Characteristics of potential concussive events in elite hurling: a video-analysis study
Bibliographic record
Abstract
BACKGROUND: High-impact sports such as hurling place participants at risk of sport-related concussion (SRC). AIMS: This study will evaluate the characteristics of potential concussive events (PCEs) that occur in elite male hurling to acquire an understanding of how they occur. METHODS: The authors recorded PCEs and their characteristics throughout two seasons of inter-county GAA competition using broadcast footage based on a previously validated protocol. RESULTS: A total of 183 PCEs were identified over 82 inter-county matches (2.23 per match; 59.5 per 1000 h of exposure). PCEs that occurred in the 4th quarter were significantly more likely to result in signs of SRC. Players most often intended to receive/control the sliotar (36.4%, n = 64) prior to PCEs. The most frequently observed mechanism was shoulder-to-head (20.2%, n = 37). Impacts to the lateral aspect of the head were 2.7 times more likely to result in visible signs than impacts to anteroposterior regions. CONCLUSIONS: Players appear to be at a higher risk of SRC later in the match or when receiving the sliotar. Strikes to the lateral aspect of the head and those involving the shoulder appear to produce severe events. These findings provide initial guidance for the development of targeted player protection strategies.
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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 | 0.002 | 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) | 0.002 | 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".