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Record W2026521474 · doi:10.1037//0096-1523.26.4.1320

Visual word recognition: Reattending to the role of spatial attention.

2000· article· en· W2026521474 on OpenAlexaff
Jennifer A. Stolz, Robert S. McCann

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2000
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCued speechLexical decision taskWord recognitionFixation (population genetics)Word (group theory)PsychologyCognitive psychologyPrime (order theory)Computer scienceSpeech recognitionCommunicationLinguisticsCognitionReading (process)NeuroscienceMathematics

Abstract

fetched live from OpenAlex

Three experiments examine whether spatial attention and visual word recognition processes operate independently or interactively in a spatially cued lexical-decision task. Participants responded to target strings that had been preceded first by a prime word at fixation and then by an abrupt onset cue either above or below fixation. Targets appeared either in the cued (i.e., valid) or uncued (i.e., invalid) location. The proportion of validly cued trials and the proportion of semantically related prime-target pairs were manipulated independently. It is concluded that spatial attention and visual word recognition processes are best seen as interactive. Spatial attention affects word recognition in 2 distinct ways: (a) it affects the uptake of orthographic information, possibly acting as "glue" to hold letters in their proper places in words, and (b) it (partly) determines whether or not activation from the semantic level feeds down to the lexical level during word recognition.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.317
Teacher spread0.297 · 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

Citations41
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Experimental Psychology Human Perception & PerformanceSame topicSpatial Cognition and NavigationFrench-language works237,207