fix: canonicalize score brackets and assessments

ml/optimizer.py

@@ -26,6 +26,8 @@ from sklearn.metrics import (
 from sklearn.model_selection import TimeSeriesSplit
 from sklearn.preprocessing import StandardScaler
 
+from scoring.policy import SCORE_BRACKETS, score_in_bracket
+
 logging.basicConfig(
     level=logging.INFO,
     format="%(asctime)s [%(name)s] %(levelname)s: %(message)s",
@@ -117,14 +119,7 @@ INTERACTION_FEATURES = ["mvrv_x_nupl", "puell_x_reserve"]
 CYCLE_FEATURES = ["days_since_ath"]
 FEATURE_COLS = SCORE_FEATURES + RAW_FEATURES + DELTA_FEATURES + INTERACTION_FEATURES + CYCLE_FEATURES
 
-BRACKETS = [
-    (0, 20, "Extreme Caution"),
-    (21, 40, "Caution"),
-    (41, 55, "Neutral"),
-    (56, 70, "Moderate Opportunity"),
-    (71, 85, "Strong Accumulation"),
-    (86, 100, "Extreme Accumulation"),
-]
+BRACKETS = SCORE_BRACKETS
 
 
 def _row_date(row):
@@ -526,7 +521,7 @@ def _composite_score(row, mode, ml_weights=None):
 def _summarize_brackets(scored_rows, score_key):
     results = []
     for low, high, label in BRACKETS:
-        days_in = [r for r in scored_rows if low <= r[score_key] <= high]
+        days_in = [r for r in scored_rows if score_in_bracket(r[score_key], (low, high, label))]
         if not days_in:
             results.append({
                 "range": f"{low}-{high}", "label": label,