outputs/embedding_analysis/embedding_model_config.json

{
  "analysis_label": "exploratory_embedding_analysis",
  "embedding_dim": 256,
  "embedding_model": "local_hashing_token_ngram_v1",
  "hash_function": "zlib.crc32 signed feature hashing",
  "inputs": {
    "condition_level": "outputs\\condition_level_representations.jsonl",
    "sliding_window": "outputs\\sliding_window_representations.jsonl"
  },
  "library": "numpy",
  "ngram_range": [
    1,
    2
  ],
  "normalization": "l2",
  "not_included": [
    "neural embeddings",
    "latent model hidden states",
    "logits",
    "probabilities",
    "reaction times",
    "API costs",
    "latency measurements"
  ],
  "projection": "PCA via numpy.linalg.svd with deterministic component sign convention",
  "tokenizer_regex": "[a-z0-9_]+"
}