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Record W2070299786 · doi:10.1249/jsr.0b013e3181b7f1f4

Field Hockey Injuries

2009· review· en· W2070299786 on OpenAlexaff
Karen Murtaugh

Bibliographic record

VenueCurrent Sports Medicine Reports · 2009
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsFowler Kennedy Sport Medicine Clinic
Fundersnot available
KeywordsMedicineField hockeyInjury preventionPoison controlMouthguardAnkleOccupational safety and healthHuman factors and ergonomicsPhysical therapyAnkle sprainPhysical medicine and rehabilitationMedical emergencyFootballSurgery

Abstract

fetched live from OpenAlex

Field hockey is a popular sport that is played throughout the world. Most of the literature on the sport has focused on describing injury patterns. This research reveals that most injuries are minor and that the most common injury is an ankle sprain. Studies also suggest that men have a higher rate of injury and that they experience severe injuries more often than women. These severe injuries include trauma to the head, face, and upper limb and usually are the result of contact with the stick or ball. Consequently, many authors suggest that all players wear face and hand protection. Current International Field Hockey Federation rules recommend minimal protective equipment (e.g., mouthguard, shin, and ankle guards), and surveys indicate that many players do not wear mouthguards regularly. Looking into the future, research should focus on developing and evaluating effective strategies for injury prevention.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.004

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 head0.053
GPT teacher head0.416
Teacher spread0.363 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations40
Published2009
Admission routes1
Has abstractyes

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