- Mentions "Mint" (a budgeting app).- Mentions code snippets with curly braces and semicolons.- Mentions "Airport" in context of international travel.- Mentions "Arrival/Departure".Let's re-evaluate based on the MOST RECENT prompt instructions."Your response should be a concise explanation (3 to 20 words) that captures what the neuron detects or predicts by finding patterns in lists.""Look at the lists and find a pattern that helps you explain the behavior of the neuron.""The explanation could be about tokens following or preceding certain tokens.""The explanation could be about words starting with a sequence.""Avoid simply listing all the tokens. Instead, try to find patterns."**MAX_ACTIVATING_TOKENS:**- uit- out- uit- International- out- out- out- International- International- out**TOKENS_AFTER_MAX_ACTIVATING_TOKEN:**- .- .- Airport- ;- ;- ;- Airport- Airport- ;Let's combine the observations:1. **'uit' / 'out' followed by '.'**: This appears in contexts like code formatting (`"});`, `.";`, `";`). The `uit` and `out` might be part of larger words or tokens that end up being interpreted as parts of code or structured text.2. **'International' followed by 'Airport'**: This is evident from "Incheon International Airport".The `TOP_POSITIVE_LOGITS` list is quite noisy, containing non-English characters (`ج`, `០០`), Spanish (`aría`, `corresponde`), French (`construire`), punctuation (`.";`, `";`, `"});`), and `fte` which could be part of code. This suggests the neuron might be sensitive to structured text, potentially code or formal documents, where specific phrases like "International Airport" appear alongside code-like markers