Factors influencing visor use among players in the National Hockey League (NHL)
Bibliographic record
Abstract
Abstract: Eye, orbital, and facial injuries are significant risks to National Hockey League (NHL) players, and can be mitigated by the use of a partial visor – currently optional for all non-rookie players. The goal of the current study was to determine the overall use of visors among non-rookie NHL players in the 2013–2014 season and assess factors influencing their uptake. This was an observational, cross-sectional study using active NHL rosters and demo-graphic information obtained from the official NHL website. Visor use was determined based on in-game video or images at two different time points in the 2013–2014 season. The use of visors during the 2013–2014 season was 75.2 % among non-rookie players. When rookies were included, the overall use of visors was 77.8%. Compared to Canadian-born players, European players were significantly more likely to choose to wear a visor (odds ratio [OR] 3.48, 95% confidence interval [CI] 1.96–6.17). Players in the younger age-groups, particularly those younger
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".