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Record W2066737979 · doi:10.1177/0027432110370736

Injury Prevention

2010· article· en· W2066737979 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.

Bibliographic record

VenueMusic Educators Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicMusicians’ Health and Performance
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Research in performing arts medicine has demonstrated that approximately 25% of music students experience a playing-related injury 1 .Since musicians' musculoskeletal injuries are associated with several factors related to practice habits 2,3,4 , music teachers can and should play a vital role in injury prevention.There is evidence that music teachers who receive relevant training in music-specific physiology do make changes in their teaching, and that these changes subsequently benefit their students 5 .This paper aims to provide music teachers with practical prevention strategies that can be used with all instrumentalists.Included are specific instructions regarding the nature and importance of several strategies, including: taking breaks, pacing techniques, cognitive rehearsal, ergonomics, warm-up and cool-down, preparing for performances, and the question of whether or not stretching is advisable.Emphasis will be placed on how music teachers (regardless of instrument) can incorporate prevention strategies into their lessons.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.024
GPT teacher head0.347
Teacher spread0.323 · 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