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Record W2023375503 · doi:10.1037/0096-1523.30.6.1064

Interactive Activation in Visual Word Recognition: Constraints Imposed by the Joint Effects of Spatial Attention and Semantics.

2004· article· en· W2023375503 on OpenAlexaff
Jennifer A. Stolz, Biljana Stevanovski

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2004
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStimulus (psychology)PsychologyPriming (agriculture)Cognitive psychologyWord recognitionSemantics (computer science)Cued speechSpeech recognitionComputer scienceLinguisticsReading (process)

Abstract

fetched live from OpenAlex

Two lexical-decision experiments investigated the effects of semantic priming and stimulus intensity when target location varied and was cued by an abrupt onset. In Experiment 1, the spatial cue was a good predictor of target location, and in Experiment 2 it was not. The results indicate that word recognition processes were postponed until spatial attention was focused on the target and that whether attention further affected word recognition depended on cue validity. The joint effects of cue validity and priming interacted when cue validity was high but were additive when cue validity was low. The joint effects of stimulus intensity and semantic priming also varied according to cue validity (i.e., interactive when high and additive when low). The results are discussed in terms of their implications for visual word recognition, the distinction between exogenous and endogenous spatial attention, and how attention is affected by visual word recognition processes.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

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

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 head0.079
GPT teacher head0.398
Teacher spread0.319 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations24
Published2004
Admission routes1
Has abstractyes

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