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    Okay, let's analyzeThe `MAX_ACTIVATING_TOKENS` list is empty.The `TOKENS_AFTER_MAX_ACTIVATING_TOKEN` list contains `<start_of_turn>` repeated many times. This suggests the model is often at the beginning of a turn or response.The `TOP_POSITIVE_LOGITS` include words like "Here", "Okay", "It", "We", "Several", "Popular", "Especially".The `TOP_ACTIVATING_TEXTS` consistently show a pattern: `<start_of_turn>user ... <end_of_turn> <start_of_turn>model Okay, ...`. Okay, let's analyzeThe `MAX_ACTIVATING_TOKENS` list is empty.The `TOKENS_AFTER_MAX_ACTIVATING_TOKEN` list contains `<start_of_turn>` repeated many times. This suggests the model is often at the beginning of a turn or response.The `TOP_POSITIVE_LOGITS` include words like "Here", "Okay", "It", "We", "Several", "Popular", "Especially".The `TOP_ACTIVATING_TEXTS` consistently show a pattern: `<start_of_turn>user ... <end_of_turn> <start_of_turn>model Okay, ...`.The pattern is that the neuron activates when the model has just completed a user turn (`<start_of_turn>user ... <end_of_turn>`) and is about to start its model response, often beginning with "Okay" or similar introductory phrases.This neuron seems to detect the transition from a user's input to the model's initiating response.Given the empty `MAX_ACTIVATING_TOKENS`, and `TOKENS_AFTER_MAX_ACTIVATING_TOKEN` being `<start_of_turn>`, and `TOP_POSITIVE_LOGITS` having words like "Okay", "Here", it strongly indicates the neuron fires when the model is *starting* to respond, often with phrases like "Okay" or "Here".The most specific pattern is the model beginning its response after a user prompt.Revised thought process:The examples show a clear structure: user asks something, then model replies, often starting with "Okay" or "Here".The `TOKENS_AFTER_MAX_ACTIVATING_TOKEN` being `<start_of_turn>` suggests the activation happens *before* the main content of the model's response, right at the `start_of_turn` for the model.The `TOP_POSITIVE_LOGITS` like "Here", "Okay", and "Popular" are common greetings or ways to start an answer.The neuron appears to be sensitive to the model beginning its answer.Explanation: "model response initiation" or "model starting to answer" seems appropriate.Let's check constraints: 3-20 words, no "tokens", no "patterns", no "This neuron detects/predicts"."model response initiation" - 3 words. Fits."starting to answer user questions" - 4 words. Fits."beginning of model's prepared answer" - 5 words. Fits.Considering the very common "Okay," at the start of many model responses in the `TOP_ACTIVATING_TEXTS`, perhaps the neuron is focused on phrases that *begin* a model's response.The provided `MAX_ACTIVATING_TOKENS` is empty, which makes it harder. However, `TOKENS_AFTER_MAX_ACTIVATING_TOKEN` is consistently `<start_of_turn>`, indicating the neuron fires *at the start* of the model's turn. The `TOP_POSITIVE_LOGITS` include "Here", "Okay", "It", "We", "Several", "Popular", which are common starting words for model explanations.The best fit is that the neuron activates when the model is beginning to provide an answer or response.Let's try: "beginning model answer"Or: "model response start"Or: "initiating model response"The `TOP_POSITIVE_LOGITS` are "Here", "Popular", "It", "Several", "In", "Okay", "We", "Berikut", "Especially". These words are often used to *start* responses or provide introductory phrases.The `TOKENS_AFTER_MAX_ACTIVATING_TOKEN` are all `<start_of_turn>`, confirming the neuron fires at the very beginning of the model's turn.Focus on the *start* of the model's response."model response commencement" - 3 words."initiating model reply" - 3 words."beginning of model answer" - 4 words.Let's look at the `TOP_ACTIVATING_TEXTS` again. Almost every `model` response starts with "Okay," or "Here," or "Let's".The neuron is predicting the start of these common model responses."response initiation phrases" - 3 words? No, that's a category."starting phrases for model answers" - 5 words."phrases that initiate model responses" - 5 words.The examples show the model *always* starts with conversational filler ("Okay,", "Here,", "Let's").The neuron is related to these initial conversational fillers."conversational response starters" - 3 words."preparing to answer query" - 4 words."model's opening reply" - 3 words."Okay, let's..." is a very common pattern.So, it's about the *start* of the model's reply."start of model reply" is exactly 4 words. It's specific.Let's stick to the most direct interpretation of the observed data. The neuron fires when the model is about to start its response."model response commencement" -

    np_acts-logits-general · gemini-2.5-flash-lite
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    google/gemma-scope-2-1b-it/resid_post/layer_17_width_16k_l0_medium
    Prompts (Dashboard)
    238,145 prompts, 512 tokens each
    Dataset (Dashboard)
    lmsys + oasst1
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    Negative Logits
     -
    1.05
     had
    0.94
     take
    0.94
     derived
    0.91
     –
    0.90
     a
    0.89
     which
    0.89
     +
    0.88
     /
    0.88
     (
    0.87
    POSITIVE LOGITS
    Here
    1.17
    Popular
    1.05
    It
    1.01
    Several
    0.99
    In
    0.99
    Okay
    0.98
    We
    0.98
    Berikut
    0.97
    Especially
    0.96
    Ine
    0.96
    Activations Density 0.173%

    No Known Activations