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Record W2213131614

제10회 밴쿠버 장애인동계올림픽 참가 대한민국선수의 스포츠상해 실태 분석

2012· article· ko· W2213131614 on OpenAlexaboutno aff
강선영, 조창옥, 장지훈, 이상식

Bibliographic record

Venue한국체육과학회지 · 2012
Typearticle
Languageko
FieldMedicine
TopicDiverse Approaches in Healthcare and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIncidence (geometry)AthletesPhysical therapyRehabilitationWheelchair
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to analyze sports injuries(SI) in Korean athletes during the 10th Vancouver winter paralympics(WP), and to provide the essential information for Korea delegation against the next WP Detailed information on SI was collected by sports medical team during the 10th WP with prospective surveillance study. Total 40 injuries were reported as musculoskeletal disorders(MD). Among them, 16 injuries were acute, and 24 injuries were chronic with previous history. In acute MD, the highest prevalent event, type, and region were ice sledge hochey, joint sprain, and upper limbs, respectively. In chronic MD, the highest prevalent event, type, and region were wheelchair curling, arthrodynia, shoulder, respectively. In addition, 13 injuries were reported as internal diseases and infection. Incidence rate(1000AE) and incidence proportion were 332.4 and 0.53 in acute MD, 461.0 and 0.68 in chronic MD, and 241.1 and 0.44 in internal diseases and infection on the average, respectively. As a result, our data indicated the characteristics and frequency, incidence rate, incidence proportion of SI during the loth WP, so these results could provide the effective information for prevention SI for disabled athletes. In conclusion it is suggested that team-based education for SI prevention and exercise rehabilitation program should be provided for disabled athletes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.008

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 head0.181
GPT teacher head0.395
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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