Sim wrist-cam periphery: bar smashed — wrist AUROC 0.900 → 0.548, inside the real spread

2026-08-12 ~06:2xZ (work session). Closes queue item sim-wrist-periphery-fix per its pre-registration (registered ~05:5xZ, in-channel 05:59Z). Result: the registered bar (≤ 0.786) was passed on the first candidate pose — the wrist camera read is now at 0.548, a hair above the 0.5 can’t-tell-them-apart point, and the sim wrist frames sit inside the real embedding spread (k-ratio 0.97×).

Plain words

The fix was moving a camera ten centimeters. Our simulated wrist camera sat on top of the wrist joint, behind the gripper — so when we gave it the real rig’s wide-angle lens, the picture filled up with the robot’s own dark plastic body, something the real camera never sees. We slid the camera forward so it sits over the base of the fingers, tilted it a little steeper toward the table, and the picture became what the real one shows: wooden table everywhere, two fingertips poking into the bottom edge. The policy’s vision encoder — which yesterday told sim wrist images from real ones 90% of the time — now barely does better than a coin flip (55%). By this measure the wrist view is the first camera whose sim images are statistically inside the cloud of real ones.

The read (registered instrument, 100-seed reset-render probe)

• Bar: MET — 0.548 ≤ 0.786, and far past it: k(sim) 1.647e-5 vs k(realB) 1.691e-5 means the average sim wrist frame is now closer to the real reference set than the average held-out real frame is.
• Guard: green — top 5-NN AUROC 0.773, bit-identical to the shipped v2 read (the top path is untouched; also a determinism check of the instrument).
• Sensitivity (registered, record-only): 20 seeds × 5 appearance draws reads 0.550 — the result is stable across appearance draws, not a lighting accident.

What changed

One runtime pose in SO101Sim._repose_wrist_cam (vendored XML untouched, both arms): the camera moves from the wrist top behind the gripper (world ≈ (0.096, −0.004, 0.160) at home, 55° below horizontal) to over the jaw base (≈ (0.150, 0.000, 0.150), 65°), same image-right = −y roll convention. Under the 72° fisheye source the old pose filled the bottom ~40% of frame with gripper-body mass; the new pose drops the body out of frame, leaving the orange moving jaw and black fixed jaw tips in the bottom quarter over full-frame table — the composition of every real episode-start frame.

REAL | old pose | new pose gallery — three reset seeds vs three real episode starts.

The candidate was found in three encoder-free iteration rounds (contact sheets vs pinned real_v2 A-half start frames — held-out B untouched); only the shipping candidate got encoder reads. Total GPU spend: ~0.04 GPU-h of probe reads (gate 0.2).

What it means

• Content composition is confirmed as the whole wrist story. The v1 close said the wrist read tracks what is in the frame, not image statistics — this lands it: no texture, grade, or plate work moved the wrist below 0.786; a 10 cm camera move took it to 0.548.
• The per-episode-aligned wrist plate axis (named at the v2 close) is retired. A composite cannot beat inside-the-real-spread, and the mush-plate negative (0.951) is explained: the plate was built for a viewpoint whose own periphery was the problem.
• The sim100 rerun gate now reads double-GO: top 0.773 ≤ 0.790 and wrist 0.548 ≤ 0.786 — both cameras at or under their registered lines. The rerun (sim100-v1-rerun) stays owner-held pending the 20-seed spot-check call; a pre-reg amendment draft is queued so the eval is launch-ready on unhold.
• Caveat (stated at every close of this series): the probe measures encoder separability of reset frames. Mid-episode wrist content (closed jaws, lifted boat, motion blur) is unmeasured, and encoder-indistinguishable does not imply behavior transfers — that is exactly what the held rerun would measure.

Artifacts

• Probe jsons: analysis__sim_wrist_periphery_fix.json (100-seed primary), analysis__sim_wrist_periphery_sensitivity.json (20×5) on fontaine-reports.
• Gallery: chart__sim_wrist_periphery_before_after.png (link above).
• Oracles: 10 green (qpos bit-identity across render styles, spawn stream vs banked v0 — the pose is render-only), check.py 704 green.