Bibliographic record
Abstract
OBJECTIVE: This article reviews the distribution and determinants of injuries reported in the pediatric ice hockey literature, and suggests potential injury prevention strategies and directions for further research. DATA SOURCES: Thirteen electronic databases, the ISI Web of Science, and 'grey literature' databases were searched using a combination of Medical Subject Headings and text words to identify potentially relevant articles. The bibliographies of selected studies were searched to identify additional articles. Studies were selected for review based on predetermined inclusion and exclusion criteria. MAIN RESULTS: A comparison between studies on this topic area was difficult due to the variability in research designs, definition of injury, study populations, and measurements used to assess injury. The majority of injuries were sustained during games compared with practices. The two most commonly reported injuries were sprains/strains and contusions. Players competing at the Minor hockey, High School, and Junior levels of competition sustained most of their injuries to the upper extremity, head, and lower extremity, respectively. The primary mechanism of injury was body checking, followed by stick and puck contact. The frequency of catastrophic eye injuries has been significantly reduced with the world-wide mandation of full facial protection for all Minor hockey players. CONCLUSIONS: Specific hockey-related injury risk factors are poorly delineated and rarely studied among pediatric ice hockey players leaving large gaps in the knowledge of appropriate prevention strategies. Risk management strategies should be focused at avoiding unnecessary foreseeable risk, and controlling the risks inherent to the sport. Suggestions for injury prevention and future research are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".