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Record W2035351037 · doi:10.1249/jsr.0b013e3181b84a09

Injuries and Medical Issues in Synchronized Olympic Sports

2009· review· en· W2035351037 on OpenAlexaff
Margo Mountjoy

Bibliographic record

VenueCurrent Sports Medicine Reports · 2009
Typereview
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAthletesFemale athlete triadSports injurySports medicineSynchronization (alternating current)MedicineInjury preventionPoison controlEntertainmentVariety (cybernetics)Suicide preventionApplied psychologyPhysical therapyPhysical medicine and rehabilitationPsychologyMedical emergencyComputer scienceChannel (broadcasting)

Abstract

fetched live from OpenAlex

Spectators of the Olympic Games can enjoy a wide variety of sports, including strength, team, timed, endurance, and artistic sports. In the Olympic program, there are two synchronized events: synchronized diving and synchronized swimming. The precision of the synchronization of the athlete's movements and skills is an added feature of entertainment. Synchronized athletes have additional training requirements to perfect the synchronization of their skills. The physical demands on the athlete from the repetition of training required for the perfection of synchronization result in injuries unique to these sports. Although both traumatic and overuse injuries occur, overuse injuries are more common. As these disciplines are artistic, judged sports, these athletes also are susceptible to eating disorders and the female athlete triad. This article reviews the training regimen of these athletes and outlines the injuries and health concerns that are common in the synchronized sports.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.400
Teacher spread0.369 · 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 designSystematic review
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

Citations37
Published2009
Admission routes1
Has abstractyes

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