{
  "video_id": "bfd481a56e25d62b",
  "channel": "export-arxiv-org-rss-cs-ai",
  "title": "When LLMs Agree, Are They Right? Auditing Self-Consistency and Cross-Model Agreement as Confidence Signals",
  "scores": {
    "depth": 3,
    "novelty": 3,
    "aria_relevance": 3,
    "production_ready": 2
  },
  "junk_penalty": 0,
  "avg_score": 2.75,
  "effective_score": 2.75,
  "verdict": "promote",
  "one_line_reason": "Rigorous empirical audit of LLM-as-judge assumption with 265k samples; directly challenges consensus-as-confidence heuristic in eval pipelines—critical for Aria's multi-agent eval and confidence calibration architecture.",
  "model": "claude-haiku-4-5-20251001",
  "cost_usd": 0.001916,
  "triaged_at": "2026-07-10T15:02:56.378908+00:00"
}