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Record W2131442234

Approach to injuries in active people.

2006· article· en· W2131442234 on OpenAlexaff
Ian Shrier

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsObservational studyMedicineRandomized controlled trialPhysical therapyMusculoskeletal injuryPopulationHuman factors and ergonomicsInjury preventionAlternative medicinePoison controlPhysical medicine and rehabilitationMedical emergencySurgeryPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To review the basic principles underlying treatment of injuries in active people. SOURCES OF INFORMATION: Basic science texts and reports of observational and randomized trials on treatment of musculoskeletal injuries were retrieved during previous exhaustive systematic reviews published by the author on a variety of musculoskeletal injury topics. MAIN MESSAGE: After an injury, further damage or re-injury can be prevented either by decreasing the stress on the tissue or increasing the stress the tissue can withstand. Regardless of the type of injury, clinicians should aim to restore function; aim to increase activity without increasing pain; recommend that patients start slowly and increase activity gradually; revisit diagnosis and treatment if patients are not responding; and treat the patient, not the condition. CONCLUSION: Most musculoskeletal injuries in the general population can be managed effectively by family physicians. Management should follow the basic principles of exercise training.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2006
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicSports injuries and prevention→French-language works237,207→