins, five spheres plus slanted plane, three views, five measurement/visibility conditions. All 15 fits converge but perturbed recovery is 1/10 (reference-start 5 trials kept separate). Even exact optical z plus oracle visibility fails both perturbations; truth-start drift is only 0.035 deg/6.25 mm. Ground truth has higher MI than every returned perturbed fit, proving a feasible better objective was missed on this scene, not proving the global optimum equals truth or explaining all real failures. Constant +0.25 m shift gives identical traces due to histogram shift invariance. Next test deterministic broader search against unchanged objective under a stated equal evaluation budget on frozen controls before revisiting real data. Preserve baseline, all starts, runtime and truth-start drift; no reference-guided seeds. Stop further stereo replacement as a presumed cure. No production/SOTA change.

Equal-cap fixed multistart result (2026-10-29)

Results, frozen at b221d707: same objective, original global bounds and 800-call ceiling; one start versus five fixed starts at 160 each. All 15 baselines/75 starts executed. Perturbed accepted recovery 1/10 → 0/10: all ten selected candidates exhaust their per-start budgets. Geometry-only pass count improves 1→5 but must not be called recovery. All-return reference-start drift worsens to 0.8646 deg despite higher MI; other four match baseline. Equal ceilings are not equal work (perturbed 193–337 vs 800 actual calls). Baseline outputs exactly reproduce prior study. Reject promotion/real-data rerun. Next allocation must preserve converged baseline and explicitly count remaining exploration/refinement work; retain visibility/drift controls because higher MI alone is unsafe. No reference-guided starts or after-result tuning.

Baseline-preserving continuation (2026-10-29)

Results, frozen at 420daa35: unchanged starts/objective/bounds, full baseline plus four ≤40-call probes, remaining calls to highest-MI explorer with exact state continuation. Converged higher-MI results only; otherwise exact baseline fallback. Recovery 1/10 → 5/10, all positive seeds pass and all negative seeds fail. All refined explorers converge; total 353–689 ≤800 calls. Six baseline fallbacks/nine replacements, exact baseline reproduction. Truth-start controls 5/5 → 4/5: all-return case now converges wrongly at 0.8560 deg/0.1427 m. Budget issue resolved; MI-only selection remains unsafe. Do not promote or rerun real data as a validated improvement. Next freeze reference-free geometric candidate validation on disjoint analytic LiDAR samples, retaining occlusion/unsupported populations and correct/wrong candidate controls. No real/SOTA claim; conditions/seeds are dependent, not independent scenes.

Disjoint geometric validation fails (2026-10-29)

Results, frozen at 3249838a: 40 fixed candidate checks on new angular LiDAR rays, no camera-occlusion filtering, reference-free per-frame median/p90/support criteria. Accepts 16/20 accurate and 2/20 inaccurate poses; rejects four correct biased-depth candidates. Crucially the all-return truth-start drift (0.8560 deg) PASSES, as does exact-range negative continuation (0.5731 deg). Shared camera depth/scene means disjoint samples are not independent sensor evidence; aggregate residuals do not bound pose error. Do not promote, retune thresholds or call continuation safe. Next compare fitting metric geometry versus MI using only original fitting samples, unchanged initial poses, fixed budget, occlusion/bias controls; reserve these points for diagnostics. Freeze estimator first, keep full-pose labels and baseline; no heldout-guided parameter selection. Synthetic results remain development evidence, not SOTA.

Direct metric-depth fitting (2026-10-29)

Results, frozen at d6651dd8: fixed-population bilinear optical-z soft-L1/TRF fitting, all original samples and unchanged pose bounds/gates. Recovery MI 1/10 → metric 6/10, both signs succeed for visible exact z, radial depth and holes. All-return occlusion fails 2/2 (~0.752 deg); +0.25 m depth bias fails 2/2 (~0.222 m). Truth-start controls regress 5/5→3/5. All 15 metric fits converge/retain support, 111–202 actual residual calls. Frozen holdout happens to agree for these outputs but retains its known false-accept limitation. Do not promote, relax gates or claim SOTA. Next isolate physically motivated non-oracle visibility handling on additional analytic controls, retaining visible-only recovery and truth-start drift checks; assess depth-bias/translation confounding separately rather than adding both mechanisms at once. Baseline exactly reproduced; no core/default changes.

One-sided metric occlusion control (2026-10-29)

Results, frozen at a2e22ce5: three fixed sphere arrangements, visible/all-return populations, both signs + true starts, 36 fits. Supported positive residual r becomes r/sqrt(1+(r/.2)^2); negative and unsupported penalties unchanged. Perturbed recovery 8/12 → 12/12; all-return 2/6 → 6/6, visible stays 6/6. True-start controls 4/6 → 6/6, though nonzero drift remains. Original visible-only accuracy worsens ~0.14→0.20 deg while still passing. All asymmetric fits converge/retain support, 131–238 calls. Original symmetric results exactly reproduce. Positive synthetic result only: no production or SOTA claim. Next isolate depth-bias versus translation confounding with fixed visibility handling, zero/positive/negative bias and truth-start controls; test observability before accepting a fitted nuisance bias. No further saturation tuning.

Japanese development review (2026-10-29)

Japanese brief summarizes evidence through 064ea6f3, separating real-data and analytic controls, adoption limits and the unexecuted depth-bias/translation-identifiability experiment proposal. Printable HTML and three-page PDF are shareable reading copies. This documentation adds no new experiment or accuracy claim.

