Record the first cap32 hybrid score while the larger run continues

Persist the newly finished cap32 hybrid result so the next session can continue the top-two validation run from measured evidence instead of only a running-state checkpoint.

Constraint: cap32 high_energy and the final report are still pending
Rejected: Wait for the full cap32 report before updating docs | Would leave the larger-subset evidence stale across sessions
Confidence: high
Scope-risk: narrow
Directive: Replace the cap32 partial section with the final two-strategy ranking once high_energy eval and report.json land
Tested: Verified /tmp/ab_smoke_seg_cap32_top2/hybrid/fma_reports_smoke/eval.json; verified docs record hybrid=20/0.95/1.0 and high_energy still training
Not-tested: Final cap32 comparison because high_energy has not finished yet

@@ -14,14 +14,16 @@
 
 当前 fresh evidence：
 - `scripts/ab_smoke_segmentation.py ... --work-root /tmp/ab_smoke_seg_cap32_top2` 已启动
-- 当前 first lane 为：
-  - `hybrid`
-- 当前已进入：
-  - `run_demo.py build-index --resume --checkpoint-every-refs 100`
+- `hybrid` 已完成首条评测：
+  - `num_queries = 20`
+  - `top1 = 0.95`
+  - `topk = 1.0`
+- `high_energy` 已进入训练阶段
 - `report.json` 尚未落盘
 
 结论：
 - 现在已经开始验证 cap24 结论在更大 `subset=32` 上是否继续成立
+- 当前至少可以确认：`hybrid` 在更大子集上仍保持较强表现
 - 即使当前 session 结束，新 session 也可直接从 handoff 中的 cap32 入口继续盯结果
 
 ### Stage: 收尾 cap24 top2 真实 FMA 对照并确认默认策略

@@ -442,8 +442,8 @@ cd /workspace/acr-engine
 |---|---|
 | `subset_size` | `32` |
 | `max_test_queries` | `20` |
-| 首个运行策略 | `hybrid` |
-| 当前阶段 | `run_demo.py build-index --resume --checkpoint-every-refs 100` |
+| `hybrid` | `num_queries=20`, `top1=0.95`, `topk=1.0` |
+| `high_energy` | 训练中 |
 | `report.json` | 尚未生成 |
 
 恢复检查命令：
@@ -453,7 +453,7 @@ pgrep -af 'ab_smoke_seg_cap32_top2|external_adapters.py smoke-local fma /tmp/ab_
 ```
 
 优先等待文件：
-- `/tmp/ab_smoke_seg_cap32_top2/hybrid/fma_reports_smoke/eval.json`
+- `/tmp/ab_smoke_seg_cap32_top2/high_energy/fma_reports_smoke/eval.json`
 - `/tmp/ab_smoke_seg_cap32_top2/report.json`
 - `b766c74` Make open-dataset manifests trainable end to end
 - `fa23144` Add a single-page open dataset workflow for training prep