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Record W2553358069 · doi:10.2147/oajsm.s118595

Evaluation, management and prevention of lower extremity youth ice hockey injuries

2016· review· en· W2553358069 on OpenAlexaboutno aff
Charles A. Popkin, Brian Schulz, Caroline Park, Thomas S. Bottiglieri, T. Sean Lynch

Bibliographic record

VenueOpen Access Journal of Sports Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsnot available
Fundersnot available
KeywordsIce hockeyInjury preventionSuicide preventionOccupational safety and healthPoison controlMedicineHuman factors and ergonomicsPhysical therapyMedical emergencyForensic engineeringPhysical medicine and rehabilitationEngineeringPathology

Abstract

fetched live from OpenAlex

Ice hockey is a fast-paced sport played by increasing numbers of children and adolescents in North America and around the world. Requiring a unique blend of skill, finesse, power and teamwork, ice hockey can become a lifelong recreational activity. Despite the rising popularity of the sport, there is ongoing concern about the high frequency of musculoskeletal injury associated with participation in ice hockey. Injury rates in ice hockey are among the highest in all competitive sports. Numerous research studies have been implemented to better understand the risks of injury. As a result, rule changes were adopted by the USA Hockey and Hockey Canada to raise the minimum age at which body checking is permitted to 13-14 years (Bantam level) from 11-12 years (Pee Wee). Continuing the education of coaches, parents and players on rules of safe play, and emphasizing the standards for proper equipment use are other strategies being implemented to make the game safer to play. The objective of this article was to review the evaluation, management and prevention of common lower extremity youth hockey injuries.

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)0.007
metaresearch head score (Gemma)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.131
GPT teacher head0.474
Teacher spread0.343 · 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 designOther design
Domainnot available
GenreReview

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

Citations26
Published2016
Admission routes1
Has abstractyes

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