Depth bias versus translation (2026-10-29)

Results, frozen at 9bee5c16: the frozen one-sided fit plus 0/+0.25/−0.25 m constant camera-depth bias on the three layouts, both populations, signed and truth starts. 210 fits plus 84 sensitivity checks, no failures dropped; zero-bias results reproduce the prior run exactly. Pose-only: positive bias fails 0/18 (Δt_z ≈ 0.85–0.97 b, 15 failures converge), negative bias passes 18/18 only because saturation masks it. Local sensitivity at truth calls every condition distinguishable (e ≈ 0.90–0.94) yet predicts only 0.10–0.18 b translation shift, so it is not a safety check. Joint pose+bias fit: pose 66/66, bias within 0.05 m only 22/66; every estimate trades β̂ − b ≈ −Δt_z (4–7 cm), zero-bias translation error grows to 4.4–8.5 cm. Verdict not_supported: do not adopt the bias variable or widen its tolerance. Positive depth bias remains a blocker before real-data reruns. Next work needs a new frozen protocol (zero-bias β/t_z offset source, trade-breaking geometry, or bias detection with wrong-candidate controls). No production or SOTA change.

Depth-bias response and local confounding (2026-10-29)

Results, frozen at ae51adee: fixed visibility solver, 3 layouts × 2 populations × biases 0,+.25,-.25 m × ± seeds/truth start =54 fits. Perturbed recovery: 12/12, 0/12, 12/12 respectively; truth-start 6/6,0/6,6/6. +bias median z displacement +0.2236 m; -bias tolerance is influenced by positive-residual saturation, not estimated correction. All 18 zero-bias outputs exactly reproduce. Three +bias runs hit max_nfev; other 51 converge, 86–592 calls. Raw Jacobian bias unexplained fraction .9539–.9842 (no <.05 flags); planar control correctly exposes degeneracy. Local raw rank does not prove robust/global bias identifiability. Next freeze experimental seven-parameter pose/bias fitting with zero correction initialization, separate bias/pose scoring, raw+robust sensitivity and plane degeneracy controls. Preserve fixed six-parameter baseline, no truth-fed bias or holdout tuning. Review PDF remains historical; stages A/B completed, C pending.

Joint pose and depth-bias estimate (2026-10-29)

Results, frozen at b58e9d93: correction initialized at zero, fixed ±.5 m bound, same asymmetric depth objective, 54 sphere fits plus 9 plane controls. Perturbed pose-only recovery 24/36→36/36 (+bias 0/12→12/12), but pose+bias recovery only 12/36, truth-start joint 6/18. All sphere fits numerically converge/pass local rank; every estimated bias is too low by .0408–.0668 m, including clean measurements. Only staggered layout meets joint bias gates. All nine plane fits converge but are correctly flagged degenerate; none accepted jointly. 8–566 optimizer calls, no failures omitted. Do not promote, relax bias gate or empirically subtract the observed offset. Next freeze analytic first-surface depth-sampling diagnostic versus bilinear pixel sampling to isolate model mismatch, keeping fixed seeds/objective and all bias/occlusion controls. Oracle sampler is diagnostic only; rank does not imply unbiased estimation/SOTA.

Analytic depth-sampling control (2026-10-29)

Results, frozen at b355c938: same solver function definitions, only bilinear sampler replaced by known first-surface raycast. 54 sphere cases, archived baseline pinned. Joint recovery 12/36→33/36, truth-start 6/18→11/18. Median bias error .05590 m→.00000948 m; zero-bias max .000341 m, strongly implicating pixel/bilinear approximation in previous systematic offset. Do not omit failures: four max_nfev, six negative-bias truth starts converge with wrong bias (up to .24990 m). 50/54 converge; 8–639 actual calls. Oracle is diagnostic only, not deployable or real-data evidence. Next separate boundary-aware image-only sampling from investigation of exact-sampler negative-bias truth-start derivative/ stopping failures; do not change both together or relax gates. Keep all six wrong-bias truth starts as controls. No production/SOTA claim.

Analytic truth-start stopping diagnosis (2026-10-29)

Results, frozen at bf5d96e0: no new fits; 18 truth-start cases probed at initial/final poses, 3 finite-difference steps and fixed bias grids. All six negative-bias failures stopped by xtol despite positive exact bias gradient 233–247; -.01 m bias step lowers cost in all six. Pose probes at 1e-8 cause >1 m residual jumps for one point with unchanged support, maximum Jacobian singular values ~1e9 and forward/central disagreement ~1. Bias derivatives remain smooth and agree with analytic values. First-surface silhouettes cause real discontinuity even without pixel interpolation; rank is not smooth covariance. Evidence identifies a local-linearization mismatch, not every internal SciPy cause. Next freeze separated scalar bias updates versus pose updates under one counted budget, original objective/samplers and all controls; require actual cost decrease. Do not use injected bias or mix in boundary-aware sampling/tolerance changes. No revised recovery, production or SOTA verdict.

Separated bias/pose blocks fail overall (2026-10-29)

Results, frozen 91e7aecb, serialization-only fix c2409b5c (initial plan/traceback retained). Same analytic objective/sampler, scalar bounded search then pose-only TRF, ≤800 shared calls/eight cycles. Perturbed joint recovery 33/36→0/36, all 36 capped; geometry+bias alone passes 18/36 but not accepted. Truth starts 11/18→17/18; negative truth starts recover bias in 6/6, only 5/6 converge. 33 regressions/six gains, actual 19–785 calls, no gate relaxation. Reject full block replacement. Preserve joint baseline; if pursuing scalar rescue, use residual-based trigger and remaining budget after completed joint fit, retaining fallback and all regression controls. No truth-label/bias-guided triggers or combining sampler changes. Monotonic cost is not proof of pose accuracy. No production/SOTA.

Baseline-preserving scalar rescue (2026-10-30)

Results, frozen cb8c265c: unchanged joint fit first, residual-only ±.01 m probes, fixed-pose bounded bias correction using remaining shared 800-call budget. All 54 baseline records exactly reproduce; all output poses identical to baseline. Perturbed joint recovery 33/36→33/36, truth starts 11/18→17/18, six gains/no regressions. Six triggers/adoptions, bias errors .000218–.006862 m; 11–639 calls. Four previous unconverged cases remain failures. Staged joint termination + scalar termination does not prove new joint stationarity. Oracle-only synthetic evidence, no production/SOTA claim. Next prioritize image-only sampling versus the frozen bilinear baseline, with full bias/occlusion/truth-start and planar controls; do not tune the four oracle failures or combine sampler/rescue changes in one unattributable comparison.

