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Record W7096116419

© 2002 Canadian Medical Association or its licensors

2002· article· en· W7096116419 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoporosisPostmenopausal womenBone mineralPrimary carePostmenopausal osteoporosisRisk assessmentFoundation (evidence)Clinical Practice
DOInot available

Abstract

fetched live from OpenAlex

JP. Evaluation of decision rules for referring women for bone densitom-etry by dual-energy x-ray absorp-tiometry. JAMA 2001;286:57-63. Background: A policy that recommends screening all postmenopausal women for low bone mineral density (BMD) would send many women unnecessarily for testing. Multiple clinical decision rules have been developed to assist clin-icians in deciding when to refer the average woman at risk for primary osteoporosis for bone densitometry. These rules range from simple to too complex to apply in day-to-day prac-tice. In addition, the National Osteo-porosis Foundation (NOF) practice guidelines1 recommend BMD testing for all women considering treatment who are 65 years or older and for younger postmenopausal women con-sidering treatment who have 1 or more risk factors for osteoporotic fracture other than menopause.

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)0.002
metaresearch head score (Gemma)0.014
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.311
Threshold uncertainty score0.523

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0050.001
Open science0.0020.001
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.6890.515

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 head0.049
GPT teacher head0.338
Teacher spread0.288 · 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
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

Citations0
Published2002
Admission routes1
Has abstractyes

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