{
  "video_id": "a1cac58ac271db2f",
  "channel": "export-arxiv-org-rss-cs-ai",
  "title": "FlowR2A: Learning Reward-to-Action Distribution for Multimodal Driving Planning",
  "scores": {
    "depth": 2,
    "novelty": 2,
    "aria_relevance": 1,
    "production_ready": 1
  },
  "junk_penalty": 0,
  "avg_score": 1.5,
  "effective_score": 1.5,
  "verdict": "summary_only",
  "one_line_reason": "Solide ML-Paper zu Autonomous Driving mit Flow-Matching-Innovation, aber keine direkte Aria-Relevanz (kein Multi-Agent, Memory, LLM-Distribution, observability); technisch sauber, aber spezialisiert auf Driving-Domain.",
  "model": "claude-haiku-4-5-20251001",
  "cost_usd": 0.001853,
  "triaged_at": "2026-06-24T15:02:42.221441+00:00"
}