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    The neuron seems to be activated by words and phrases related to "Cámara" (camera), particularly in contexts like "Cámara de Comercio" (Chamber of Commerce) and "Cámaras de seguridad" (security cameras). It also appears in sequences starting with "Cam" or "Camar" that lead to words like "camaradería" (camaraderie) or forms of "cámara". There's also a less prominent connection to "Senado" (Senate).Considering the prompt's rules:- Concise explanation (3-20 words).- Find a pattern.- Avoid listing tokens.- Be specific.- Do not start with "This neuron detects/predicts" or mention "tokens" or "patterns".- Do not capitalize the first letter unless it is a proper noun.The most striking pattern is the recurring presence of "Cámara" and its variants, often followed by terms related to security, commerce, or specific institutional bodies (like la Cámara de Comercio). The "Camar-" prefix also appears, linking to "camaradería".Let's try to capture this.1. **Camera and Commerce/Security Contexts**: "Cámara" is present, and contexts include "Comercio" and "seguridad".2. **Camaraderie**: "Camaradería" is mentioned.3. **Cam- prefix**: "Camarero" is one of the activating texts.The dominant theme is "Cámara" and its direct associations, plus the "Camar-" prefix leading to related concepts.Possible explanations:- cámara, seguridad, comercio, camaradería- Cámara de Comercio, cámaras de seguridad- cámaras, camaradería, comercioLet's refine to be more abstract and capture the essence without listing. The neuron seems to associate 'camera' with organizational contexts (commerce, senate) and also 'camar-' with positive social interaction ('camaradería').Think about the core *meaning* of these appearances.- Cámara: device, institution, assembly.- Cámara de Comercio: an institution.- Cámaras de seguridad: security devices.- Camaradería: friendship, fellowship.- Camarero: a profession.- Senado: an institution.The TOP_POSITIVE_LOGITS suggest financial or numerical contexts ($ , revenue, Auction, reward, Cow, Rew, ). This doesn't seem strongly connected to the MAX_ACTIVATING_TOKENS or TOP_ACTIVATING_TEXTS. The instructions say: "Not ALL top activating texts/tokens have to match the exact same pattern, but a majority should."Let's re-evaluate MAX_ACTIVATING_TOKENS and TOKENS_AFTER_MAX_ACTIVATING_TOKEN first.MAX_ACTIVATING_TOKENS: Cámara, de, cámaras, camar, Cam, ar, camar, cámaras, Senado, CamTOKENS_AFTER_MAX_ACTIVATING_TOKEN: de, seguridad, ,, ero, pos, illa, adería, ,, )., inito- Cámara de seguridad- Cámaras de seguridad- Cámara de Comercio- SenadoThe "Camar-" part connects to "camarero" and "camaradería"."Cámara" connects to "seguridad" and "Comercio".Let's focus on the strong `cámara, cámaras` and `camar` patterns.`cámara` is followed by `de seguridad`, `de Comercio`.`camar` is followed by `ero` (leading to camarero), `adería` (leading to camaradería).It seems to be about entities and relationships.- `Cámara` (camera/chamber) itself, and its uses.- `Camar-` prefixes related to professions and social groups.What if the neuron distinguishes between the *device* `cámara` and the *institution* `Cámara de Comercio` or `Senado`? Or perhaps it's just about the root `cámara` and related prefixes like `camar-`.Considering the specific instruction "finding patterns in lists":The most frequent root is "Cam" or "Cámar" or "Cámar".It appears as:- Cámara- cámaras- Camar- camar- Senado (less frequent but present in max activating tokens)The tokens after highlight:- de seguridad (Cámara de seguridad)- de Comercio (context from activating text)- ero (camarero)- adería (camaradería)So, the pattern is "Cam" or "Cámar" potentially followed by specific suffixes or words.The question is how to phrase this concisely and specifically."Camera, chamber, camaraderie" - this is a list, rules say avoid listing all tokens."Camera and related prefixes" - too meta."camera, chamber, senate, camar-:prefix" - still listing.Let's look at the overall theme.- Camera (device)- Chamber (institution), eg. Chamber of Commerce- Senate (institution)- Camar - prefix for profession (camarero) or social group (camaradería).It's a blend of literal object (camera) and abstract concepts derived from similar roots.How about focusing on the common root and its diverse meanings?"cam/cám- roots: camera, chamber, comrade" -- "comrade" isn't directly there, but "camaradería" implies it.Let's reread the rules:- "finding patterns in lists"- "concise explanation (3 to 20 words)"- "could be a single word, or phrase, or pattern."- "could be about tokens following or preceding certain tokens."- "could be about words starting with a sequence."- "Avoid simply listing all the tokens. Instead, try to find patterns."- "Just say the pattern itself"- "Do not mention "tokens" or "patterns" in your explanation."The pattern is the prefix "cam" or "cám" and its variations/extensions.The output is what the neuron *detects or predicts*.It detects words that start with "Cam" or "Cám" and then often lead to specific contexts.- **Cámara** -> de seguridad (...), de Comercio (...).- **Camar** -> ero (...), adería (...).- **Cam** -> Sen (...), Cám (...).Let's try to generalize from these.The neuron is sensitive to the "Cam-" sound/spelling. It distinguishes between camera (device) and chamber (institution), and also social contexts like camaraderie.What about something that emphasizes this duality or spread?"Camera, chamber, social groups""camera, institution, camaraderie""cam- prefixes: camera, commerce, senate, fellowship" - still a list.The pattern is the *prefix* `cam-` and its common subsequent meanings.The neuron is essentially recognizing the root "cam-" and its various semantic branches.Let's try to be more specific about the *types* of things it's finding."Camera, chamber, senate, social groups" - 5 words.This captures the core ideas.- **Camera**: device- **Chamber**: institution (Cámara de Comercio)- **Senate**: institution- **Social groups**: CamaraderíaLet's check if any single word can capture it. No.A phrase.Let's look again at the TOKENS_AFTER_MAX_ACTIVATING_TOKEN:- `de seguridad` (camera)- `ero` (camarero)- `adería` (camaradería)- `Senado` (already in

    np_acts-logits-general · gemini-2.5-flash-lite
    New Auto-Interp
    Top Features by Cosine Similarity
    Configuration
    google/gemma-scope-2-27b-it/transcoder_all/layer_11_width_262k_l0_small_affine
    Prompts (Dashboard)
    238,145 prompts, 512 tokens each
    Dataset (Dashboard)
    lmsys + oasst1
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    Negative Logits
     dvara
    0.67
     Jason
    0.66
     sash
    0.63
    ...");
    0.60
     VD
    0.59
     LHC
    0.58
     ISS
    0.57
     LANA
    0.57
     GND
    0.57
     velké
    0.57
    POSITIVE LOGITS
    $
    0.70
    )
    0.68
    reward
    0.65
    го
    0.61
    #
    0.61
    revenue
    0.60
    Auction
    0.60
    Cow
    0.59
    Soy
    0.58
    Rew
    0.58
    Activations Density 0.000%

    No Known Activations