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    2. Gemma-2-27B
    3. 22-GEMMASCOPE-RES-131K
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    Explanations

    The neuron fires on high‐level topic nouns—i.e. the key subject words used as section or document headings (like “eruption,” “truck,” “neutron,” etc.).

    oai_token-act-pair · o4-miniTriggered by @jyhe0408

    specific word pairings

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Configuration
    google/gemma-scope-27b-pt-res/layer_22/width_131k
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
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    Negative Logits
     réinitial
    -1.83
     déchir
    -1.72
     réve
    -1.69
     refroid
    -1.68
     motoru
    -1.57
     éte
    -1.56
     coute
    -1.56
     équilibr
    -1.56
     nettoy
    -1.55
    殽
    -1.55
    POSITIVE LOGITS
     as
    2.02
    y
    1.91
     in
    1.77
    r
    1.77
    g
    1.63
    z
    1.62
    f
    1.57
    in
    1.56
    t
    1.53
     for
    1.52
    Activations Density 0.083%

    No Known Activations