Image-only edge-preserving depth sampling (2026-10-30)

Results, frozen 8a9babf4: nearest-pixel anchor, retain 2x2 neighbors within .2 m optical z and renormalize bilinear weights. No scene/oracle information, no scalar rescue; identical joint solver functions. 54 sphere + nine plane cases. Perturbed joint recovery 12/36→32/36, truth starts 6/18→10/18, median bias error .055900→.002071 m. All sphere poses pass pose gates and numerically converge. 26 gains but two regressions: staggered negative-bias truth starts both populations. Six negative truth starts, four positive-seed and two original positive truth starts still fail bias gate. Nine planes remain rejected as degenerate; 8–201 calls. Do not promote or relax thresholds. Next isolate residual-triggered scalar rescue with this image-only sampler, full 63-case denominator and shared budget; keep all failures and report staged termination honestly. No real-data or SOTA claim, core/defaults unchanged.

Scalar rescue with image-only sampling (2026-10-30)

Results, frozen 0b0fa0bb: unchanged rescue algorithm, imports switched to image-only sampler/joint fit. All 63 baseline records reproduce exactly, all poses unchanged. Perturbed joint recovery 32/36→32/36, truth starts 10/18→16/18, six gains/zero regressions. Six negative-bias truth starts recover, including the two earlier regressions. Eight triggers/adoptions; two positive-seed corrections improve but still fail. Six sphere failures remain, including two >.05 m near-threshold failures. Nine planes stay rejected. 8–215 optimizer calls, median bias error .002071→.001974 m. Staged termination is not new joint stationarity; no production/SOTA claim. Next prioritize a frozen transfer comparison on existing spent real recordings, fixed sampler/rescue versus comparable bilinear metric baseline, full drives/seeds, truth-start drift and rejection/runtime reporting. Real depth lacks synthetic bias truth. Do not tune the six synthetic failures or spend fresh holdouts first.

Real-data metric transfer fails (2026-10-30)

Results, frozen 1ceb2d52: six spent KITTI drives × positive/negative/reference starts × bilinear/edge/edge+rescue, 54 fits, three archived restored-SGBM frames per drive. Fixed 4096 file-order points/frame, 102 input files hash-verified. Perturbed accepted recovery is 0/12 for all three. Reference starts 1/6, 3/6, 3/6; perturbed translation median worsens .309→.507 m with edge sampling. Rescue triggers/adopts 17/18 but poses are unchanged, so no recovery gain. All nested edge baselines reproduce; 81–192 / 57–151 / 90–170 calls. Synthetic gains do not transfer; reject adoption. Historical MI 6/12 is not a matched baseline because objective and point sampling differ. Next freeze reference-vs-fit cost/support/signed-residual diagnostics and a matched MI control on the same selected inputs before choosing another optimizer or frontend. Do not tune synthetic thresholds, infer bias accuracy from unlabeled real depth, or spend fresh holdouts. Core/defaults unchanged; no SOTA claim.

Matched-input MI and real cost diagnosis (2026-10-30)

Results, frozen 4a1cf7b8: 18 MI fits on the same 4096 file-order points/frame as metric transfer, plus four fixed-state cost/support probes of all 54 archived metric fits. MI recovery 1/12, reference controls 5/6, all converge. Historical full-cloud MI 6/12 is not this selected input's baseline: sampling cannot be assumed harmless. At equal fitted bias, inaccurate fits still beat reference cost on common support in 17/18 bilinear, 13/18 edge, 12/18 rescue cases. Reference zero-bias support only 1414–1737/12288, median >1 m residual fraction ~22%. Recomputed costs match archive. Do not infer one exclusive cause or global minima; no adoption/SOTA claim. Next freeze full-cloud matched MI/metric control on the same spent recordings, including both seeds and reference starts, to resolve the input-population confound before changing the objective or consuming fresh data. No optimizer/ threshold tuning; preserve low-cost inaccurate cases as evidence.

Full-cloud control rejects the metric path (2026-10-30)

Results, frozen 07398b48: 54 full-cloud fits, same six drives, three frames and 18 starts; 107739–124044 points/frame. MI historical result records reproduce exactly 12/12, perturbed recovery 6/12; bilinear and edge+rescue remain 0/12. Reference controls MI 5/6, bilinear 1/6, edge+rescue 0/6. Thus thinning harmed MI but does not explain metric failure. Sixteen scalar adoptions leave poses unchanged. Common-support, equal-bias wrong-pose cost preference remains 17/18 bilinear and 15/18 rescue. All budgets/hashes/counts verified; no defaults/adoption/SOTA claim. Close sampler/scalar tuning. Next independently specify a stereo uncertainty control (range-dependent depth error from disparity noise) on known geometry, fixed noise/occlusion conditions and unchanged regression controls, before any real-data retuning. Keep full-cloud MI as baseline; do not fit noise thresholds to these spent real cases or consume fresh holdouts as development data.

Stereo uncertainty normalization rejected (2026-10-30)

Results, frozen 2eb1336d: 342 paired synthetic fits, bilinear metric baseline versus .1/max(.1,.5*z_measured²/120) residual scaling before existing saturation/loss. Clean + .5 px disparity noise (two seeds), all three optical biases, layouts/populations/starts; nine clean plane controls per method. Clean fixed outputs exactly reproduce 63/63. Clean perturbed joint 12/36→1/36, reference 6/18→0/18; 18 regressions/one gain. Noisy perturbed recovery 0/72 for both, reference 0/36→8/36 only. Noisy perturbed candidate convergence just 2/72. Both reject all nine planes; 8–800 actual calls. Reject candidate, do not tune floor/sigma or adopt. Next distinct hypothesis: independently specify direct disparity-domain error rather than measured-depth variance weighting, freeze the same regression controls before evaluation. No claim of success yet; MI real baseline/core unchanged.

