Assessment of visuomotor function and dynamic balance control in youth hockey players with or without previous sport-related concussion over a 70-day period
Bibliographic record
Abstract
Introduction: Balance is now recognized as a clinical domain of sport-related concussion (SRC). Currently, the Return-to-Sport (RTS) protocol does not include assessment of dynamic stability or sensorimotor integration. Our recent findings have objectively identified youth athletes with from those without a previous SRC during a dynamic visuomotor balance task. Rationale: To determine whether a visuomotor dynamic balance task can identify differences between youth hockey players with and without previous SRC over time. Methods: Youth hockey players (n=31; age=12-17 years), who reported previous SRC (CONC= 13) and no history of SRC (CONT= 18) were tested twice over 70 days. Participants stood in single support on a Nintendo Wii Balance board sampled at 100Hz and performed three Go/No-Go tasks with each non-stance foot. Five FitLights were arranged on the floor anteriorly at +60°, +30°, and 0° and were used as the Go (GREEN)/No-Go (RED) stimulus. Balance control was assessed using RMS velocity of COP (vCOP) in anterior-posterior (A/P) and medial-lateral (M/L) planes. A repeated measures mixed-ANOVA was conducted to measure differences between groups. Results: The results indicate a significant group effect for both A/P vCOP (CONC= 8.18; CONT= 11.33, F= 18.97, p
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".