conductor(probability_logic): transcript_clean.txt (10k words) + presentation frame extractor

scripts/tier2/artifacts/video_analysis_campaign_20260621/extract_pres_frames.py

@@ -0,0 +1,16 @@
+from pathlib import Path
+content = Path('conductor/tracks/video_analysis_probability_logic_20260621/artifacts/ocr.md').read_text()
+chunks = content.split('## ')
+for chunk in chunks[1:]:
+    name = chunk.split('\n')[0].strip()
+    body = chunk
+    fence = chr(96)*3
+    if fence in body:
+        parts = body.split(fence)
+        body = parts[1] if len(parts) >= 2 else body
+    is_chat = 'Streamer Mode' in body or 'Yesterday at' in body or '21:43' in body
+    has_pres = any(s in body for s in ['Definition', 'Logic', 'Probabil', 'Bayesian', 'Frequentist', 'Boolean', 'Lattice', 'Inference', 'Sum Rule', 'Product Rule'])
+    if has_pres and not is_chat:
+        print(f'=== {name} ===')
+        print(body[:800])
+        print()