{
  "sample": true,
  "synthetic": false,
  "provenance": {
    "title": "Duck swimming at Knollenteich",
    "author": "PantheraLeo1359531",
    "source_page": "https://commons.wikimedia.org/wiki/File:Ente_am_Knollenteich_20250624_C1433.webm",
    "source_url": "https://upload.wikimedia.org/wikipedia/commons/f/fe/Ente_am_Knollenteich_20250624_C1433.webm",
    "source_sha256": "8d698a3b0c472b8c9dee480e12ef32c6cf3ff80d15d5275821b2a45d8c11130a",
    "license": "CC BY 4.0",
    "license_url": "https://creativecommons.org/licenses/by/4.0/",
    "recorded_at": "2025-06-24",
    "changes": "Resized to 640\u00d7360 and transcoded to H.264/AAC for browser playback; poster extracted. The source author notes color correction.",
    "authenticity_note": "The author describes this as their own camera footage. Source attribution is not a forensic guarantee of authenticity or an endorsement."
  },
  "purpose": "Reproducible UI and evidence-coverage example; not a detection accuracy benchmark.",
  "clip": "/samples/duck-pond.mp4",
  "poster": "/samples/duck-pond-poster.webp",
  "report": "/samples/duck-pond-report.json",
  "clip_sha256": "e5c5480a183fdfe90d1bbe4e84919f4c67d9185f706bc5da16e2cf2f1c61b526",
  "analyzer_source_sha256": "181d93adc48a609817cfe236c131e246b477e73c68709cc44660fd78ccbc3eaf",
  "reproduce": "python scripts/generate-commercial-sample.py",
  "result": {
    "schema_version": "aivd.report.v1",
    "service_version": "modal-ffmpeg-cv-audio-v11",
    "result_state": "uncertain",
    "ai_likelihood": 0.44,
    "confidence": 0.775,
    "platform": "upload",
    "source_info": {
      "duration_seconds": 9.292,
      "size_bytes": 1428596,
      "format_name": "mov,mp4,m4a,3gp,3g2,mj2",
      "bit_rate": 1230001,
      "width": 640,
      "height": 360,
      "fps": 24.0,
      "video_codec": "h264",
      "audio_codec": "aac",
      "audio_sample_rate": 48000,
      "audio_channels": 2,
      "audio_duration_seconds": 9.233,
      "audio_video_duration_delta_seconds": 0.059,
      "has_audio": true,
      "analysis_method": "sampled_visual_heuristics",
      "probability_calibrated": false,
      "requested_sample_positions_seconds": [
        1.549,
        4.646,
        7.743
      ],
      "audio_check_mode": "p0_audio_basic",
      "audio_windows_analyzed": 1,
      "audio_silence_ratio": 0.4762,
      "audio_clipping_ratio": 0.0
    },
    "frame_analysis": {
      "frame_count": 3,
      "compression_anomaly": 0.078,
      "temporal_consistency": 0.775,
      "texture_entropy": 0.688,
      "edge_consistency": 0.966,
      "sharpness_mean": 196.597
    },
    "public_metrics": {
      "audio_video_consistency": {
        "score": 0.003,
        "status": "checked",
        "level": "Basic audio technical check",
        "explanation": "Audio presence, duration alignment, silence, clipping, and level stability were checked with a low-cost audio sample. Paid reports can add sampled audio-motion windows. Semantic speech/video matching is not performed."
      }
    },
    "audio_video_analysis": {
      "status": "checked",
      "score": 0.003,
      "level": "Basic audio technical check",
      "explanation": "Audio presence, duration alignment, silence, clipping, and level stability were checked with a low-cost audio sample. Paid reports can add sampled audio-motion windows. Semantic speech/video matching is not performed.",
      "mode": "p0_audio_basic",
      "windows_analyzed": 1,
      "window_seconds": 20.0,
      "silence_ratio": 0.4762,
      "clipping_ratio": 0.0,
      "audio_dynamic_range": 0.0,
      "duration_delta_seconds": 0.059
    },
    "signals": [
      {
        "key": "metadata_reliability",
        "label": "Metadata reliability",
        "score": 0.75,
        "explanation": "ffprobe extracted container, stream, codec, duration, and bitrate metadata."
      },
      {
        "key": "compression_anomaly",
        "label": "Compression anomaly",
        "score": 0.078,
        "explanation": "Frame sharpness and histogram changes are checked for unusual compression/artifact patterns."
      },
      {
        "key": "temporal_consistency",
        "label": "Temporal consistency",
        "score": 0.775,
        "explanation": "Sampled frames are compared for frame-to-frame consistency."
      },
      {
        "key": "texture_entropy",
        "label": "Texture entropy",
        "score": 0.688,
        "explanation": "Sampled frame luminance entropy is used as a lightweight texture signal."
      },
      {
        "key": "edge_consistency",
        "label": "Edge consistency",
        "score": 0.966,
        "explanation": "Canny edge density variation is used as a simple artifact proxy."
      },
      {
        "key": "audio_video_consistency",
        "label": "Audio-video consistency",
        "score": 0.003,
        "status": "checked",
        "level": "Basic audio technical check",
        "explanation": "Audio presence, duration alignment, silence, clipping, and level stability were checked with a low-cost audio sample. Paid reports can add sampled audio-motion windows. Semantic speech/video matching is not performed."
      }
    ],
    "billing": {
      "credits": 1,
      "size_mb": 1.362,
      "duration_seconds": 9.292
    },
    "limitations": [
      "Visual indicators are rule-based screening signals, not a calibrated probability that a video is AI-generated.",
      "A few sampled frames cannot cover every moment; normal scene changes can affect visual indicators.",
      "This is a signal-based screening report, not proof.",
      "CPU ffmpeg/OpenCV signals are weaker than a dedicated forensic or GPU deepfake model.",
      "Social page URLs that cannot be safely fetched are not bypassed; upload/direct video URLs produce stronger reports."
    ],
    "recommendation": "Use this report as first-pass evidence. Manually review important cases before making public or high-impact decisions."
  }
}