A systematic video analysis of National Hockey League (NHL) concussions, part II: how concussions occur in the NHL
Bibliographic record
Abstract
BACKGROUND: Concussions in sports are a growing cause of concern, as these injuries can have debilitating short-term effects and little is known about the potential long-term consequences. This work aims to describe how concussions occur in the National Hockey League. METHODS: Case series of medically diagnosed concussions for regular season games over a 3.5-year period during the 2006-2010 seasons. Digital video records were coded and analysed using a standardised protocol. RESULTS: 88% (n=174/197) of concussions involved player-to-opponent contact. 16 diagnosed concussions were a result of fighting. Of the 158 concussions that involved player-to-opponent body contact, the most common mechanisms were direct contact to the head initiated by the shoulder 42% of the time (n=66/158), by the elbow 15% (n=24/158) and by gloves in 5% of cases (n=8/158). When the results of anatomical location are combined with initial contact, almost half of these events (n=74/158) were classified as direct contact to the lateral aspect of the head. CONCLUSIONS: The predominant mechanism of concussion was consistently characterised by player-to-opponent contact, typically directed to the head by the shoulder, elbow or gloves. Also, several important characteristics were apparent: (1) contact was often to the lateral aspect of the head; (2) the player who suffered a concussion was often not in possession of the puck and (3) no penalty was called on the play.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".