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Record W2135192317 · doi:10.1080/02643290600588095

Inhibition of return: Twenty years after

2006· article· en· W2135192317 on OpenAlexaff
Juan Lupiáñez, Raymond M. Klein, Paolo Bartolomeo

Bibliographic record

VenueCognitive Neuropsychology · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInhibition of returnPsychologyStimulus (psychology)NeuropsychologyCognitive psychologyCognitionPhenomenonNeuroscienceDevelopmental psychologyVisual attentionEpistemology

Abstract

fetched live from OpenAlex

When responding to a suddenly appearing stimulus, we are slower and/or less accurate when the stimulus occurs at the same location of a previous event than when it appears in a new location. This phenomenon, often referred to as inhibition of return (IOR), has fostered a huge amount of research in the last 20 years. In this selective review, which introduces a Special Issue of Cognitive Neuropsychology dedicated to IOR, we discuss some of the methods used for eliciting IOR and its boundary conditions. We also address its debated relationships with orienting of attention, succinctly review findings of altered IOR in normal elderly and neuropsychiatric patients, and present results concerning its possible neural bases. We conclude with an outline of the papers collected in this issue, which offer a more in-depth treatment of behavioural, neural, and theoretical issues related to IOR.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.070
GPT teacher head0.349
Teacher spread0.279 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations178
Published2006
Admission routes1
Has abstractyes

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