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    3. Gemma-3-12B
    5. 31-GEMMASCOPE-2-RES-16K
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    Explanations

    The neuron fires on stand-out content words—specialized, domain-specific keywords (e.g. CrossFit, core, cardiovascular, carbon, nuclear, energy-saving, Retina, FlexNav)—rather than common function words.

    oai_token-act-pair · o4-miniTriggered by @jyhe0408
    New Auto-Interp
    Top Features by Cosine Similarity
    Configuration
    google/gemma-scope-2-12b-pt/resid_post/layer_31_width_16k_l0_medium
    Prompts (Dashboard)
    392,802 prompts, 256 tokens each
    Dataset (Dashboard)
    monology/pile-uncopyrighted
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    Negative Logits
     miRNAs
    0.73
     mRNAs
    0.68
     cDNA
    0.64
     Saccharomyces
    0.64
     framebuffer
    0.63
     hepatocytes
    0.63
     mAbs
    0.61
     Coulomb
    0.61
     MoU
    0.61
     QTL
    0.60
    POSITIVE LOGITS
    whatever
    0.71
    Valentines
    0.70
    됬
    0.69
    偷偷
    0.67
    骇
    0.65
    Đi
    0.64
     وغيرها
    0.64
    Ά
    0.64
    Whatever
    0.63
    Exper
    0.62
    Activations Density 0.789%

    No Known Activations