Direct disparity preserves clean controls, still fails noisy recovery (2026-10-30)

Results, frozen c577773e: 171 candidate fits against archived fixed-metric baseline, exact paired depth hashes. Bilinear sample disparity, residual .2*(d_observed-120/(z+bias)), same robust loss/search. Clean joint recovery stays 12/36 perturbed, 6/18 reference, no regressions. Noisy reference 0/36→24/36, but noisy perturbed 0/72→0/72, all candidate noisy perturbed fits fail convergence/support. Nine planes rejected, 8–800 calls. No adoption or real transfer. Next freeze reference-versus-failed-pose objective landscape diagnostics with controlled bias on these same noise realizations before another residual variant or optimizer change. Do not relax caps/gates or claim reference-start gains as perturbed recovery. Core/MI defaults unchanged.

Disparity pose-path diagnosis (2026-10-30)

Results, frozen 21203727: all 171 archived fits, two fixed-bias eleven-point reference→fit paths, 3762 diagnostic passes. Depth hashes and fitted endpoint costs reproduce. No new fitting/verdicts. Noisy perturbed cases at fitted bias: returned fit beats reference in 72/72, but an interior sample beats BOTH endpoints in 69/72 (34/36 +35/36). Same counts on common support. At injected bias reference beats fit in 66/72; ranking depends strongly on nuisance bias. No global-minimum claim. Next freeze bounded derivative-free coordinate search of the same disparity objective, original starts and shared 800-call cap versus archived TRF. No truth paths as initialization/gates, no sampler/loss changes. Full clean/noisy/bias/ occlusion/reference/plane controls required. No adoption or SOTA claim.

Derivative-free coordinate search rejected (2026-10-30)

Results, frozen 3c966459, formatting-only rerun da10b9bb (initial plan/partial output/log retained). All 171 final cases, paired depth hashes verified, same objective and 800-call limit. Clean perturbed joint 12/36→0/36, noisy 0/72→0/72. Reference controls clean 6/18→16/18, noisy 24/36→32/36; those are not perturbed recoveries. Nine planes rejected, 85–800 calls, monotonic accepted cost. Reject replacement; no defaults changed. Close residual/weight/search micro-variants. Next review independent geometric camera/LiDAR correspondences and reusable external adapters for a genuinely distinct matched comparison; freeze assumptions/evaluation before new fits. Retain full-cloud MI baseline 6/12 and all negative evidence. No SOTA claim.

Independent geometry pilot prepared (2026-10-30)

Preparation, freeze 92a59724: review confirms prior SuperGlue/I2PNet correspondence failures; do not rerun their threshold variants. Native trimmed mutual point-to-point and Chen-Medioni ICP exist; Open3D absent. Prepared 18 stereo/LiDAR frame pairs, original restored SGBM, pose-free backprojection and independent .2 m voxel selection, finite <=80 m. Source 25536–42927 points, target 38351–71126, all NPZ hashes/counts verified. Manifest/schema committed; arrays under /workspace/work/stereo-registration-20261030. No fits or new accuracy claim. Next implement/freeze 108-trial runner per stereo_registration_protocol.md (18 pairs ×3 starts ×2 native ICP variants), full failure accounting and all-three-frame drive success. Historical joint MI6/12 is not a matched single-frame comparator. No reference-dependent preparation.

Native stereo geometry registration fails pilot (2026-10-30)

Results, freeze bd9709ee: 108 fits (18 frame pairs ×3 starts ×2 native ICP variants), full input/artifact hashes checked. Perturbed frame recovery point 1/36, plane 0/36; all-three-frame drive/start recovery 0/12 both. Reference controls 6/18, 2/18 frames, 1/6, 0/6 drives. Converged perturbed 8/36,9/36, others iteration cap; geometric-only 5/36 each is not recovered. Reject adoption; no post-result cap or voxel/gate tuning. Full detailed gzip results under /workspace/work/stereo-registration-pilot-20261030, summary/schema/hashes committed. Historical joint MI6/12 is contextual only. Next quantify reference-pose stereo/LiDAR overlap, nearest-target distances and normal agreement on all18 frames before another registration variant; offline truth diagnostics only, no truth-filtered fitting. No defaults or SOTA claim.

Stereo geometry overlap and normal diagnosis (2026-10-30)

Results, frozen c7ddb8c6, all18 prepared pairs, reference-pose diagnostics only. Camera-FOV source coverage within 1 m 80.97–93.89% (median86.15%), but within .2 m median46.97%. Whole-source within1 m median17.82% reflects partial FOV overlap. Normal pairs (both PCA-valid, FOV and <=1 m) agree within15 deg only 28.90–63.64%, median49.22%; target normal validity median99.31% is not surface accuracy. Explicit counts/reverse quantiles retained. No new fits/masks or accuracy changes; input hashes verified. Next specify measurement-only correspondence/surface reliability on independent controlled geometry (noise/occlusion), verify accuracy and spatial/directional support before frozen real comparison. Do not tune truth-based masks on these 18 spent frames, equate eigengap with correctness or merely raise ICP iteration caps.

Measurement-only surface gate fails precision (2026-10-30)

Results, frozen 54c0a3e0: 27 controlled frame conditions, three analytic layouts/origins, clean +.5px seeds730/731. 5x5 affine disparity fit, RMS<=1px and depth sigma<=.2m; no truth enters selection. Selected clean joint XYZ/normal precision100%, but noisy median 13.31/13.05% (all-valid4.80/4.88%), range7.92–29.33%, failing80% screen in 18/18 noisy. Retention5.17–28.58%, occupied4–13/16 cells; all noisy normal spectra pass ratio screen despite inaccurate normals. Reject gate; no real transfer/ICP rerun. Next derive/test angular uncertainty from disparity-slope covariance and verify coverage against exact normals before any new filtering; keep support failures explicit. Do not substitute planarity/depth uncertainty for normal accuracy or tune the18 spent real frames. Core/defaults and MI baseline unchanged.

