Tighten relevance scoring and Polymarket ranking

Score against original user intent on Reddit, remove the artificial low-end relevance floor, and make Polymarket semantics dominate generic market quality signals.

Also apply the relevance filter to Polymarket and update the affected cross-source tests.

Validation: uv run python -m unittest

tests/test_instagram_sc.py

@@ -57,9 +57,9 @@ class TestComputeRelevance(unittest.TestCase):
         boosted = instagram._compute_relevance("claude code", "random video about stuff", ["claudecode", "ai"])
         self.assertGreater(boosted, base)
 
-    def test_floor_at_01(self):
+    def test_no_match_returns_zero(self):
         rel = instagram._compute_relevance("quantum physics", "cat dancing video")
-        self.assertGreaterEqual(rel, 0.1)
+        self.assertEqual(rel, 0.0)
 
     def test_empty_query_returns_default(self):
         rel = instagram._compute_relevance("", "Some video title")

tests/test_polymarket.py

@@ -569,8 +569,9 @@ class TestTextSimilarity(unittest.TestCase):
 
     def test_partial_token_overlap(self):
         score = polymarket._compute_text_similarity("Arizona Basketball", "Will Arizona win?")
-        # "Arizona" matches, "Basketball" doesn't -> 0.5
-        self.assertAlmostEqual(score, 0.5)
+        # Partial informative match should stay below exact match.
+        self.assertGreater(score, 0.3)
+        self.assertLess(score, 0.6)
 
     def test_no_overlap(self):
         score = polymarket._compute_text_similarity("Arizona Basketball", "Will AI regulation pass?")
@@ -595,7 +596,7 @@ class TestTextSimilarity(unittest.TestCase):
             "Who will be the #1 overall seed?",
             outcomes=["Duke", "Arizona", "Houston"],
         )
-        self.assertEqual(score, 0.85)
+        self.assertEqual(score, 1.0)
 
     def test_outcome_bidirectional_match(self):
         """Topic 'Arizona Basketball' should match outcome 'Arizona' (outcome in core)."""
@@ -604,16 +605,17 @@ class TestTextSimilarity(unittest.TestCase):
             "Who will be the #1 overall seed?",
             outcomes=["Duke", "Arizona", "Houston"],
         )
-        self.assertEqual(score, 0.85)
+        self.assertEqual(score, 0.88)
 
     def test_outcome_token_overlap(self):
-        """Partial token overlap with outcome gets 0.7 when no substring match."""
+        """Partial token overlap with outcome gets a moderate score."""
         score = polymarket._compute_text_similarity(
             "Iran War",
             "Unrelated geopolitics title",
             outcomes=["War continues", "Peace deal"],
         )
-        self.assertEqual(score, 0.7)
+        self.assertGreater(score, 0.3)
+        self.assertLess(score, 0.6)
 
     def test_outcome_no_match(self):
         """No outcome match falls through to title token overlap."""
@@ -632,7 +634,15 @@ class TestTextSimilarity(unittest.TestCase):
             "Unrelated title",
             outcomes=["Arizona"],
         )
-        self.assertEqual(score, 0.85)
+        self.assertEqual(score, 1.0)
+
+    def test_generic_only_odds_match_stays_below_threshold(self):
+        score = polymarket._compute_text_similarity(
+            "Anthropic odds",
+            "Republican 2026 House odds",
+            outcomes=["Yes", "No"],
+        )
+        self.assertLess(score, 0.3)
 
     def test_title_match_still_beats_outcome(self):
         """Title substring match (1.0) takes priority over outcome match (0.85)."""

tests/test_reddit_sc.py

@@ -47,16 +47,28 @@ class TestExpandRedditQueries(unittest.TestCase):
         self.assertGreaterEqual(len(queries), 1)
 
     def test_default_includes_review_variant(self):
-        queries = reddit.expand_reddit_queries("cursor IDE", "default")
+        queries = reddit.expand_reddit_queries("cursor IDE pricing", "default")
         self.assertTrue(any("worth it" in q or "review" in q for q in queries))
 
+    def test_default_skips_review_variant_for_prediction(self):
+        queries = reddit.expand_reddit_queries("anthropic odds", "default")
+        self.assertFalse(any("worth it" in q or "review" in q for q in queries))
+
+    def test_default_skips_review_variant_for_breaking_news(self):
+        queries = reddit.expand_reddit_queries("kanye west", "default")
+        self.assertFalse(any("worth it" in q or "review" in q for q in queries))
+
     def test_deep_includes_issues_variant(self):
-        queries = reddit.expand_reddit_queries("cursor IDE", "deep")
+        queries = reddit.expand_reddit_queries("cursor IDE pricing", "deep")
         self.assertTrue(any("issues" in q or "problems" in q for q in queries))
 
