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Record W2146101229 · doi:10.1136/bjsm.2010.076992

Sports injuries and illnesses during the Winter Olympic Games 2010

2010· article· en· W2146101229 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBritish Journal of Sports Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of Calgary
FundersUniversity of British ColumbiaInternational Olympic Committee
KeywordsAthletesMedicinePhysical therapyIce hockeyConcussionInjury preventionOccupational safety and healthPoison controlPhysical medicine and rehabilitationMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Identification of high-risk sports, including their most common and severe injuries and illnesses, will facilitate the identification of sports and athletes at risk at an early stage. AIM: To analyse the frequencies and characteristics of injuries and illnesses during the XXI Winter Olympic Games in Vancouver 2010. METHODS: All National Olympic Committees' (NOC) head physicians were asked to report daily the occurrence (or non-occurrence) of newly sustained injuries and illnesses on a standardised reporting form. In addition, the medical centres at the Vancouver and Whistler Olympic clinics reported daily on all athletes treated for injuries and illnesses. RESULTS: Physicians covering 2567 athletes (1045 females, 1522 males) from 82 NOCs participated in the study. The reported 287 injuries and 185 illnesses resulted in an incidence of 111.8 injuries and 72.1 illnesses per 1000 registered athletes. In relation to the number of registered athletes, the risk of sustaining an injury was highest for bobsleigh, ice hockey, short track, alpine freestyle and snowboard cross (15-35% of registered athletes were affected in each sport). The injury risk was lowest for the Nordic skiing events (biathlon, cross country skiing, ski jumping, Nordic combined), luge, curling, speed skating and freestyle moguls (less than 5% of registered athletes). Head/cervical spine and knee were the most common injury locations. Injuries were evenly distributed between training (54.0%) and competition (46.0%; p=0.18), and 22.6% of the injuries resulted in an absence from training or competition. In skeleton, figure and speed skating, curling, snowboard cross and biathlon, every 10th athlete suffered from at least one illness. In 113 illnesses (62.8%), the respiratory system was affected. CONCLUSION: At least 11% of the athletes incurred an injury during the games, and 7% of the athletes an illness. The incidence of injuries and illnesses varied substantially between sports. Analyses of injury mechanisms in high-risk Olympic winter sports are essential to better direct injury-prevention strategies.

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.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.244
Teacher spread0.239 · 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