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Record W2993647374

Chronic back problems among workers.

2000· article· en· W2993647374 on OpenAlexaffabout
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Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsMedicineDepression (economics)DemographyLogistic regressionIncidence (geometry)PopulationGerontologyHealth problemsEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: This article examines associations between selected work- and non-work-related factors and the incidence of chronic back problems over the next two years. DATA SOURCE: The data are from the longitudinal household component of the National Population Health Survey, conducted by Statistics Canada. The analysis is based on 3,234 male and 3,129 female respondents who, in 1994/95, were aged 16 or older, employed, rated their health as good, very good or excellent, and reported no diagnosed chronic back problems. ANALYTICAL TECHNIQUES: All analyses were weighted to represent the Canadian population in 1994/95. Unadjusted cross-tabulations and multiple logistic regression were used to examine the associations between respondents' characteristics in 1994/95 and newly diagnosed chronic back problems in 1996/97. MAIN RESULTS: More than 1 million (9%) Canadian workers aged 16 or older developed chronic back problems between 1994/95 and 1996/97. Back injury, chronic stress, depression, and being aged 40 to 49 were significantly associated with subsequent chronic back problems.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.667

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations19
Published2000
Admission routes2
Has abstractyes

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