Feature Iteration Run #576: zz_sylvain

# AUTOLOOP: zz_sylvain (3 iterations)

> **Phase**: Y4.7 Option B (DSL → Python code → FeatureSet candidate)
> **Target indicator**: zz_sylvain
> **Base feature_set_id**: 7
> **Claim**: (default) Propose a new k_* feature that improves risk-adjusted returns
> **Objective mode**: scalarize
> **Metrics**: ['profit_factor', 'sharpe_ratio', 'win_rate', 'max_drawdown', 'test_accuracy']
> **Total duration**: 116.90s
> **Total accepted**: 2
> **Total rejected**: 1

## Iterations 詳情

### Iteration 1
- DSL: `k_high.pct_change(12) - k_low.pct_change(12)` (feature=k_loop_iter_1_341fcc)
- DSL valid: True
- FeatureSet candidate id: 681
- baseline PF: 1.286 → modified PF: 1.404
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.7421
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.286, modified=1.404, diff=0.118
  - sharpe_ratio: baseline=7.879, modified=10.708, diff=2.829
  - win_rate: baseline=0.553, modified=0.568, diff=0.015
  - max_drawdown: baseline=0.075, modified=0.051, diff=-0.023
  - test_accuracy: baseline=0.986, modified=0.986, diff=0.000

### Iteration 2
- DSL: `(k_high.pct_change(12) - k_low.pct_change(12)) * i_atr(k_high, k_low, k_close, 14)` (feature=k_loop_iter_2_dce0f6)
- DSL valid: True
- FeatureSet candidate id: 682
- baseline PF: 1.286 → modified PF: 1.520
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 1.3687
- accepted: True, reason: accepted

**Metrics summary:**
  - profit_factor: baseline=1.286, modified=1.520, diff=0.234
  - sharpe_ratio: baseline=7.879, modified=13.066, diff=5.187
  - win_rate: baseline=0.553, modified=0.580, diff=0.027
  - max_drawdown: baseline=0.075, modified=0.051, diff=-0.023
  - test_accuracy: baseline=0.986, modified=0.986, diff=0.000

### Iteration 3
- DSL: `(return_5 * vol_ratio) - (hl_range * dist_to_high)` (feature=k_loop_iter_3_2b7a37)
- DSL valid: True
- FeatureSet candidate id: 683
- baseline PF: 1.286 → modified PF: 1.286
- t_stat: 0.000, p_value: 1.000, cohens_d: 0.000
- scalar_score: 0.0000
- accepted: False, reason: p=1.000 ≥ 0.05, cohens_d=0.000 ≤ 0.3

**Metrics summary:**
  - profit_factor: baseline=1.286, modified=1.286, diff=0.000
  - sharpe_ratio: baseline=7.879, modified=7.879, diff=0.000
  - win_rate: baseline=0.553, modified=0.553, diff=0.000
  - max_drawdown: baseline=0.075, modified=0.075, diff=0.000
  - test_accuracy: baseline=0.986, modified=0.986, diff=0.000