Detecting Opsoclonus Myoclonus Ataxia Syndrome (OMAS): Associations of Eye Tracking Metrics with Cognitive Outcomes
Bibliographic record
Abstract
This cross-sectional study compares free-viewing (FV) eye tracking metrics between children with Opsoclonus-myoclonus-ataxia syndrome (OMAS) and healthy age/sex-matched controls (HC) and investigates correlations of FV metrics with cognitive metrics. Participants included OMAS-diagnosed youth (n=11) and HC (n=15), who completed a FV eye tracking task and cognitive testing (NIH Toolbox). We quantified mean saccade rate (MSR) (saccades/s) and mean fixation duration (MFD) (milliseconds) for clip-aligned analyses. The OMAS group exhibited suppressed MSR (p=0.003, d=1.026) and longer MFD (p=0.043, d=1.045) compared to HC. MSR positively correlated with Dimensional Change Card Sort (DCCS) Task (r=0.572, p=0.011) and List Sorting Working Memory (LSWM) Test scores (r=0.575, p=0.001). MFD negatively correlated with DCCS Task (r=-0.687, p=0.001) and LSWM Test scores (r=-0.555, p=0.014). Children with OMAS demonstrated suppressed saccade rates and longer fixations across FV clip-changes: these correlated with lower scores in set-shifting and working memory tasks, indicating these FV metrics may reveal specific cognitive abnormalities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".