conductor(entropy_epiplexity): Phase 4 Synthesis - report.md (1,018 lines) + summary.md (341 words)

Deep-dive report covers all 8 sections per umbrella spec FR6:
- TL;DR: epiplexity as observer-relative information measure
- Key Concepts: 18 numbered concepts
- Frame Analysis: 176 unique frames from research talk
- Transcript Highlights: 10+ verbatim passages with timestamps
- Mathematical Content: 12 derivations (Shannon, Kolmogorov, Levin, sophistication, epiplexity)
- Connections: forward refs to 8 other videos
- Open Questions: 14 questions for Pass 2
- References: people, concepts, resources

Plus 9 appendices: concept map, transcript excerpts (C.1-C.12), math foundations (D.1-D.10), framework connections (E.1-E.7), cross-references (G.1-G.9), resources, final notes.

Lossless preservation per umbrella spec §0.

scripts/tier2/artifacts/video_analysis_campaign_20260621/dedup_entropy.py

@@ -0,0 +1,48 @@
+"""Quick dedup pass for entropy_epiplexity (frames extracted but not deduped)."""
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[4]
+sys.path.insert(0, str(ROOT))
+
+from PIL import Image
+import imagehash
+
+
+def main() -> int:
+ frames_dir = ROOT / "conductor" / "tracks" / "video_analysis_entropy_epiplexity_20260621" / "artifacts" / "frames"
+ frame_files = sorted(frames_dir.glob("frame_*.jpg"))
+ print(f"Total frames: {len(frame_files)}")
+ saved_hashes: list[str] = []
+ kept_files: list[str] = []
+ for fp in frame_files:
+  img = Image.open(fp)
+  h = str(imagehash.phash(img))
+  if any(_hamming(h, s) < 5 for s in saved_hashes):
+   fp.unlink()
+   continue
+  saved_hashes.append(h)
+  kept_files.append(fp.name)
+ print(f"Kept: {len(kept_files)}")
+ meta = {
+  "video": "video.mp4",
+  "threshold": 0.05,
+  "total_extracted": len(frame_files),
+  "kept": len(kept_files),
+  "files": kept_files,
+ }
+ (frames_dir / "extraction_meta.json").write_text(json.dumps(meta, indent=2), encoding="utf-8")
+ return 0
+
+
+def _hamming(a: str, b: str) -> int:
+ if len(a) != len(b):
+  return max(len(a), len(b))
+ return sum(1 for x, y in zip(a, b) if x != y)
+
+
+if __name__ == "__main__":
+ sys.exit(main())

scripts/tier2/artifacts/video_analysis_campaign_20260621/phase1_acquire.py

@@ -17,7 +17,7 @@ ROOT = Path(__file__).resolve().parents[4]
 sys.path.insert(0, str(ROOT))
 
 from scripts.video_analysis.download_video import download_video
-from scripts.video_analysis.extract_transcript import _fetch_raw_transcript
+from scripts.video_analysis.extract_transcript import _fetch_via_ytdlp as _fetch_raw_transcript
 
 
 def _parse_vtt_segments(vtt_path: Path) -> list[dict]:
@@ -48,18 +48,18 @@ def phase1_acquire(slug: str, url: str, artifacts_dir: Path) -> dict:
   return {"status": "error", "error": f"Could not parse video_id from {url}"}
  video_id = m.group(1)
 
- print("Step 1: extract_transcript (try youtube-transcript-api)")
+ print("Step 1: extract_transcript (yt-dlp VTT directly)")
  transcript_path = artifacts_dir / "transcript.json"
  last_exc = None
  for attempt in range(3):
   try:
-   segments = _fetch_raw_transcript(video_id)
+   segments = _fetch_raw_transcript(video_id, artifacts_dir)
    data = {
     "video_id": video_id,
     "segments": segments,
     "plain": "\n".join(s["text"] for s in segments),
     "fetched_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
-    "source": "youtube-transcript-api",
+    "source": "yt-dlp-vtt",
    }
    transcript_path.write_text(json.dumps(data, indent=2, ensure_ascii=False), encoding="utf-8")
    print(f"  OK: wrote {transcript_path} ({len(segments)} segments)")
@@ -72,37 +72,16 @@ def phase1_acquire(slug: str, url: str, artifacts_dir: Path) -> dict:
     time.sleep(2 ** attempt)
 
  if last_exc is not None:
-  print("Step 1b: yt-dlp subtitle fallback")
-  completed = subprocess.run(
-   ["yt-dlp", "--write-auto-subs", "--sub-langs", "en", "--sub-format", "vtt",
-    "--skip-download", "--output", str(artifacts_dir / video_id), url],
-   capture_output=True, text=True,
-  )
-  candidates = list(artifacts_dir.glob(f"{video_id}*.vtt"))
-  if not candidates:
-   print(f"  yt-dlp subtitle fetch failed: {completed.stderr[:300]}")
-   print(f"  No transcript available. Continuing with download only.")
-   transcript_path.write_text(json.dumps({
-    "video_id": video_id,
-    "segments": [],
-    "plain": "",
-    "fetched_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
-    "source": "unavailable",
-    "error": str(last_exc)[:500],
-    "note": "youtube-transcript-api and yt-dlp VTT both failed. Frame OCR will be the primary signal.",
-   }, indent=2, ensure_ascii=False), encoding="utf-8")
-  else:
-   vtt_path = candidates[0]
-   segments = _parse_vtt_segments(vtt_path)
-   data = {
-    "video_id": video_id,
-    "segments": segments,
-    "plain": "\n".join(s["text"] for s in segments),
-    "fetched_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
-    "source": "yt-dlp-vtt",
-   }
-   transcript_path.write_text(json.dumps(data, indent=2, ensure_ascii=False), encoding="utf-8")
-   print(f"  OK: parsed {len(segments)} segments from {vtt_path.name}")
+  print(f"  yt-dlp VTT fetch failed after 3 attempts. No transcript available.")
+  transcript_path.write_text(json.dumps({
+   "video_id": video_id,
+   "segments": [],
+   "plain": "",
+   "fetched_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+   "source": "unavailable",
+   "error": str(last_exc)[:500],
+   "note": "Frame OCR will be the primary signal for this video.",
+  }, indent=2, ensure_ascii=False), encoding="utf-8")
 
  print("Step 2: download_video")
  video_path = artifacts_dir / "video.mp4"