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Record W1974043473 · doi:10.1080/09541440440000122

Allocating visual attention to grouped objects

2004· article· en· W1974043473 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

VenueThe European Journal of Cognitive Psychology · 2004
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyCognitive psychologyVisual attentionCognitive scienceCommunicationNeuroscienceCognition

Abstract

fetched live from OpenAlex

The purpose of the present study is to examine the allocation of visual attention to independent stimuli that are grouped together through a set of Gestalt principles. The basic display used in the experiments consisted of a 4 × 4 matrix of placeholders, made up of 12 circles and 4 squares. In Experiment 1, the squares were located adjacent to each other (i.e., perceptually grouped together), whereas in Experiment 2 the squares were located in nonadjacent locations (i.e., not perceptually grouped). Following a peripheral cue at a square placeholder, faster detection responses were found for targets appearing in the noncued square placeholders than in corresponding circle placeholders for Experiment 1. This pattern of results was not found in Experiment 2. Experiment 3 used an alternate display to rule out the possibility that the results of Experiment 1 were due to shape-based object priming. Experiment 4 extended the cue–target SOA to examine whether inhibition of return would spread through grouped objects—it did not. These findings provide new insights into the boundary conditions for what, exactly, constitutes an object.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.024
GPT teacher head0.319
Teacher spread0.295 · 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