Bibliographic record
Abstract
The purpose of this study is to analyze the sports injuries of patients who visited a sports rehabilitation center between April 1, 2014 to May 30, 2015 and provide basic data and useful information for the development of comprehensive and systematic care to patients. The total number of patient was 522; 358 men and 164 women. We analyzed the status of sports injuries by age, affiliation, pain region, disease nature, cause and quarter. For data analysis, the frequency and percentage were estimated; analysis of frequency and chi-square test were carried out by using SPSS Win Ver. 12.0. The results of the present study were as followed: First, the frequency of age groups in Teenagers and twenties were higher than others. Second, the frequency of affiliation groups was higher in order of ordinary people, middle school students, university students. Third, the frequency of pain region was higher in order of knee joint, ankle joint, lumber and sacral region. Fourth, the frequency of disease nature was higher in order of sprains and strains. The importance of such information lies in the fact that sports injuries are mostly avoidable and theoretically controllable through the implementation of preventive measures. We present basic data for sports medicine clinic utilization. Also, we expect that these data would be useful information for development of comprehensive and systemic rehabilitation care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".