MétaCan
Menu
Back to cohort
Record W2006657755 · doi:10.1080/17470218.2012.762798

Optimal and Preferred Eye Landing Positions in Objects and Scenes

2013· article· en· W2006657755 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

VenueQuarterly Journal of Experimental Psychology · 2013
Typearticle
Languageen
FieldComputer Science
TopicVisual Attention and Saliency Detection
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer visionEye movementPsychologyComputer scienceCommunicationArtificial intelligenceOptometryMedicine

Abstract

fetched live from OpenAlex

Viewing position effects are commonly observed in reading, but they have only rarely been investigated in object perception or in the realistic context of a natural scene. In two experiments, we explored where people fixate within photorealistic objects and the effects of this landing position on recognition and subsequent eye movements. The results demonstrate an optimal viewing position-objects are processed more quickly when fixation is in the centre of the object. Viewers also prefer to saccade to the centre of objects within a natural scene, even when making a large saccade. A central landing position is associated with an increased likelihood of making a refixation, a result that differs from previous reports and suggests that multiple fixations within objects, within scenes, occur for a range of reasons. These results suggest that eye movements within scenes are systematic and are made with reference to an early parsing of the scene into constituent objects.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score0.269

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 communication0.0000.001
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 head0.020
GPT teacher head0.339
Teacher spread0.319 · 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