Defining the effective impact mass of elbow and shoulder strikes in ice hockey
Bibliographic record
Abstract
Reconstruction of real-life events can be used to investigate the relationship between the mechanical parameters of the impact and concussion risk. Striking mass has typically been approximated as being the mass of the body part coming into contact with the head without accounting for the force applied by the striking athlete. Thus, the purpose of this study was to measure the effective impact mass of three common striking techniques in ice hockey. Fifteen participants were instructed to strike a suspended 50th percentile Hybrid III headform at least three times with their elbow or shoulder. Effective impact mass was calculated by measuring the change in velocity of the player and the headform. Mean effective impact mass for the extended elbow, tucked-in elbow, and shoulder check conditions were 4.8, 3.0, and 12.9 kg, respectively. Peak linear accelerations were lower than the values associated with concussion in American football which could be a reflection of the methodology used in this study as well as inherent differences between both sports.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".