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Record W2066437310 · doi:10.1037/0096-1523.33.2.348

Separate mechanisms recruited by exogenous and endogenous spatial cues: Evidence from a spatial Stroop paradigm.

2007· article· en· W2066437310 on OpenAlexaff
María Jesús Funes, Juan Lupiáñez, Bruce Milliken

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2007
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsMcMaster University
Fundersnot available
KeywordsStroop effectPsychologyCognitive psychologyFixation pointFixation (population genetics)NeuroscienceCognitionPopulationComputer scienceMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

The present experiments tested whether endogenous and exogenous cues produce separate effects on target processing. In Experiment 1, participants discriminated whether an arrow presented left or right of fixation pointed to the left or right. For 1 group, the arrow was preceded by a peripheral noninformative cue. For the other group, the arrow was preceded by a central, symbolic, informative cue. The 2 types of cues modulated the spatial Stroop effect in opposite ways, with endogenous cues producing larger spatial Stroop effects for valid trials and exogenous cues producing smaller spatial Stroop effects for valid trials. In Experiments 2A and 2B, the influence of peripheral noninformative and peripheral informative cues on the spatial Stroop effect was directly compared. The spatial Stroop effect was smaller for valid than for invalid trials for both types of cues. These results point to a distinction between the influence of central and peripheral attentional cues on performance and are not consistent with a unitary view of endogenous and exogenous attention.

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)0.004
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.090
GPT teacher head0.355
Teacher spread0.264 · 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

Citations86
Published2007
Admission routes1
Has abstractyes

Explore more

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