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Record W2052721690 · doi:10.1037/a0025050

Perception of temporal order is impaired during the time course of the attentional blink.

2011· article· en· W2052721690 on OpenAlexafffund
Thomas M. Spalek, Hayley E. P. Lagroix, Matthew Yanko, Vincent Di Lollo

Bibliographic record

VenueJournal of Experimental Psychology Human Perception & Performance · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsSimon Fraser University
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of Canada
KeywordsRapid serial visual presentationAttentional blinkPerceptionPsychologyCognitive psychologyVisual perceptionTime perceptionAudiologyNeuroscience

Abstract

fetched live from OpenAlex

Identification accuracy for the second of two target (T2) is impaired when presented shortly after the first (T1). Does this attentional blink (AB) also impair the perception of the order of presentation? In four experiments, three letter targets (T1, T2, T3) were inserted in a stream of digit distractors displayed in rapid serial visual presentation (RSVP), with T3 always presented directly after T2. The T1-T2 lag was varied to assess the perception of T2-T3 temporal order throughout the period of the AB. Factorial manipulation of the presence or absence of distractors before T1 and between T1 and T2 had similar effects on accuracy and on perception of temporal order. It is important to note that perception of temporal order suffered even when accuracy was unimpaired. This pattern of results is consistent with prior-entry theories of the perception of temporal order but not with episodic-integration theories. Simulations based on the Episodic Simultaneous Type, Serial Token (eSTST) model (Wyble, Bowman, & Nieuwenstein, 2009) provided excellent fits to the data except for the condition in which no distractors were presented in the RSVP stream.

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 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 score0.690
Threshold uncertainty score0.998

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.122
GPT teacher head0.392
Teacher spread0.270 · 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.

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

Citations22
Published2011
Admission routes2
Has abstractyes

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