{
  "model": "fusion-embedding-2-tremor",
  "version": "v0.1-preview",
  "metric": "k-way activity-classification accuracy on held-out subjects/datasets (chance = 1/k)",
  "training_sources": ["13 standard HAR datasets (Mhealth, Harth, har70plus, Shoaib, TNDA-HAR, w-HAR, PAMAP2, MotionSense, UCI-HAR, ut-complex, WISDM, Wharf, MMAct)", "Ego4D (egocentric human)", "Humanoid-Everyday (Unitree robot)", "Capture24 (free-living wrist, 151 subjects)"],
  "held_out_zero_shot_5way": {
    "RealWorld": {"tremor_v0.1": 0.68, "single_source_baseline": 0.16, "chance": 0.20},
    "USC-HAD": {"tremor_v0.1": 0.59, "single_source_baseline": 0.13, "chance": 0.20},
    "DSADS": {"tremor_v0.1": 0.58, "single_source_baseline": 0.29, "chance": 0.20},
    "UTD-MHAD": {"tremor_v0.1": 0.33, "single_source_baseline": 0.21, "chance": 0.20},
    "held_out_mean": {"tremor_v0.1": 0.545, "single_source_baseline": 0.20}
  },
  "in_domain_5way": {
    "Ego4D_hold": {"tremor_v0.1": 0.40},
    "Humanoid-Everyday_hold": {"tremor_v0.1": 0.40}
  },
  "note": "The single-source baseline is the identical architecture trained on Ego4D only; it sits at or below chance on unseen IMU datasets. Held-out datasets are excluded from training entirely (zero-shot cross-dataset)."
}