ml: 按运行手册审查修订——头分目录不互相覆盖（ml/runs/<CFG>、selected_ckpt/CKPT）；统一 $PYTHON（Windows Git Bash 可跑）；gen 按实测样本/任务自动补量；R10 改终态判据（≥5k 样本/s≈60k 步≤3.5h）；m5 纯策略/仿真安全层双口径；无老师题定长 6 s 口径；APG 展开随批时长、端点+中点铰链、余量 3 mm（投影同步）；挖错池只用本轮；门禁加 R7；bench 加 R8 对抗集与刹停率、--nc-n/--route-n/--r8-n；新增 check_r2 与 acceptance；export 默认 fp32；出题分块防 OOM；val 为空保护

ml/mining/gate.py

@@ -1,4 +1,6 @@
-"""门禁（方案 §7.2 第 6 步）：新模型须 ①门禁集到达率不降 ②A 类降幅 ≤ 0.5 个百分点 ③上一轮修好的错题 95% 仍对。
+"""门禁（方案 §7.2 第 6 步）：新模型须 ①门禁集到达率不降 ②A 类降幅 ≤ 0.5 个百分点 ③上一轮修好的错题 95% 仍对
+④R7：B/C 类（需绕行）左右比例变化 ≤ 5 个百分点 ⑤R7：两者都到达的题行程中位数比 ≤ 1.05。
+门禁集为无老师题，到达按定长 6 s 口径（见 closed_loop.NOREF_SEC）。
   python -m ml.mining.gate --old cur.pt --new cand.pt --tasks ml/runs/gate_tasks.jsonl --out gate.json [--fixed prev_fixed.jsonl]
 通过则把 cand 复制为 --current（默认 ml/runs/current.pt）。gate.json 含 accept / gain_pp，loop.sh 据此决定继续或停止。"""
 import argparse, json, shutil
@@ -38,15 +40,27 @@ def main():
         if ft:
             r2, p2 = evaluate(load(a.new, a.device), kin, ft, a.device)
             keep = sum(per_task_success(p2)) / len(ft)
-    accept = gain >= 0 and a_drop <= 0.5 and (keep is None or keep >= 0.95)
-    out = {'old': ro, 'new': rn, 'gain_pp': gain, 'A_drop_pp': a_drop, 'fixed_kept': keep, 'accept': accept}
+    # R7：左右比例与行程
+    cat = [t['cat'] for t in tasks]
+    so_side = torch.cat([p['side'] for _, p in po]); sn_side = torch.cat([p['side'] for _, p in pn])
+    det = torch.tensor([c in ('B', 'C') for c in cat])
+    left = lambda sd, ok: (((sd > 0) & det & ok).sum() / ((det & ok).sum().clamp(min=1))).item()
+    ok_o, ok_n = torch.tensor(so, dtype=torch.bool), torch.tensor(sn, dtype=torch.bool)
+    lr_shift = abs(left(sn_side, ok_n) - left(so_side, ok_o)) * 100
+    both = ok_o & ok_n
+    tro = torch.cat([p['travel'] for _, p in po]); trn = torch.cat([p['travel'] for _, p in pn])
+    travel_ratio = (trn[both].median() / tro[both].median().clamp(min=1e-6)).item() if both.any() else None
+    r7 = lr_shift <= 5.0 and (travel_ratio is None or travel_ratio <= 1.05)
+    accept = gain >= 0 and a_drop <= 0.5 and (keep is None or keep >= 0.95) and r7
+    out = {'old': ro, 'new': rn, 'gain_pp': gain, 'A_drop_pp': a_drop, 'fixed_kept': keep,
+           'R7_left_share_shift_pp': lr_shift, 'R7_travel_median_ratio': travel_ratio, 'R7_ok': r7, 'accept': accept}
     # 本轮新修好的题（旧错新对）留给下一轮做"仍对"检查
     fixed_now = [t for t, x, y in zip(tasks, so, sn) if (not x) and y]
     with open(a.out.replace('.json', '_fixed.jsonl'), 'w') as f:
         for t in fixed_now: f.write(json.dumps(t) + '\n')
     json.dump(out, open(a.out, 'w'), indent=1)
     if accept: shutil.copy(a.new, a.current)
-    print(json.dumps({k: out[k] for k in ('gain_pp', 'A_drop_pp', 'fixed_kept', 'accept')}))
+    print(json.dumps({k: out[k] for k in ('gain_pp', 'A_drop_pp', 'fixed_kept', 'R7_left_share_shift_pp', 'R7_travel_median_ratio', 'accept')}))
 
 
 if __name__ == '__main__':