EYE-SYNC Saccade Outcomes and Health/Demographic Factors in CFL Athletes
Bibliographic record
Abstract
The purpose of the present study was to examine the relationship between demographic and health factors, and oculomotor functioning during baseline testing in professional athletes. Four hundred twenty-eight male athletes consented and participated in the baseline concussion assessments of the Canadian Football League (CFL). Athletes ranged from 21 to 40 years of age (M =26.44, SD =2.873), and reported a history of 0, 1, or 2+ sport-related concussions (SRCs). All athlete participants completed the Head Check questions of demographics and medical history, and the EYE-SYNC saccade test to explore how the presence of a history of concussions, Attention-Deficit/Hyperactivity Disorder (ADHD), Learning Disability (LD), age, and post-exertion influenced baseline measures of oculomotor functioning using the EYE-SYNC saccade outcomes of accuracy and precision. Correlations revealed no significant relationships between combined vertical and horizontal saccade outcomes (LeftAccuracyXY, LeftPrecisionXY, RightAccuracyXY, RightPrecisionXY) and the demographic/health variables (p > .05). Independent t-tests indicated no significant differences in mean saccade performance between athletes with and without ADHD and/or LD (p > .05). Furthermore, three-way multiple analysis of variance (MANOVA) run with age group (21-25, 26-30, 31-40) and concussion group (0, 1, 2+) revealed no main effects of age, F(8, 844) = .914, p = .504, Wilks’ = .983, partial η2 = .0) or history of concussion, F(8, 510) = .856, p = .554, Wilks’ = .974, partial η2 = .013). A one-way repeated measures analysis of variance (MANOVA) revealed no significant differences from pre- to post-exertion assessments, F(4, 56) = .411, p = .800, Wilks’ = .971. The oculomotor functioning of CFL athletes at baseline, measured using the EYE-SYNC saccade task, does not appear to be influenced by a history of concussion, ADHD, LD, age, or physical exertion. This information may help professionals with their clinical decision-making regarding the diagnosis of SRCs, and return-to-play.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".