Angular confidence gate retains no points (2026-10-30)

Results, freeze ce9d5e9e: coefficient covariance from .5px Gaussian noise on5x5 affine disparity, conservative95% normal ball→cone; same27 conditions/depth hashes. Added cone<=15deg retains 0/27 conditions' points, so all noisy support screens fail; empty precision is null. Prior gate median cone90deg, coverage~99% is uninformative. All-valid coverage ~91–94% reveals curved/boundary model error. Exact-plane20000-sample sanity check coverage99.465%, median bound35.68deg versus actual9.19deg: bound is loose, so do not claim intrinsic absence of accurate normals. No ICP/real transfer or defaults. Next test tighter angular uncertainty on exact planes with coverage AND support, then separately test model bias on curved/boundary patches. Do not tune thresholds on spent real frames or treat noise covariance as coverage of model error.

Tangent normal confidence fails coverage (2026-10-30)

Results, freeze f349514f, import-only rerun febdaa2b (initial outputs/plan retained; final cases identical).27 exact-plane scenarios ×20000 draws: 9/27 fail94% coverage, all frontal slope cases; minimum78.47%, median98.005%. Old ball min97.90%. Thus first-order normalized normal covariance is not calibrated across this noise/geometry range. 27 surface controls: clean selections empty; noisy nonempty only near_foreground frame2 (10/2 points), all support screens fail. No real filter/ICP or defaults. Close5x5 confidence shortcuts. Next direction: coherent surface estimation with larger support and explicit variance-versus-curvature/boundary bias control; freeze independent coverage criteria before fitting or real-data selection. Do not tune windows/thresholds on18 spent real frames. No SOTA claim.

Larger coherent surfaces improve but fail all-frame gate (2026-10-30)

Results, freeze f3672551:108 conditions, 5/11/21 and smallest-passing adaptive support, same27 measurement hashes. Plane smooths center depth as well as normal; not comparable to prior raw-XYZ precision. 21px noisy median joint precision 80.94/81.69%, retention 30.65/30.81%, but only 5/9 frames per seed pass gates; adaptive 3/9,4/9, median79%. Clean21px median74.65% (2/9 pass): curvature/boundary model bias remains. Angular coverage63–87% under nominal95% plane bound. No real transfer/ICP or defaults. Next measurement-model validation: independent spatial patch prediction or curvature-aware fitting, exact-plane and curved/boundary coverage/support controls. Do not choose a window using truth or tune RMS/scale on18 spent real frames.

Disjoint surface prediction passes controlled screen (2026-10-30)

Results, freeze d72a83a1:54 paired rows, same27 measurements.21px checkerboard221-fit/220-holdout predictive chi-square with shared coefficient covariance,99% gate; no truth selection. Exact-plane 10000-draw acceptance98.88%. Noisy joint precision medians 99.92/99.87%, retention 23.44/23.86%, all18/18 noisy and9/9 clean pass quality/support screen. Archived baseline27/27 exact. Final full-patch estimate reuses validation pixels; not independent confidence. Some angular coverage<95%, no guarantee or ICP claim. Next parameterize camera/stereo geometry with exact analytic parity first: current fx240/fB120 constants must not be applied verbatim to real KITTI. Freeze real intrinsics/stereo/noise/resampling assumptions before18-frame quality transfer; no tuning to reference normals, then matched ICP only if justified. No defaults/SOTA.

Camera-parametric predictive surfaces transfer partly (2026-10-30)

Results, freeze 22453494: explicit camera intrinsics/fB/noise, bitwise parity of all arrays on27 analytic conditions. 36 paired real quality rows on18 frames: baseline 13/18, predictive 15/18 pass; median normal agreement 86.12→88.16%, retention 26.81→24.77%. Failed candidate frames0005/38,0005/114,0009/111; no exclusions or relaxed gate. No ICP rerun per all-frame requirement. Restored-depth fB/z is surrogate disparity, .5px independence is uncalibrated on real data; no calibration/SOTA claim. Next fixed spatial distance/normal residual maps for all18, emphasizing3 failures, compare measurement support/boundaries; diagnose before changing model and never turn reference-derived maps into fit masks. Matched registration remains pending.

Spatial maps show interior surface disagreement (2026-10-30)

Results/maps, freeze 9a8327fd: all18 numeric/PNG maps, unchanged predictive surface masks. Aggregate counts/fractions reproduce prior report; all hashes and16-cell totals verified. 18/18 interior normal failure rates exceed boundary-band rates; median 17.83% vs7.27%. Distance failure interior higher14/18, median13.69% vs7.72%. Failed0005/38, 0005/114,0009/111 interior normal failures68.8%,42.5%,35.5%. No semantic/dynamic causal claim. Prior prose distance68.62% belongs to frame114 (corrected), machine outputs unchanged. Numeric NPZ local, all18 PNGs committed. No fits or mask edits. Next review prior stereo-consistency trials before choosing an independent cross-view/temporal check for coherently wrong geometry. No repeat matcher/gate tuning or truth-derived masks on18 spent frames; freeze distinct comparison first.

Reverse consistency still leaves three failed surfaces (2026-10-30)

Results, freeze d6bcae4e: conditional1px cycle test after predictive surfaces, all18 frames.18 raw restored SGBM and12 historical filtered arrays reproduce exactly. No plane refits or optimizers. Three failures remain agreement 45.71%,75.50%,78.83% (<80%), retention93.78%, 95.83%,93.69% of prior selected. Agreement improves13/18 but median88.16→87.95%; no remedy/adoption. Rejected/missing group noisier, yet accepted surfaces unreliable. Next audit independent camera-motion availability and temporal overlap before any temporal consistency design. Pin motion/time/frame/scale assumptions, no reference camera/LiDAR extrinsic in measurement selection. If unavailable/insufficient overlap, report it. No reverse-threshold retuning, ICP or fresh-data/SOTA claim.

