±180° wraparound census: rare, concentrated in one repo — unwrap-at-load arm killed

2026-08-05. CPU-side analysis (idea #14), no GPU touched — ran beside the smoke test. Spawned by the stage-1 sign-convention surprise (the 14.9× kevin510 “standout” was a wraparound artifact, not a mirror); prioritized by the owner’s 15:45Z confirmation that ±180° wrist_roll wrap is a known SO101 calibration-time artifact they hit on their own rig. Verdict feeds tonight’s paired-run decision per the 16:13Z steering: wraps are rare in training data, so the unwrap-at-load arm is dropped and arm B goes to the next-best treatment.

The causal story (from the lerobot issue tracker)

The web trail (posted in-channel 16:20Z) is a consistent cluster, all wrist_roll: #1255 (encoder wrap at the 0–4095 boundary, closed without a fix), PR #777 (removed the ±180° software wrap guards in favor of mid-range-zero calibration — creating the exposure), #3193 / #1296 (the “Magnitude exceeds 2047” calibration-offset family, set_half_turn_homings() root cause), fixed properly only in release 0.6.0 (Mar 2026: “fix wrist_roll calibration + use_degrees default”). Exposure window ≈ Jun 2025 → Mar 2026 — squarely the community-dataset recording era. Mechanism singles out wrist_roll, the one continuous-rotation joint: a calibration whose zero lands mid-range lets trajectories cross ±180° and wrap by ~360°.

One prediction of this story is not testable locally: the mirror re-serializes every repo to codebase_version: v3.0, so the recording-era lerobot version is gone from local metadata and the wrap-rate-vs-version correlation can’t be computed here.

Instrument

probes/probe_wrap_census.py (anchors asserted in-probe; scratch parity confirmed before formalizing). Two censuses:

• Part A — panel: over the laptop reference npz (eval__bijou_arb_rcond_100k_ddp4__step_100000__panel_k4l2, 17,204 core frames, 878 repos), count frames whose truth chunk spans

  300° per dim, and bound their contribution to the official pooled chunk_mae (abs_error_sum / (valid_steps × dims) — reproduces the instrument’s 5.8026 bitwise before any slicing).

• Part B — training corpus: over all 878 selected repos on disk (20,719,389 frames, 42,872 episodes), count consecutive-frame |Δ| > 300° within an episode, per repo per dim, in both action and observation.state — the load-time discontinuity an unwrap-at-load transform would repair.

Part A: 0.09% of panel frames carry 1.2% of panel MAE

Only two repos supply panel wrap frames: kevin510/lerobot-cat-toy-placement (shoulder_lift + wrist_roll) and willnorris/bbox-2 (five dims including gripper — a different, whole-state corruption; see below).

The excess (0.0720) is larger than the ±0.05 gate we used to declare the baseline re-score matched — i.e. wrap frames alone are the size of an effect we’d otherwise chase. But it is a metric artifact concentrated in 16 frames, not a modeling signal: shortest-arc scoring recovers 0.053 of it with zero training change. Changing the eval metric moves every anchor (mainline’s included), so per charter §2 that proposal goes to the owner rather than into the instrument: logged as a recommendation, not applied.

Part B: 0.19% of training episodes, half of them one repo

23 / 878 repos have ≥ 1 wrap jump; 81 / 42,872 episodes (0.19%) are affected. Per-dim total action jumps: wrist_roll 204, shoulder_lift 80, elbow_flex 18, wrist_flex 1, others ~0 — wrist_roll dominates, as the calibration mechanism predicts. The distribution is extremely concentrated:

Reading the tail: kevin510 is systematically corrupted — every episode wraps, on two joints, in both action and state; it is the canonical instance of the calibration story and was already the stage-1 aggregate-screen standout. willnorris/bbox-2 is a different disease — simultaneous > 300° jumps across all six state dims (including gripper, which is not an angle) on 11 episodes, with actions clean: that is a state-stream glitch (dropped/garbled frames), not angle wraparound. Everything else is isolated single-episode noise.

Verdict against the pre-registered gate

Idea #14’s falsification line: “if wrap frames are < 0.1% of the panel and their excess MAE is negligible, bank as a curiosity.” Measured: 0.093% of panel frames — under the line — and 0.19% of training episodes, half of it one 40-episode repo (0.09% of the corpus).

Training side: an unwrap-at-load arm cannot pay for an H100 run. The treatment would alter 0.19% of episodes; any effect is far inside pairing noise at 40k steps. Dropped per the 16:13Z steering; arm B of tonight’s paired run goes to the next-best treatment (separate pre-registration).

Eval side: real but small, and fixable without training. The 0.0720 panel excess is worth a one-line metric consideration (shortest-arc error) — owner sign-off required since it re-bases every anchor. Cheap alternative if metric stability is preferred: exclude or unwrap the two corrupt repos in the panel definition at the next panel version bump.

Data hygiene: two named repos. kevin510 (systemic wrap) and willnorris/bbox-2 (state-stream glitch) are flagged for any future curated-v1 exclusion list; at 82 episodes combined they are immaterial to training today.

Caveats

• The jump detector (|Δ| > 300° between consecutive same-episode frames) misses wraps that happen to align with a chunk boundary in eval and any wrap smaller than the threshold; at 300° vs a ~360° physical jump the margin is comfortable.
• Part B counts discontinuities, not “operates near ±180°” — a repo whose wrist sits at 179° without crossing scores clean, which is correct for the unwrap-at-load question but not a full risk census for other wrap-adjacent pathologies.
• codebase_version is uniform (v3.0) post-mirror, so the version correlation the causal story predicts is untestable locally (noted above).

2026-08-09 addendum: the kinematic-continuity screen (idea #9, VISTA-style rig-calibrated scoring, no wrap-specific threshold) independently re-derived this census’s two structural repos from scratch and closed the sub-300° gap noted in the limitations above: 42 further episodes across 30 repos carry single-tick dropout jumps under the 300° line (0.08% of the corpus — the effect-size verdict here is unchanged).