Multiple P3 evidence of a two-stage process in word gender decision
Bibliographic record
Abstract
All French nouns must be assigned to one of two grammatical genders: masculine or feminine. Participants used either the superordinate labels masculin/féminin or the singular indefinite articles un/une to classify French target nouns. Reaction time to the labels masculin/féminin was about 200 ms longer than to the un/une labels. When the indefinite articles were used, a single P3 peak of the event-related potential was elicited. When superordinate labels were used, a double-peaked positivity was observed. The latency of the initial P3 in the masculin/féminin trials was not significantly different from that in the un/une trials. The second positive wave peaked approximately 300 ms following the first. An explanation consistent with these data is that subjects used a two-stage process to classify the nouns appearing with superordinate labels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".