sim/calibration/README.md

Calibration data — Chief Engineer outcome simulator

Observations used to calibrate sim/outcome.py (the one simulated boundary — see ../../SIMULATION.md). Each row is a real(ish) print: the settings used + room + the real outcome (+ optional 0–1 quality). The tune-simulator skill scores the simulator against these. Packaged so it can be published as a Hub dataset later (Sharing is Caring).

Files

File	Rows	What
observations.sample.jsonl	12	Hand-crafted template, mixed outcomes — the schema reference.
observations.modal.jsonl	260	Ingested on Modal: 82 from 3DTime (G-code headers) + 178 from FDM Error Detection (known-failure logs).
results/baseline.*.json	—	Machine-readable metrics (accuracy, MAE, confusion, fan=0 count) per dataset.
results/report.*.txt	—	Human-readable harness output (confusion + per-row mismatches).
CALIBRATION-REPORT.md	—	The analysis + the decision (and why we did not tune to this data).

Schema (one JSON object per line)

{"material":"PLA","geometry_type":"overhang","env_temp":22.0,"env_humidity":45.0,
 "nozzle_temp":210.0,"bed_temp":60.0,"retraction_mm":3.0,"fan_pct":0,
 "first_layer_fan_pct":0,"outcome":"failed_sag","quality":0.7}

Enums (material/geometry_type/outcome) match core/models.py.

Provenance & licenses

• 3DTime (3DTimeDataset/3DTime) — published Printables models; outcomes are all success (they printed). Settings parsed from G-code headers.
• FDM Error Detection (NilsHagenBeyer/3D-printing_recorder) — G-code + YAML with labelled failures (good / stringing / under-extrusion). The source of the real failures.

⚠ Known data-quality caveats (read before trusting a calibration)

• fan_pct defaults to 0 when M106 isn't in the G-code header (178/260 rows). This makes overhangs look fan-off and the simulator (correctly) predict sag → false mismatches. Do not tune sag to these rows.
• Geometry is a bbox heuristic for 3DTime rows (no real geometry label), so many ordinary prints are tagged overhang.
• 3DTime outcomes are uniformly success — no failure signal; good for Lane-A references, weak for outcome calibration. See CALIBRATION-REPORT.md and ../../docs/plan/RESEARCH-NEEDS.md for the fixes that make this set tunable.