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Record W2145330809 · doi:10.1136/bjsports-2013-092234

A systematic video analysis of National Hockey League (NHL) concussions, part I: who, when, where and what?

2013· article· en· W2145330809 on OpenAlexafffund
Michael G. Hutchison, Paul Comper, Willem Meeuwisse, Ruben J. Echemendía

Bibliographic record

VenueBritish Journal of Sports Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of TorontoUniversity of CalgarySt. Michael's Hospital
FundersUniversity of TorontoOntario Neurotrauma Foundation
KeywordsLeagueIce hockeyConcussionPhysical medicine and rehabilitationMedicinePhysical therapyPsychologyInjury preventionApplied psychologyPoison controlEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Although there is a growing understanding of the consequences of concussions in hockey, very little is known about the precipitating factors associated with this type of injury. AIM: To describe player characteristics and situational factors associated with concussions in the National Hockey League (NHL). METHODS: Case series of medically diagnosed concussions for regular season games over a 3.5-year period during the 2006-2010 seasons using an inclusive cohort of professional hockey players. Digital video records were coded and analysed using the Heads Up Checklist. RESULTS: Of 197 medically diagnosed concussions, 88% involved contact with an opponent. Forwards accounted for more concussions than expected compared with on-ice proportional representation (95% CI 60 to 73; p=0.04). Significantly more concussions occurred in the first period (47%) compared with the second and third periods (p=0.047), with the majority of concussions occurring in the defensive zone (45%). Approximately 47% of the concussions occurred in open ice, 53% occurred in the perimeter. Finally, 37% of the concussions involved injured players' heads contacting the boards or glass. CONCLUSIONS: This study describes several specific factors associated with concussions in the NHL, including period of the game, player position, body size, and specific locations on the ice and particular situations based on a player's position.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.029
GPT teacher head0.306
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations123
Published2013
Admission routes2
Has abstractyes

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