{
  "base_revision": "1a9eb8af2754ad2329a24cfe50d388cb559441d0",
  "artifact_revision": "a78fd9de52e4e3884e4530f634754d2a910a2c55",
  "teacher_cache_revision": "7b10485ee9d205ce2f7b660dfc6a90012d78b1cb",
  "seed": 92851,
  "generator_parameters": 3994676,
  "steps_per_arm": 2000,
  "batch_size": 32,
  "arms": [
    "control",
    "region"
  ],
  "matched": "Same fixed selected targets, input augmentation batches, initial weights, optimizer and updates. Treatment adds .4 object residual consistency + .15 local missing chroma.",
  "supervised": "L1/20 + .25 sliced chroma distribution + .1 gradient difference (existing r.losses)",
  "target_choice": "One complete original or cached DDColor target per training image, selected once by v3 complete-image loss. No per-pixel target mixing. Reject teacher proposal if it removes over40% of original chroma or has >1.5x+1.5 mean chroma edge strength.",
  "region_loss": "Mean absolute spatial residual after subtracting regional mean prediction-target error. Allows constant alternative hue shifts while retaining target patterns.",
  "segmentation": "Frozen torchvision DeepLabV3 ResNet50 COCO_WITH_VOC_LABELS_V1 on original RGB, default520px preprocessing. Confident connected foreground interiors + homogeneous original-color SLIC background surfaces. Max64 regions/image.",
  "inference": "Unchanged architecture and one-pass inference; segmentation/teacher are training-only.",
  "data": "Seeded8192 subset of original training fold; pinned Imagenette/COCO shards and verified cached DDColor. 50% mild archival-style input degradations.",
  "evaluation": "Reused dense-run development and test are explicitly regression sets. New128 COCO val/0001 examples exclude round7 and dense-run evaluation IDs and training byte duplicates. New holdout used only after training; familiar archived-photo probes are not independent historical validation.",
  "limitations": [
    "20 foreground semantic classes only",
    "touching same-class objects can merge",
    "RGB-derived masks are imperfect",
    "DDColor targets are fallible",
    "teacher/encoder upstream pretraining overlap unknown",
    "one seed and short pilot",
    "synthetic film variation is not true archival training",
    "frozen target selection can retain v3 biases"
  ],
  "budget": {
    "hard_timeout_minutes": 30,
    "training_stop_minutes": 23,
    "maximum_compute_usd": 1.25
  },
  "release_policy": "All checkpoints retained for review; no automatic production replacement"
}