+    def test_deep_skips_issues_variant_for_prediction(self):
+        queries = reddit.expand_reddit_queries("anthropic odds", "deep")
+        self.assertFalse(any("issues" in q or "problems" in q for q in queries))
+
     def test_deep_has_more_queries_than_quick(self):
-        quick = reddit.expand_reddit_queries("cursor IDE", "quick")
-        deep = reddit.expand_reddit_queries("cursor IDE", "deep")
+        quick = reddit.expand_reddit_queries("cursor IDE pricing", "quick")
+        deep = reddit.expand_reddit_queries("cursor IDE pricing", "deep")
         self.assertGreater(len(deep), len(quick))
 
 

tests/test_relevance.py

@@ -75,7 +75,7 @@ class TestTokenOverlapRelevance(unittest.TestCase):
 
     def test_floor_at_0_1(self):
         rel = token_overlap_relevance("quantum physics", "cat dancing video")
-        self.assertGreaterEqual(rel, 0.1)
+        self.assertEqual(rel, 0.0)
 
     def test_full_match_returns_1(self):
         rel = token_overlap_relevance("python tutorial", "Python Tutorial for Beginners")
@@ -96,6 +96,15 @@ class TestTokenOverlapRelevance(unittest.TestCase):
         rel = token_overlap_relevance("the a is", "some content here")
         self.assertEqual(rel, 0.5)
 
+    def test_generic_only_overlap_stays_below_filter_threshold(self):
+        rel = token_overlap_relevance("anthropic odds", "Republican house odds update")
+        self.assertLess(rel, 0.3)
+
+    def test_informative_partial_match_stays_above_generic_only(self):
+        generic_only = token_overlap_relevance("anthropic odds", "Republican house odds update")
+        informative = token_overlap_relevance("anthropic odds", "Anthropic valuation market")
+        self.assertGreater(informative, generic_only)
+
 
 class TestHashtagRelevance(unittest.TestCase):
     """Tests for hashtag-aware relevance (TikTok/Instagram pattern)."""

tests/test_scrapecreators_x.py

@@ -44,9 +44,9 @@ class TestComputeRelevance(unittest.TestCase):
         score = scrapecreators_x._compute_relevance("", "some text")
         self.assertEqual(score, 0.5)
 
-    def test_floor_at_01(self):
+    def test_no_match_returns_zero(self):
         score = scrapecreators_x._compute_relevance("abcdef ghijkl", "xyz")
-        self.assertGreaterEqual(score, 0.1)
+        self.assertEqual(score, 0.0)
 
 
 class TestExtractCoreSubject(unittest.TestCase):

tests/test_tiktok.py

@@ -33,9 +33,9 @@ class TestTikTokRelevance(unittest.TestCase):
         rel = tiktok._compute_relevance("", "Some video title")
         self.assertEqual(rel, 0.5)
 
-    def test_floor(self):
+    def test_no_match_returns_zero(self):
         rel = tiktok._compute_relevance("quantum physics", "cat dancing video")
-        self.assertGreaterEqual(rel, 0.1)
+        self.assertEqual(rel, 0.0)
 
 
 class TestExtractCoreSubject(unittest.TestCase):

tests/test_youtube_relevance.py

@@ -62,7 +62,7 @@ class TestComputeRelevance(unittest.TestCase):
 
     def test_no_match(self):
         result = _compute_relevance("Claude Code", "Python Web Scraping")
-        self.assertEqual(result, 0.1)  # Floor
+        self.assertEqual(result, 0.0)
 
     def test_empty_query_returns_neutral(self):
         result = _compute_relevance("", "Some Video Title")
@@ -74,7 +74,7 @@ class TestComputeRelevance(unittest.TestCase):
 
     def test_empty_title(self):
         result = _compute_relevance("Claude Code", "")
-        self.assertEqual(result, 0.1)  # Floor
+        self.assertEqual(result, 0.0)
 
     def test_case_insensitive(self):
         result = _compute_relevance("claude code", "CLAUDE CODE Tutorial")
@@ -89,9 +89,9 @@ class TestComputeRelevance(unittest.TestCase):
         )
         self.assertEqual(result, 1.0)
 
-    def test_floor_at_0_1(self):
+    def test_no_match_returns_zero(self):
         result = _compute_relevance("quantum computing", "cat videos compilation")
-        self.assertEqual(result, 0.1)
+        self.assertEqual(result, 0.0)
 
     def test_cap_at_1_0(self):
         result = _compute_relevance("AI", "AI AI AI AI AI")
@@ -103,7 +103,7 @@ class TestComputeRelevance(unittest.TestCase):
 
     def test_single_word_no_match(self):
         result = _compute_relevance("Seedance", "Random cooking video")
-        self.assertEqual(result, 0.1)
+        self.assertEqual(result, 0.0)
 
 
 if __name__ == "__main__":