MétaCan
Menu
Back to cohort
Record W4408212485 · doi:10.1101/2025.03.02.641038

Steering in the presence of a gaze-contingent occlusion over a quarter of the visual field

2025· preprint· en· W4408212485 on OpenAlexaboutno aff
Arianna P. Giguere, Matthew R. Cavanaugh, Krystel R. Huxlin, Duje Tadin, Brett R. Fajen, Gabriel J. Diaz

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsnot available
Fundersnot available
KeywordsGazeQuarter (Canadian coin)Visual fieldField (mathematics)PsychologyComputer visionOptometryComputer scienceNeuroscienceMedicineHistoryMathematicsArchaeology

Abstract

fetched live from OpenAlex

Why do some cortically blind (CB) drivers who are missing vision from a quadrant or hemifield have trouble maintaining a central lane position, while others do not? A recent driving study in virtual reality showed that most patients with right-sided visual field deficits (right CB) perform similarly to controls, while most of those with left CB demonstrated a unique pattern of steering biases (Giguere et al., 2025). In this study, we tested the hypothesis that these biases could result from loss of visual information falling on the blind field. The steering and gaze behavior of 24 subjects with normal vision (mean age: 19.8 years, SD: 1.44) were recorded in a virtual reality steering task while gaze-contingent occluding masks were imposed on a quadrant of their visual field. The central five degrees of vision were spared to mimic the sparing present in most CB patients. Turn direction (left/right), turn radius (two non-constant radii), and occlusion quadrant (one of four quadrants or no occlusion) were randomized between trials. We found that the pattern of steering biases observed in CB drivers were not replicated when visually-healthy drivers were subjected to gaze-contingent masks, and we conclude that it may be a mistake to characterize the effects of cortical blindness on steering behavior as consistent with a simple omission of visual information. This insight has the potential to guide future research on CB adaptation to their visual impairments and possible interventions to improve their steering performance.

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 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)0.001
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 score0.421
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.002
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 head0.009
GPT teacher head0.235
Teacher spread0.226 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicGaze Tracking and Assistive TechnologyFrench-language works237,207