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Record W2522350522 · doi:10.1037/xlm0000330

Attentional capture by deviant sounds: A noncontingent form of auditory distraction?

2016· article· en· W2522350522 on OpenAlexafffund
François Vachon, Katherine Labonté, John E. Marsh

Bibliographic record

VenueJournal of Experimental Psychology Learning Memory and Cognition · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDistractionPsychologyCognitive psychologyStimulus (psychology)CognitionMismatch negativityTask (project management)Electroencephalography

Abstract

fetched live from OpenAlex

The occurrence of an unexpected, infrequent sound in an otherwise homogeneous auditory background tends to disrupt the ongoing cognitive task. This "deviation effect" is typically explained in terms of attentional capture whereby the deviant sound draws attention away from the focal activity, regardless of the nature of this activity. Yet, there is theoretical and empirical evidence suggesting that the attention-capture mechanism underlying this form of distraction could rather be triggered in a task-contingent fashion. The present study aimed at determining whether the auditory deviation effect reflects the action of either a stimulus-driven or a task-contingent orienting mechanism. To do so, we conducted a systematic investigation whereby the impact of verbal deviants-a letter embedded in the repetition of another letter-and spatial deviants-a sound presented contralaterally to the other sounds-on verbal and spatial short-term memory (STM) was assessed. This study established that both verbal and spatial deviants can hinder both verbal and spatial order-reconstruction (Experiment 1) and missing-item tasks (Experiment 2). Such results demonstrate that the deviation effect reflects a general form of auditory distraction as interference took place both within and across domains and regardless of the processes engaged in the focal task. (PsycINFO Database Record

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 score0.028
Threshold uncertainty score0.283

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 head0.029
GPT teacher head0.326
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 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

Citations74
Published2016
Admission routes2
Has abstractyes

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