{
  "schema_version": 1,
  "seed": 20261025,
  "sample_count": 50,
  "models_expected": [
    "pe-av-small-16-frame",
    "pe-av-base-16-frame",
    "pe-av-large-16-frame",
    "pe-av-small",
    "pe-av-base",
    "pe-av-large"
  ],
  "models_complete": [
    "pe-av-small-16-frame",
    "pe-av-base-16-frame",
    "pe-av-large-16-frame",
    "pe-av-small",
    "pe-av-base",
    "pe-av-large"
  ],
  "complete": true,
  "target": {
    "name": "dino_adjacent_cosine_distance_mean",
    "definition": "Mean of four adjacent cosine distances between L2-normalized DINOv2-small CLS embeddings of five evenly sampled frames in the first at most 30 seconds.",
    "model": "facebook/dinov2-small",
    "model_revision": "ed25f3a31f01632728cabb09d1542f84ab7b0056",
    "minimum": 0.0005012750625610352,
    "maximum": 0.8779892921447754,
    "mean": 0.33711791545152664,
    "standard_deviation": 0.25308041019439664,
    "motion_metrics_sha256": "4544291023bd4b0bee6c7cf9836bd57bab8819b2f34038bd61481b7bece1434a"
  },
  "method": {
    "folds": 5,
    "outer_train_videos": 40,
    "outer_test_videos": 10,
    "inner_training_videos": 32,
    "inner_validation_videos": 8,
    "split": "One seeded random permutation split into five disjoint test folds; identical folds and inner partitions for every model. Each video has exactly one held-out prediction.",
    "input": "Frozen, normalized whole-clip video embeddings only; no audio, DINO frame embeddings, target-derived metrics, or video identifier is used as a feature.",
    "preprocessing": "Fit centered PCA to training videos only; retain at most 16 components, then standardize retained component scores using training means/standard deviations. Target scaling also uses training data only.",
    "early_stopping": "Select epoch using only 32 inner-fit and 8 inner-validation videos, with all preprocessing fit on the 32. Reinitialize and refit using all 40 outer-training videos for the selected epoch count, then predict the 10 untouched outer-test videos.",
    "ridge_alpha": 10.0,
    "mlp": {
      "hidden_units": 8,
      "activation": "ReLU",
      "learning_rate": 0.01,
      "weight_decay": 0.01,
      "maximum_epochs": 500,
      "patience": 40,
      "minimum_validation_improvement": 0.0001,
      "optimizer": "AdamW",
      "batch": "full training subset",
      "loss": "mean squared standardized-target error"
    },
    "network": "16 PCA inputs -> 8 ReLU hidden units -> 1 linear output (145 parameters when 16 components retained).",
    "selection": "No tuning, selection of prompts, or hyperparameter search on outer-test results; raw regression predictions are not clipped.",
    "r2_definition": "Pooled out-of-fold R2 = 1 - sum((target-prediction)^2)/sum((target-global_target_mean)^2). Mean baseline predicts each outer training-fold mean, so its OOF R2 need not be zero.",
    "zero_shot_contrast_predefined": "Mean cosine(slideshow, cartoon/animation, moving live action) minus mean cosine(static photo, static image with captions)."
  },
  "limitations": [
    "Exploratory 50-video experiment with five small test folds; performance is unstable and is not a validated deployment result.",
    "One fixed split seed and one MLP initialization per fold; no confidence interval or estimate of variability across split/initialization seeds.",
    "DINO semantic frame change is a computed proxy, not human motion/static-video ground truth. It responds to cuts, viewpoint and semantic changes and can miss brief or subtle motion between sampled frames.",
    "The target encoder differs from the PEAV predictor; both describe the same videos, so this does not constitute an independent human-label validation.",
    "Video-level separation prevents frame leakage within a video, but unverified near-duplicate or related source videos could still span folds.",
    "A positive R2 indicates prediction of this proxy only; a negative R2 means the predictions underperform the global target-mean reference. Compare also the held-out train-mean baseline.",
    "Zero-shot prompt associations are separate descriptive correlations without fitted calibration; no classification accuracy or sound/motion probabilities are claimed."
  ],
  "runtime": {
    "device": "CPU",
    "cpu_affinity": [
      64,
      65,
      66,
      67,
      68,
      69,
      70,
      71,
      72,
      73,
      74,
      75,
      76,
      77,
      78,
      79
    ],
    "torch_threads": 1,
    "torch_version": "2.10.0+cu130",
    "numpy_version": "2.3.5",
    "analysis_source_sha256": "aeed86dffb3f08a3a54c4ec2c22693ae5894793a0789b7b31ced0ad21ec69002"
  },
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