mentions of files and code assets—filenames with extensions, paths, and environment/config variables—within programming or technical snippets.

self-referential disclaimers where the assistant identifies itself as an AI language model and explains limitations or refusal to comply.

instructions that set up role‑play/jailbreak personas and task constraints (e.g., unfiltered “AIM” scenarios), as well as numbered requests for alternative expressions or synonyms.

sentences or clauses containing first-person pronouns (especially "I" / "My") — i.e., author statements about their actions or issues.

The neuron mainly detects substrings of proper nouns and other uncommon named-entity-like tokens (fragmented names and rare/foreign words).

the neuron detects numeric tokens and numeric/measurement-related elements (numbers, dates, percentages, units).

tokens that are database schema elements and structural identifiers (table names, column names, headers, and related DB/code identifiers).

tokens marking the assistant role or the start of an assistant response.

finds modal and auxiliary verbs (words expressing ability, necessity, or possibility such as can, must, will, be).

Tokens that are part of the assistant's generated output (i.e., the assistant role / response text).

Tokens that mark the assistant/response header and related system metadata (i.e., assistant role and start/end header tokens).

The neuron detects code-like syntax tokens and programming-language keywords (i.e., places in the text that look like source code).

This neuron detects instruction/request verbs (imperative task words like "create", "write", "design", "teach", "make") that signal a user asking the model to perform a task.

tokens representing numeric values, monetary amounts, quantities, and time units (numbers, $/NRE, thousands, weeks, etc.).

The neuron detects named entities—proper nouns like people, organizations, places, dates and other capitalized titles.

The neuron detects dismissive or minimizing language about mental-health problems that urges simplistic self-control instead of acknowledging real distress.

mentions of mobile app (or software) development requests, specifications, and price/estimate or project-planning language.

Detects short impersonal third-person pronouns used as sentence subjects (the neutral "it"-type subject).

This neuron detects mentions of central characters (proper names) and strong narrative actions—tokens that mark who is acting in the story.

The neuron detects short name-like or handle-like tokens (author names, usernames, or blog/site handles).