Temporal readiness blocked on sparse input (2026-10-30)

Results, freeze be471af7:12 image-only pair audits, intervals3.728–11.590s. Only 1/12 meets30-cheirality/6cells screen (0011/116→174);0002 many essential inliers but zero cheirality, not proof of no overlap. OXTS available, but local IMU→camera chain uses target LiDAR-camera extrinsic; monocular scale unknown. No independent metric camera motion in declared input set. ±1neighbor local inventory0/36 complete stereo pairs. No data downloaded or new fits. Next prerequisite: freeze bounded ±1 stereo acquisition/preparation on SAME six spent drives (archive/member/timestamp/byte pins) before fetching, then short-gap support and metric-motion validation. StereoVO shares depth errors, not independent truth. No target-extrinsic-derived selection, arbitrary scale or fresh holdouts.

Short-baseline neighbor acquisition and support (2026-10-30)

Results: scope 550055c0, exact member ranges ce811402, audit 11f93d00, histogram reconciliation 79ce9e80. 72 images/36 stereo neighbors, only same six spent drives,56.85MiB range requests; archive/CRC/SHA/byte caps verified. First audit aborted on raw-vs-equalized pixels; initial plan/log retained, all18 centers match after existing equalization. Short-gap .1031–.1038s support 28/36 (old long-gap1/12, not paired accuracy). 0005/0009/0013/0015 each6/6,0011 4/6,0002 0/6. All failures retained. No metric motion, temporal masks, ICP or calibration claim. Right images acquired but unused. Next freeze metric stereoVO with independent controlled-motion/scale validation, no target extrinsic, all36 pairs/failures and explicit shared-stereo error coupling. No fresh recordings/holdouts, default changes or SOTA claim.

Camera-only metric motion feasibility (2026-10-30)

Results, freeze 271b9e75: 18 generated correspondence controls pass (<.2deg/.05m), maxima .04315deg/.005561m. All36 real pairs evaluated;54 unique depths,18 central arrays exact archive parity, all hashes verified. Metric camera-only bidirectional PnP support/cycle 34/36; 0013/106→107 and107→108 fail50% inlier ratios, not cycle. Cycle median .03353deg/ .01547m. No target extrinsic/OXTS/LiDAR used; shared stereo error means no independent real accuracy claim. Previous eight essential failures remain included. Next freeze controlled-motion/visibility temporal surface consistency, then real estimated-motion-only diagnosis. Keep failed motion pairs and missing/out-of-view/ occluded support explicit; reference/LiDAR score only after selection. No temporal filter/ICP/extrinsic calibration/default/SOTA claim yet.

Temporal surface verification rejected (2026-10-30)

Results, freeze 53c39a61:18 exact render projection controls pass, min98.34% visible consistency. All18 real centers, 36 estimated-motion checks; both-neighbor1px disparity agreement. Quality/support 15/18→13/18, retention median24.77→19.43%. Original failures still agreement 45.24%,76.02%,76.98%.0013/107 empty from unsupported motions;0015/74 distance failure21.79%. All categories retained; no truth in temporal classification. Close self-consistency mask sequence, no ICP/tolerance retuning. Next reference- assisted error attribution of estimated motion versus available OXTS/time/camera- conversion proxy, evaluation-only and uncertainty explicit. Target-extrinsic chain must never feed selection or be called independent metric truth. No defaults/SOTA.

Motion proxy and offline replacement leave main failures (2026-10-30)

Results: motion freeze 7fb15ad9, reference-assisted counterfactual freeze 5bed804c.36 OXTS camera-time/chain proxy comparisons: median estimate disagreement .03515deg/.02631m, max.10140deg/ .13856m. Common±10ms proxy change max.02690deg/.003180m; same-index max.14515deg/ .08386m, omit lever translation max.04472m. Sensitivity is not uncertainty bound. 18 counterfactual centers preserve masks/gates/unsupported flags; proxy motion uses target calibration EVALUATION ONLY. Main failures agreement 45.20/76.21/76.54% versus45.24/76.02/76.98 estimated motion. Overall13/18→14/18 diagnostic only, original measurement-only verdict unchanged. No independent motion truth or adoption claim. Next underlying stereo matching ambiguity/surface reconstruction attribution, review prior frontend evidence first; no reference-selected masks, SGBM retuning or another self-consistency gate. LiDAR normal/calibration/timing alternatives remain explicit.

Stereo appearance does not certify surface correctness (2026-10-30)

Results, freeze 1812d061:18 fixed raw stereo appearance probes,121636 sampled/120010 common-valid, offsets±1/2/4/8, zero-mean5x5 SAD, no matcher/mask/depth changes.18 raw depths exact archive parity. Wrong-normal ambiguity median44.56% vs32.48%; but wrong-group median base cost LOWER in11/18, including all3 persistent failures. Association is not calibrated confidence; strata and exclusions explicit. No new selector or recovery claim. Close stereo-surface confidence variants. Next review a materially distinct direct RGB–LiDAR provider beyond failed SuperGlue/I2PNet: architecture/checkpoint/license, training overlap and CPU/GPU readiness, then ONE frozen feasible spent-data pilot. No fresh holdouts, SGBM/threshold retuning or runtime-as-accuracy/SOTA claim. Preserve full-cloud MI6/12 and all negative evidence; report concrete prerequisites if blocked.

