---
license: odc-by
tags: [calibration, diffusion-language-model, masked-diffusion]
---

# C3 audit traces

Position-level traces from the C3 selection-conditional calibration audit
(ANLP Monsoon 2026, team DuckDuckDuckGoose): one row per (masked state, masked
position), schema v2 -- `model variant revision precision dataset git_commit seed
mask_kind policy k target_rate mask_rate step n_masked doc_id state_id state_idx
doc_len span_start span_len position top1 conf ell p_true entropy margin topk_ids
topk_p delta_ell agree committed commit_rank` (`c3/traces/collect.py`). Pools are
drawn at analysis time, so the audit can be re-run with other pool designs without
another forward pass.

| path | what |
|---|---|
| `main-110m-v3/` | ANLP-project/c3-mdlm-110m on 1,979 documents of the 2,000-document calibration set, fp32; 4 shards x 10 parts, `*.meta.json` per shard, and `main-110m-v3.dataset.json`, a zero-copy manifest of the parts (file, sha256, rows) that `c3.assemble.load_traces` reads directly: no merge step needed. Shards 0-1 and 2-3 were collected at two commits that differ only outside the trace code (validated with `--allow-mixed-commits`) |
| `timesplit-110m-v3/` | the same model on the 500-document time-split set (doc_ids 200000-200499), fp32, in the same layout: 1 shard x 10 parts, its `*.meta.json` and the manifest `timesplit-110m-v3.dataset.json` |
| `t2floor-110m-v3-fp32/` | non-determinism floor of ANLP-project/c3-mdlm-110m: 20 reserve documents, T2 pilot design, fp32; 5 bitwise-identical repeats, floor 0 |
| `validation/` | `main-110m-v3.json`, `timesplit-110m-v3.json`: `scripts/validate_run.py` on each manifest (every check passes); `floor_local-110m-v3_fp32.json`: the floor; `validate_*.json`, `*.meta.json`: metadata and row-count validation of the earlier merged copies against the closed-form design |
| `t2pilot-llada-base-fp16/` | T2 pilot: LLaDA-8B-Base fp16, 5 repeats (non-determinism floor) |
| `stage0-llada-8b-4bit/` | Stage 0 pilot: LLaDA-8B 4-bit, 20 documents |
| `corpus/` | calibration, reserve and time-split documents (FineWeb-Edu, ODC-By) and the exclusion manifests removed from the 110M training stream |

Code: https://github.com/abhirajratna/ANLP-Project