Effect of sub-concussive impacts sustained throughout a contact-sport season on quiet stance centre of pressure
Bibliographic record
Abstract
Objective To examine how sub-concussive head trauma throughout a contact-sport season affects quiet stance centre of pressure (COP) sway Design Prospective cohort Setting Laboratory Participants: Twenty-four elite male football players (age range 18–22) were recruited for the study Intervention Quiet stance data was collected at the start and at the end of the competitive season. One-minute trials were performed with eyes-open and eyes-closed on a force plate (NDI True Impulse) with feet hip-width apart and hands-on-hips. Biomechanical head-impact exposure was indexed using the xPatch (X2 Biosystems) Outcome measures COP measures: Anterior/posterior (AP) and medial/lateral (ML) root-mean-square displacement (RMSd) and mean velocity. Biomechanical head-impact data: For hits above 20g, peak linear acceleration (PLA), and peak rotational acceleration (PRAwere estimated across the competitive season. Independent variables included time (2) and condition (2) Results RM-ANOVA reveal an effect of condition (eyes-open vs eyes-closed) in AP-RMSd (p=0.035, 95% CI: 0.006, 0.159), ML-RMSd (p<0.0001, CI: 0.083, 0.250), and ML mean velocity (p<0.0001, 95% CI: 0.111, 0.308). However, despite exposure to a cumulative 8147.2±6215.5 g in linear acceleration and 34.5 x 106 ± 59.0x106 rad/s2 in rotational acceleration, there were no significant differences between conditions for COP measures at post-season Conclusions In contrast to the prolonged COP alterations observed following acute concussions, there were no discernable effects of sub-concussive trauma on COP sway during quiet stance in the same population. This is an important finding as it reveals that participation in contract-sport does not impair quiet stance balance Competing interests None.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".