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exp: 多段推理代价实测(2段+5.97ms/4段+17.7ms/8段+42ms，B=1 K=8)——靠段数补偏差不进 20ms 预算

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docs/experiment_round38_steps_cost.json
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{
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docs/探索日志.md
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- **对 `backoff` 的预期与判据**：全拒意味着"连第 1 步的端点或中点已经穿进障碍"，缩步能不能救取决于**穿得有多深**（穿 0.1 mm 救得回，穿 3 mm 救不回）。这个数转储里没记（只记被选中那条），所以直接由 `backoff_mean`/`reject_all_mean` 来量：
`reject_all_mean ≈ 原全拒次数`（=backoff_mean+brakes_mean，与轮次 33 cap 的 19.55 可比），`backoff_mean/(backoff_mean+brakes_mean)` 就是"缩步能救回的比例"。这是补跑（#22）要读的第一个数。
## 多段推理的代价实测（B=1、K=8、逐轮交替、奇数轮反序）
- `docs/experiment_round38_steps_cost.json`（24 轮 × 每轮 40 次，取每档的中位）：
| 段数 | 推理 P50 | 相对 1 段增量 |
|---|---|---|
| 1 | 9.02 ms | — |
| 2 | 14.98 ms | **+5.97 ms** |
| 4 | 26.72 ms | +17.71 ms |
| 8 | 51.07 ms | +42.05 ms |
- 每多一段 ≈ 多一次解码器前向（编码器 `mem` 只算一次），所以增量近似线性；9.02 ms 这一档比轮次 33 报的 7.2 ms 高，是不同会话的时钟/上下文差别，**只用同批内的差值，不用绝对值跨轮比**。
- 合到整周期上：轮次 34 的现口径 P50 ≈ 33.5 ms，两段就是 ≈39.5 ms（25 Hz），四段 ≈51 ms（19.6 Hz）——**离 20 ms 预算更远**，所以"靠多段推理把一步的偏差补回来"在部署上不成立，只能作为开环诊断口径。
- 与 K 这条轴叠加会更糟（K=16 认证点翻倍），所以 `K=8/16 × cert_batch=0/1` 的四格周期微基准排在当前批次里（`ml/runs/_kcost_probe.py`），这是判断"候选数能不能买到部署里的到达率"的关键一列。
## 候选为什么会"塌"：两段积分把 K 条候选吸成一条（轮次 39 探针，机理定案）
- `ml/runs/_cand_div.py`（256 题特征、同一批噪声 z、K=8，只改段数）：