Influence of phonological expectations during a phoneme deletion task: Evidence from event‐related brain potentials
Bibliographic record
Abstract
Several studies have identified a negativity [the phonological mismatch negativity (PMN)] preceding the N400 during auditory sentence comprehension. The present study investigated whether the PMN reflects a prelexical or lexical stage of spoken word recognition. Event-related brain potentials (ERPs) were recorded to investigate phonological processing independently from lexical/semantic influences during a task requiring metalinguistic analysis of speech stimuli. Participants were instructed to omit the initial phoneme from a word ("clap" without the/k/) after which they heard a correct (lap) or incorrect (cap, ap, nose) answer. The PMN (peaking at 270 ms) was largest to incorrect items and did not differentiate between items that shared the same rime and items that were phonologically unrelated to the correct choice. Further, the PMN did not differ between word (cap) and nonword (ap) choices. The P300 was largest to correct items but was also seen to choices that rhymed with the correct answer. It is concluded that the PMN serves as a neural marker for the analysis of acoustic input merging with prelexical phonemic expectations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".