Direct-provider official-source readiness review (2026-10-30)

Review/pilot prerequisites, machine evidence: official CoFiI2P ed90edf5, CorrI2P 4f4a7550, DeepI2P cd21389d pinned/hashed and read, not executed. Conditional priority CoFiI2P correspondence mechanism; all current unmodified paths blocked by CPU-only runtime/unchecked weights/dependencies. CoFi/Corr no root license found in pinned trees (terms unresolved, not legal verdict), Deep MIT but CUDAExtension. KITTI train0–8/val9–10 code does not establish exact checkpoint/raw-frame isolation. No weight digests or inference/accuracy claim. CoFi loader prealigns using dataset calibration; MUST bypass with explicit initializer-only input boundary and tested transform/crop/normal lineage. Its test model path differs from train/val, so do not claim the entire model requires labels. Concrete conditional54-invocation spent-data pilot is specified; prerequisites GPU or validated port, pinned appropriate weight/terms, no-reference adapter, training provenance. No fresh data, package install or code copied into core. Guessed2D3D-MATR URL unresolved and retained, not an official candidate claim.

CoFiI2P initializer-only geometry boundary completed (2026-10-30)

Contract and limitations, implementation freeze 333e368b, synthetic verification: four hash-pinned inputs only (image/cloud/camera/explicit initializer); no reference or dataset loader. Nonidentity points/normals, IDs, correction composition, odd-size crop/pixel mapping, BGR values, reference-file mutation and input rejection covered by four unit tests. Three-point synthetic CLI smoke passes eight planned checks. No real frame, model inference, accuracy or checkpoint-parity claim. Original point rows survive; no sampling/pyramid yet. Actual rounded resize/pixel-center affine differs from official nominal0.5 K scaling; BGR/feature stride also need explicit checkpoint compatibility review. Caller initializer/normal provenance remains an upstream obligation, not established by reference-file mutation alone. Next resolve preprocessing parity and model bridge (sampling/lineage, neighborhoods, fine-feature pixel coordinates), plus GPU/validated port, suitable pinned weights/ terms and training overlap. Then freeze one54-call spent-data pilot; do not resume stereo-mask variants or claim SOTA from geometry tests. Core/defaults unchanged.

CoFiI2P model-shaped CPU geometry and patch audit (2026-10-30)

Contract/source findings, freeze b6d0628e, synthetic result: independent voxel mean+CSR source lineage, count selection, five replacement-sampled levels, 128 KNN and explicit fine-pixel decoder. Default20480/10240/5120/2560/1280 smoke on4096 synthetic points repeated exactly; all39 selected exhaustive KNN-distance checks pass. Unique voxels per level4096/3775/2581/1504/811; keep duplicates and centroid contributor sets. Related tests21 pass; no model call or real frame. Official eval adds patch row to u/column to v despite (h,w) flatten; decoder requires row_major or official_eval_legacy explicitly.12/16 positions differ, NOT measured model error. Freeze convention before any pilot, never select by reference errors. Open3D voxel ordering/KNN ties/random streams and truth-prealigned voxel grid NOT numerically reproduced; this is NOT a validated CPU inference port. Local BGR, crop and pixel-center mapping still lack checkpoint parity. Next prioritize suitable checkpoint provenance/terms, upstream image preprocessing, GPU/validated inference runtime and training overlap; then one preregistered54-call spent-data pilot. Do not continue geometry polishing as a substitute for model evidence. Core/defaults and historical MI6/12 plus all negative evidence remain unchanged.

CoFiI2P inference deferred on concrete runtime/checkpoint blockers (2026-10-30)

Readiness/handoff, machine evidence: runtime torch2.4.0+cpu/Python3.12, CUDA unavailable, Open3D absent. Official OneDrive/Baidu HEADs both proxy CONNECT403 under enforced policy; GitHub releases page no releases. No checkpoint bytes/digest, external execution, new real data or accuracy result. DeepI2P KITTI RGB conversion and CoFi nuScenes PIL pipeline support RGB ancestry, not exact distributed KITTI crop/color/K provenance. Do not call local BGR parity. Issue26 collaborator acknowledges historical train-only translation suppression and plans retraining; IMPORTANT pinned ed90edf5 line225 is COMMENTED OUT, so current source DOES train with translations. Distributed checkpoint training revision/date still unknown. Issue25 collaborator reports no validation/test distinction; this does NOT prove overlap with our spent raw frames. Issue7 about3GB inference is author report, not measured bound. Issue20 coarse-only report does not prove patch axis issue caused it or permit reference-selected variants. Require GPU workspace, suitable official checkpoint SHA/terms/training recipe and prepared-image provenance, then bounded no-reference model smoke and frozen54-call spent-data pilot. User was asked for available GPU/checkpoint location; do not invent access, bypass proxy, retrain blindly or keep polishing CPU geometry instead of obtaining model evidence.

Bounded alternative-provider follow-up closed (2026-10-30)

Review, machine evidence: official NCLR40de8eea, FreeReg d13a45f5, FFreeReg branch0b397094 pinned,18 source hashes. NCLR has calibration/PnP components inside representation learning, but README weights are todo; no ready pretrained unknown-extrinsic provider established. Root Apache2.0, sparse-convolution dependencies. FreeReg has CPU fallbacks in some components (do NOT blanket claim CUDA-only), but multiple unpinned large weights/ dependencies and no feasible complete current runtime verified. FFreeReg removes virtual-camera/diffusion requirements but still DepthPro+YOHO/FCGF weights, explicit CUDA demo and MinkowskiEngine. Estimated K, scale resampling and point lineage need frozen policy before calibration use; do NOT relabel a stereo substitution as Free-FreeReg reproduction. FreeReg/FFreeReg no tracked root license; dependency terms separate. About42MB source clones include bundled demos, none evaluated. Zero model calls/weight download/calibration fits; core/defaults unchanged. Close speculative provider search and adapter expansion. Next useful execution requires accessible GPU and suitable official checkpoint with SHA/terms/training and image provenance, as in CoFi handoff. No accuracy/SOTA advance claimed.

