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Record W4240304287 · doi:10.1037/e615452012-018

The impact of arthritis on Canadian women

2003· dataset· en· W4240304287 on OpenAlexaffabout
Naomi M. Kasman, Elizabeth M. Badley

Bibliographic record

VenuePsycEXTRA Dataset · 2003
Typedataset
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsArthritisMedicineInternal medicine

Abstract

fetched live from OpenAlex

Health Issue: Arthritis is one of the most prevalent chronic conditions in Canada and a leading cause of long-term disability, pain, and increased health care utilization.It is also a far more prevalent condition among women than men.Information was obtained primarily from the 1998-99 National Population Health Survey and the Canadian Joint Replacement Registry. Key Findings:In 1998, the overall prevalence of self-reported arthritis or rheumatism in Canadian women was 20.0%.This rate increased to 55.6% among women over 75 years of age.Compared to women with chronic conditions, women with arthritis were more likely to experience long-term disability; report worse health; experience more pain; be dependent upon others and consult general practitioners, specialists, and physiotherapists more frequently.While men and women with arthritis under-utilize total joint replacement surgery, the degree of under-use was over three times greater for women. Data Gaps and Recommendations:There is a lack of detailed information on the use of health care services by women with arthritis.There are also no systematic data available on the prescribing of medications, access to services such as assistive devices or exercise programs, or use of community support, self-management strategies, or rehabilitation services.The burden of arthritis both on women and on society is expected to increase as the population ages.A comprehensive health strategy to reduce the impact of arthritis is required to ensure that health and support services are available in a timely manner and provided in such a way to meet the needs of Canadian women.

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 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)0.000
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.024
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.314
Teacher spread0.305 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations1
Published2003
Admission routes2
Has abstractyes

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