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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 OpenAlex
Jennifer A. Stolz, Robert S. McCann

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

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.995

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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