User has NO GPU; CoFiI2P CPU graph now exercised (2026-10-30)

CPU-only is an explicit user constraint, not a pending GPU request. Supersedes the previous GPU-first next actions. Protocol/results, freeze 3b15f88a, seed20261030/two threads: actual external CoFiI2P test-mode model with random weights and None label arguments completes both2048 and20480 points. Forward4.13/10.36s, peakRSS735.4/1901.6MiB, init5.40/5.53s. All8 outputs finite/CPU, repeat tensors exact; same seeded model-state hash across point counts. Random predicted pairs10/4 are NOT correspondence accuracy, no PnP fit/real frame/checkpoint. Only two external copied files patched:4 CUDA transfers to input device, unused Open3D/plot imports removed, native NumPy kernel generation with NPY cache instead of Open3D PLY, bounded predicted-pair loop. Existing SciPy geometry/order/tie/grid differences remain; not verified official CPU/GPU/Open3D numerical parity. Source copy and outputs workspace-only, no external code copied to core; einops0.8.1 tiny dependency installed, no GPU/Open3D/TorchVision package install. Core/defaults unchanged. Next accessible official KITTI weight SHA/terms/training+image recipe, then bounded CPU checkpoint smoke and frozen spent-data pilot. GPU is NOT required for this exercised graph. Do not re-request GPU or repeat closed MI search/stereo variants.

CPU checkpoint loader and raw pair lineage exercised (2026-10-30)

Contract/results/template, freeze 5b90e2e6: request pins checkpoint/bridge/prepared chain, declares image/layout/source/training/ terms, rejects reference fields. torch.load(weights_only=True,map_location=cpu) plus exact tensor keys/shapes/dtypes/finiteness and strict load; no prefix/wrapper/ dtype guessing, unsafe fallback or random fallback. Native fine_process indices observed unchanged; exports original-image pixels, LiDAR voxel centroids and CSR of ALL original contributor IDs. No covariance/confidence/quality/pose invented. Official checkpoint still absent and official hosts still policy-excluded; no repeat denial probes or mirror search. Full synthetic raw state196.97MiB saved, then loaded in separate process at20480 points: init+load5.82s/forward10.21s, peakRSS1.92GiB, allCPU/finite/exact repeat.4 pairs but only3 distinct voxels/pixels, all retained; no pose fit/accuracy. Fixture seed matches target initialization; different-state load mutation verified separately by small-model tests. Synthetic kind requires explicit --allow-fixture and remains labeled in result.32 related tests, schemas/digests/original centroid+ID/pixel checks pass. Source/weights outside core; no learned model or fresh dataset acquired. Next fill learned-request template with an accessible official KITTI artifact and SHA/source/terms/training+image recipe, then bounded CPU smoke and preregistered spent-data pilot. CPU-only user constraint persists; stop adding substitute random-weight experiments as accuracy evidence.

v3 capture complete on all 55 spent drives (2026-10-31)

Results: tools/kitti_camera_lidar_v3_batch.py fetched, converted, captured (seven real checks) and replayed all 55 spent KITTI raw drives in one cloud session, with archive/calibration pins committed first (4d82d125). Summary complete; the current-rule replay equals the committed v2 aggregate exactly (52 scored, 125/156 judged axes, 3 deg 122/125, 1 deg 125/125, maxima 0.450/1.503 deg). The proposed 3.5 margin keeps coverage but flags only 114/125 3 deg turns and adds a 1.350 deg yaw error on 0036 while removing the 0002/0057 errors (turned-run judged axes >0.5 deg: 10 → 5). Against v2's gate values it would pass on these spent drives (8.8 % 3 deg misses, 1.350 deg), but only post hoc: 3.5 was chosen after reading v2 evaluation drive 0002, and the margin moves a large error to 0036. Do not adopt it as a default; no threshold change. Four zip64 drives first failed on cut range transfers; all eight failed attempts are kept. The fetch fix a7a83db0 retries each range as a fresh, length/ETag/CRC-checked request. (The interim --retry-all-errors appended partial bodies and was caught by the length check.) NPZ inputs remain only on the batch machine for 23 drives; the other 32 need re-capture before replaying a new rule. Next: a different start-selection/axis-evidence rule developed on cached inputs, then replayed on all 55 drives with coverage, missed turns and judged-axis errors reported together. KITTI-360 pre-registration stays pending; no fresh data was read and no SOTA claim is made.

Cross-start agreement rule screened (2026-10-31)

Results, protocol frozen 98262f84: opt-in start_agreement_deg=0.5 withholds a rotation axis when evidenced optima from different starts differ by more than the check's 0.5 deg std bound. Screened once on all 55 spent drives (23 cached, 32 re-captured; 32 disk-preflight failures retained). Verdict not_carried_forward: turned-run judged errors beyond 0.5 deg 10 → 2, none new, maximum 1.503 → 0.532 deg; but 3 deg turns flagged only 82/124 (66 %) against the 90 % v2 value, while 1 deg 117/124 and baseline/coverage checks pass. Post hoc: 40/42 missed 3 deg and 7/7 missed 1 deg trials show cross-start disagreement, as does one baseline (0029). Flagging disagreement is the next hypothesis, needing its own frozen protocol with that baseline cost stated. Spent data only; no default, CLI or SOTA change.

Opt-in cross-start disagreement warning shipped (2026-10-31)

At the user's request the flagging variant is a practical opt-in, not a v3 claim: calibrex check|estimate|drift --camera-lidar-start-agreement-deg 0.5 withholds camera-LiDAR rotation axes where evidenced optima from different starts differ by more than 0.5 deg, lists them as start_disagreement and makes the pair at least warn. Defaults, caches and v2 results are unchanged; schemas only widen. On the 55 spent drives (motivating data, measurement): KITTI calibration warned 1/55 (0029 yaw), 3 deg turns warned 122/124, 1 deg 124/124, turned-run judged errors >0.5 deg 10 → 2. A disagreement warning does not identify the error's size or direction. A v3 claim still needs a separately pre-registered rule on unread KITTI-360 data; do not cite these rates as audited.