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Record W2120988704 · doi:10.1037/a0018741

Visual word recognition: Evidence for global and local control over semantic feedback.

2010· article· en· W2120988704 on OpenAlexafffund
Serje Robidoux, Jennifer A. Stolz, Derek Besner

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2010
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAssociative propertyStimulus (psychology)Computer scienceNatural language processingArtificial intelligenceCognitive psychologySemantic memorySpeech recognitionPsychologyCognitionNeuroscienceMathematics

Abstract

fetched live from OpenAlex

Two lexical decision experiments examined the joint effects of stimulus quality, semantic context, and cue-target associative strength when all factors were intermixed in a block of trials. Both experiments found a three-way interaction. Semantic context and stimulus quality interacted when associative strength between cue-target pairs was strong, and the interaction was eliminated when the strength was weak. These results support a role for a local mechanism that relies on trial specific information, in addition to a mechanism that makes use of global information available across a block of trials. The absence of an interaction between the joint effects of semantic context and stimulus quality is attributed to blocking the feedback from the semantic system to the orthographic system, functionally separating the orthographic and semantic modules.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.423
Teacher spread0.371 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2010
Admission routes2
Has abstractyes

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