MétaCan
Menu
Back to cohort
Record W4393132487 · doi:10.16910/jemr.17.3.2

Dynamics of eye dominance behavior in virtual reality

2024· article· en· W4393132487 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 Eye Movement Research · 2024
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsUniversity of Toronto
FundersEuropean Commission
KeywordsVirtual realityComputer scienceOcular dominanceEye movementDominance (genetics)Flexibility (engineering)Human–computer interactionArtificial intelligenceComputer visionReplicateContext (archaeology)Eye trackingCognitive psychologyPsychologyMathematicsGeography

Abstract

fetched live from OpenAlex

Prior research has shown that sighting eye dominance is a dynamic behavior and dependent on horizontal viewing angle. Virtual reality (VR) offers high flexibility and control for studying eye movement and human behavior, yet eye dominance has not been given significant attention within this domain. In this work, we replicate Khan and Crawford's (2001) original study in VR to confirm their findings within this specific context. Additionally, this study extends its scope to study alignment with objects presented at greater depth in the visual field. Our results align with previous results, remaining consistent when targets are presented at greater distances in the virtual scene. Using greater target distances presents opportunities to investigate alignment with objects at varying depths, providing greater flexibility for the design of methods that infer eye dominance from interaction in VR.

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)0.004
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: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.405
Teacher spread0.348 · 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