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Record W2013938384 · doi:10.1037/1076-898x.11.1.3

Object-Based Attention and Cognitive Tunneling.

2005· article· en· W2013938384 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Experimental Psychology Applied · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsObject (grammar)CognitionPerceptionCognitive psychologyPsychologyComputer scienceQuantum tunnellingVisual perceptionHuman–computer interactionComputer visionArtificial intelligenceNeurosciencePhysics

Abstract

fetched live from OpenAlex

Simulator-based research has shown that pilots cognitively tunnel their attention on head-up displays (HUDs). Cognitive tunneling has been linked to object-based visual attention on the assumption that HUD symbology is perceptually grouped into an object that is perceived and attended separately from the external scene. The present research strengthens the link between cognitive tunneling and object-based attention by showing that (a) elements of a visual display that share a common fate are grouped into a perceptual object and that this grouping is sufficient to sustain object-based attention, (b) object-based attention and thereby cognitive tunneling is affected by strategic focusing of attention, and (c) object-based attention is primarily inhibitory in nature.

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.

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 score0.011
Threshold uncertainty score0.540

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 head0.103
GPT teacher head0.415
Teacher spread0.312 · 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