{
  "schema": "studycommons.hero.provenance.legacy.v1",
  "asset_role": "Study Commons Daily Read hero",
  "slug": "how-traffic-lights-know",
  "generator": "QwenImage21Pipeline",
  "generation_id": "img-96f262b4c37f94e38fb0c0bd",
  "model_id": "Qwen/Qwen-Image-2.1",
  "model_revision": "b3179ad355be050328e483a9dfdd9e60cd62adfa",
  "model_index_sha256": "cf1ecd104ea090855d60d8cec0895c1e9d6ee41b2f87e231b678beecd1cf7809",
  "scheduler_config_sha256": "5895f3a167c14a967fe9ac70c64924ae5acc79799e0679fd12907e594a713cd1",
  "checkpoint_sha256": "7f17c6a21036f6c085010c689172ca62b4a6af197d162494dc35eca6eab811da",
  "checkpoint_weights": [
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      "file": "vae/diffusion_pytorch_model.safetensors",
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  ],
  "checkpoint_fingerprint_note": "Checkpoint fingerprints recorded during retrospective reproduction, not at first generation; independently reproduced PNG and AVIF are byte-identical to the original approved files.",
  "model_license": "Qwen Research License; non-commercial research/evaluation only. Separate permission required for commercial use.",
  "prompt": "Polished 16:9 documentary-style educational hero image for a Canadian Grade 4-5 article about how traffic lights know when to change. Realistic suburban signalized intersection in daylight. A normal passenger car waits behind the stop line at a red traffic signal. In the right foreground, show a realistic human hand pressing a standard pedestrian crosswalk push button with the INDEX FINGER ONLY. The index finger is clearly extended and touching the center of the button; the middle finger, ring finger and little finger are visibly curled back toward the palm; the thumb is visible at the side. The hand anatomy must be natural and unmistakable, with no other finger touching the button. Beside the pole is a realistic grey traffic-signal controller cabinet. Across the intersection are coherent signal heads and ordinary road markings. Clean Canadian suburban setting, crisp documentary photography, technically plausible traffic hardware, child-friendly, restrained cinematic light, uncluttered composition, no visible detector-loop drawings, no fake sensor markings, no text, no labels, no arrows, no logos, no watermark.",
  "prompt_sha256": "7020af443997c3b65d51f625cc6ffcee648ad742c040414533fb41c9c661352b",
  "negative_prompt": "middle finger touching button, middle finger extended, rude gesture, obscene gesture, wrong finger pressing button, extra fingers, missing fingers, fused fingers, malformed hand, floating hand, disembodied arm, text, letters, labels, infographic, arrows, diagram, watermark, logo, cartoon, fantasy, crash, police, emergency vehicles, contradictory signal colors, impossible lane geometry, duplicate cars, blurry, oversaturated",
  "seed": 24092451,
  "num_inference_steps": 20,
  "true_cfg_scale": 4.0,
  "requested_width": 1280,
  "requested_height": 720,
  "actual_width": 1280,
  "actual_height": 704,
  "width": 1280,
  "height": 704,
  "scheduler": "FlowMatchEulerDiscreteScheduler",
  "scheduler_config": {
    "_class_name": "FlowMatchEulerDiscreteScheduler",
    "_diffusers_version": "0.37.0.dev0",
    "base_image_seq_len": 256,
    "base_shift": 0.5,
    "invert_sigmas": false,
    "max_image_seq_len": 8192,
    "max_shift": 0.9,
    "num_train_timesteps": 1000,
    "shift": 1.0,
    "shift_terminal": 0.02,
    "stochastic_sampling": false,
    "time_shift_type": "exponential",
    "use_beta_sigmas": false,
    "use_dynamic_shifting": true,
    "use_exponential_sigmas": false,
    "use_karras_sigmas": false
  },
  "generator_device": "cuda",
  "generator_algorithm": "torch.Generator(device='cuda:0').manual_seed(seed)",
  "torch_dtype": "bfloat16",
  "cpu_offload": "model",
  "vae_tiling": false,
  "use_kv_cache": true,
  "lora": null,
  "reference_images": [],
  "gpu": "CUDA GPU (device-specific details intentionally excluded)",
  "output_png_sha256": "96f262b4c37f94e38fb0c0bd49bfa7290de1bbe18a0b454112e49eae1acce751",
  "postprocess": {
    "format": "AVIF",
    "encoder": "libaom-av1",
    "filter": "scale=1280:720:force_original_aspect_ratio=increase:flags=lanczos,crop=1280:720",
    "still_picture": 1,
    "crf": 1,
    "bitrate": 0,
    "cpu_used": 6,
    "pix_fmt": "yuv420p",
    "frames": 1,
    "ffmpeg_version": "ffmpeg version 6.1.1-3ubuntu5",
    "source_png_sha256": "96f262b4c37f94e38fb0c0bd49bfa7290de1bbe18a0b454112e49eae1acce751",
    "output_avif_sha256": "3fe626991c08f92d85ccdc4fb425997058bfa405fcc122820783da86e23fdfb6",
    "output_avif_width": 1280,
    "output_avif_height": 720,
    "output_avif_bytes": 198719
  },
  "reproduction_verification": {
    "verified_at": "2026-10-14T11:40:05.523963+00:00",
    "runtime": {
      "torch": "2.14.0+cu130",
      "diffusers": "0.41.0.dev0",
      "transformers": "5.17.0",
      "cuda": "13.0"
    },
    "model_revision": "b3179ad355be050328e483a9dfdd9e60cd62adfa",
    "png_byte_identical": true,
    "avif_byte_identical": true,
    "original_generation_runtime": "not independently recorded at original generation",
    "original_publication_date": "2026-09-25",
    "verification_notes": "Original approved PNG and original AVIF have been recreated byte-identically using the identified model checkpoint, recorded seed and exact postprocessing settings."
  },
  "reproduce": {
    "script": "tools/reproduce_legacy_hero.py",
    "command": "python3 tools/reproduce_legacy_hero.py --provenance hero-provenance.json --model-dir MODEL_DIR --png replay.png --avif replay.avif --strict-hash",
    "requirements": "Licensed Qwen Image 2.1 checkpoint, CUDA-capable environment, Diffusers, Transformers, PyTorch and FFmpeg. Version details are in reproduction_verification.runtime."
  },
  "provenance_note": "Retrospective evidence-backed reproduction record. Independently verified matching PNG and AVIF SHA-256; original runtime versions not separately captured at generation time. This is not a copyright or commercial-use license."
}