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Record W2137771526 · doi:10.1111/1467-9280.01418

New Objects, Not New Features, Trigger the Attentional Blink

2003· article· en· W2137771526 on OpenAlexaff
Jane E. Raymond

Bibliographic record

VenuePsychological Science · 2003
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity College of the North
Fundersnot available
KeywordsRapid serial visual presentationAttentional blinkObject (grammar)PsychologyFeature (linguistics)PerceptionCognitive psychologyCognitive neuroscience of visual object recognitionCommunicationComputer visionArtificial intelligenceComputer scienceNeuroscienceLinguistics

Abstract

fetched live from OpenAlex

When two different targets must be selected from a rapid serial visual presentation (RSVP) of images, perception of the second target will be markedly reduced if it is presented within about a half second of the first. Known as the attentional blink (AB), this effect reflects temporal limitations in attentional processes enabling awareness of image representations. I tested whether these limitations occur at an object or feature level of processing by presenting (in RSVP) multiple images of the same (old) object depicted in different orientations. Targets were defined by new features added either to this or to a new object. When the first target feature appeared on the old object, no AB effects were found even when the second target was a new object. When a new object carried the first target feature, an AB effect was found even when the second target feature appeared on the same "new" object. The AB appears to reflect limitations in the creation of new object representations, rather than temporal limitations of awareness per se.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.133
GPT teacher head0.406
Teacher spread0.273 · 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 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

Citations58
Published2003
Admission routes1
Has abstractyes

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