Bibliographic record
Abstract
The current research utilizes lexical decision within an oddball ERP paradigm to study early lexical processing. Nineteen undergraduate students completed four blocks of the oddball lexical decision task (Nonword targets among Words, Word targets among Nonwords, Word targets among Pseudowords, and Pseudoword targets among Words). We observed a reliable P3 ERP component in conditions where the distinction between rare and frequent trials could be made solely based on lexical status (Words among Nonwords and Nonwords among Words). We saw a reliable P3 to rare words among frequent pseudowords, but no P3 was observed when participants were asked to detect pseudowords in the context of frequent word stimuli. We argue that this observed modulation of the P3 results is consistent with psycholinguistic literature that suggests that two criteria are available during lexical access when performing a lexicality judgement, a non-lexical criterion that relies on global activation at the word level and a lexical criterion that relies on activation of a lexical representation (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; Grainger & Jacobs, 1996).
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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 | 0.001 | 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) | 0.000 | 0.002 |
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".