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Record W2072518154 · doi:10.1080/01690965.2011.603932

Does phonology play a role when skilled readers read high-frequency words? Evidence from ERPs

2011· article· en· W2072518154 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLanguage and Cognitive Processes · 2011
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsWestern University
Fundersnot available
KeywordsHomophonePhonologyN400SpellingReading (process)OrthographyPsychologyWord (group theory)LinguisticsPhoneticsPortlanditeWord lists by frequencyCognitive psychologyEvent-related potentialComputer scienceCognitionNatural language processingNeuroscienceHistory

Abstract

fetched live from OpenAlex

We used event-related brain potentials to clarify the role of phonology in activating the meanings of high-frequency words during skilled silent reading. Target homophones (meet) in sentences such as The students arranged to meet in the library to study were replaced on some trials by either a high-frequency homophone mate (meat) or a spelling control word (mean). Differences between homophone errors and spelling controls were observed, both in the N400 component and in earlier time windows, suggesting that phonology continues to play a role in activating word meanings even for highly practiced words. A manipulation of the frequency of the correct target word provided evidence concerning the nature of the processing involved.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.020
GPT teacher head0.282
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it