The occurence of musculoskeletal disorders and level of upper trunk postural stability measured by upper quarter Y-balance test in guitar players
Bibliographic record
Abstract
Title: The occurence of musculoskeletal disorders and level of upper trunk postural stability measured by upper quarter Y-balance test in guitar players Objective: The thesis deals with arts medicine, health disorders and postural stability of guitar players. The aim of this diploma thesis is to determine prevalence of playing-related musculoskeletal disorers (PRMD) throught questionnaire and upper trunk postural stability level occuring in guitar players throught upper quarter Y-balance test (UQYBT). Methods: This experimental pilot study included 20 guitar player aged 18-25, playing the instrument 10-14 h per week at least. Prevalence of musculoskeletal disorders was measured by modified Nordic Musculoskeletal Diosorders Questionnaire. Definition of musculoskeletal disorders was specified by Zaza's PRMD definition. Annual and weekly prevalence of PRMD was determined and its effect on daily activities. Upper trunk postural stability level was measured by upper quarter Y-balance test. Composite score was calculated from maximal distances reached in each direction for analysis. Descriptive statistics, Microsoft Excel program and statistics method Shapiro-Wilk test were used for data analysis. Results: Annual prevalence of PRMD was found in 90 % of guitar players. PRMD in guitar players upper trunk...
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".