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Record W7154567156 · doi:10.48448/k4dr-c749

The Role of Eye Movement Consistency in Aging-Related Decline in Face Recognition

2025· other· W7154567156 on OpenAlexaff
Cognitive Science Society 2025, Gail Eskes, Janet Hsiao, Lai Ling Hui, Esther Yuet Ying Lau, WS Lo, Yueyuan Zheng

Bibliographic record

VenueUnderline Science Inc. · 2025
Typeother
Language
Field
Topic
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEye movementConsistency (knowledge bases)Facial recognition systemFace (sociological concept)Gaze-contingency paradigmContrast (vision)

Abstract

fetched live from OpenAlex

Face recognition is shown to involve a prolonged developmental process where one gradually develops a more consistent but idiosyncratic visual routine with increasing age. In contrast to this developmental trend, here we found that aging was associated with decreased eye movement consistency during face recognition, which in turn contributed to declined face recognition performance. Although aging was not associated with changes in eye movement pattern, a less eyes-focused eye movement pattern predicted poorer face recognition performance together with lower eye movement consistency and age in older adults, suggesting that the idiosyncratic eye movement patterns acquired during early adulthood continue to account for their face recognition performance. Their decreased eye movement consistency was associated with declines in selective attention and inhibition control, suggesting difficulties in the execution of the learned visual routines. These findings have important implications for ways to facilitate older adults’ face recognition to promote healthy aging.

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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.841
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.012
Science and technology studies0.0010.007
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.014
GPT teacher head0.288
Teacher spread0.273 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

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