fix(confidence): pass multi_lens_observed kwarg to merge_confidence

tests/pilot/test_ai_review.py

@@ -1855,8 +1855,25 @@ def test_merge_confidence_critical_drops_to_one():
 
 
 def test_merge_confidence_multi_lens_drops_extra():
-    f = {"severity": "low", "_multi_lens": True}
-    assert merge_confidence([f]) == 4
+    # The flag has moved to a kwarg; passing `_multi_lens` on the dict is no
+    # longer enough — the kwarg is the only path that drops the score.
+    f = {"severity": "low"}
+    assert merge_confidence([f], multi_lens_observed=True) == 4
+
+
+def test_merge_confidence_multi_lens_survives_normalization():
+    """Real flow: `_multi_lens` is set on the raw finding, but stripped by
+    `_normalize_finding`. `merge_confidence(...)` with only the kwarg sees a
+    normalized finding; the dedup must be triggered by `multi_lens_observed=`
+    being true, not by reading `_multi_lens` off the dict."""
+    raw = {"_multi_lens": True, "severity": "low", "path": "x", "line": 1,
+           "problem": "p", "fix": "", "suggestion": "", "reference": ""}
+    normalized = _normalize_finding(raw)
+    assert "_multi_lens" not in normalized  # confirms the strip
+    # Now call merge_confidence the way review_pr will:
+    assert merge_confidence([normalized], multi_lens_observed=True) == 4
+    # And without the kwarg, the flag-on-dict path is gone:
+    assert merge_confidence([normalized]) == 5
 
 
 def test_merge_confidence_clamped():