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Record W2396022660 · doi:10.1016/j.coem.2005.12.002

10.1016/j.coem.2005.12.002

2000· review· en· W2396022660 on OpenAlexvenueno aff
Geneva M. Giang

Bibliographic record

VenueTime to knit · 2000
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsEpidemiologyIntervention (counseling)MedicineWork (physics)Duration (music)Physical therapyPsychiatry

Abstract

fetched live from OpenAlex

In 2001, the number of repeated trauma cases accounted for 4% of total workplace injuries and 65% of all occupational illnesses, with work-related upper extremity disorders accounting for most cases. Because chronic disability leads to the highest cost, systematic evaluation of this growing occupational condition is needed. This article sheds light on work-related upper extremity disorders by understanding the prevalence and pattern for these diagnoses, their impact on outcomes influenced by age, gender and geography on metrics such as utilization, duration, disability status, and costs. To assess these types of outcomes measurements, a good reporting and management system must be in place to allow for ongoing evaluation and analysis of data and in the construction of intervention programs to improve provider performances and, ultimately, patient outcomes.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.331
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.6690.582

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 head0.017
GPT teacher head0.266
Teacher spread0.250 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2000
Admission routes1
Has abstractyes

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