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Record W3152727437 · doi:10.1037/xge0001061

Re-examining attention capture at irrelevant (ignored?) locations.

2021· article· en· W3152727437 on OpenAlexaff
Seema Prasad, Ramesh Kumar Mishra, Raymond M. Klein

Bibliographic record

VenueJournal of Experimental Psychology General · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyTask (project management)Cognitive psychologyPsycINFOCued speechMEDLINE

Abstract

fetched live from OpenAlex

In 2018, Ruthruff and Gaspelin used a modified spatial cuing paradigm in which targets were presented at two locations while abrupt-onset cues could be presented at four locations. They found that performance following cues presented at irrelevant locations was no worse than following no cue or following a centrally presented cue. They concluded, as conveyed by the title of their article (Immunity to Attentional Capture at Ignored Locations) that a spatial attentional control setting had eliminated capture of attention. This conclusion was reached by comparing response time to targets on cue-absent versus irrelevant cues condition. We administered the exact same task in Experiment 1 and observed that responses on irrelevant trials were faster compared with cue absent trials providing support for the "immunity to attention capture claim" made by Ruthruff and Gaspelin (2018). However, cue absent trials may not be the most appropriate baseline condition as they lack the alerting benefit provided by cue-present trials. Thus, equivalent response times (RTs) on trials with absent cues and irrelevant cues observed in Ruthruff and Gaspelin (2018) could have been due to the lack of this alerting benefit. We tested this in Experiment 2 by additionally including a warning beep on every trial as an alerting signal. With this methodological change, we observed that responses were slower on irrelevant trials compared with the cue absent trials suggesting interference from cues at irrelevant locations. This study underscores the importance of using the appropriate baseline while testing attention capture. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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 score0.018
Threshold uncertainty score0.691

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)0.0000.000

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 head0.182
GPT teacher head0.431
Teacher spread0.249 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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