Altered inter-segmental coordination in athletes with a history of concussion
Bibliographic record
Abstract
Concussion-recovered athletes have a higher risk of injury following return to sport. This study investigated the effect of history of concussion on the pattern and variability of inter-segmental coordination in athletes during squat jumps and timed squat and hinge tasks. A human pose estimation algorithm was applied to videos of 111 athletes (72 with no history of concussion (NOHX), 9 within 1 year of concussion (CONC1), 30 more than one-year post-concussion (CONC2) performing a series of movement tasks. Continuous relative phase metrics, calculated from phase angles of two contiguous segments, were used to evaluate inter-segmental coordination. Linear models were used to evaluate the causal effect of concussion group on hip, knee, and ankle coordination and repetition duration for each task. CONC1 affected repetition duration and knee and hip coordination and variability, while CONC2 influenced knee coordination. The findings suggest that concussion may have long-term persisting effects on lower-limb inter-segmental coordination in athletes.
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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 | 0.000 | 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) | 0.002 | 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".