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Record W1590967661 · doi:10.15537/1658-3175.2904

Osteoporosis in men

2005· article· en· W1590967661 on OpenAlexaff
R. Faraawi

Bibliographic record

VenueSaudi Medical Journal · 2005
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsMedicineOsteoporosisBone mineralVitamin D and neurologyProspective cohort studyBisphosphonateBone densityInternal medicinePhysical therapyPediatrics

Abstract

fetched live from OpenAlex

Osteoporosis and fragility fractures are more prevalent in men than previously assumed and mortality rates following a major osteoporotic fracture are higher in men as compared with women. There is still uncertainty on how to interpret bone mineral density BMD in men, and few prospective studies exist that have examined the association between BMD and fracture risk. Prospective studies that have evaluated fracture risk suggest that risk increases as BMD decreases in men in a similar way as described in women. Although data are limited, prior fragility fractures also increase subsequent fracture risks in both men and women. Prevention of osteoporosis in men is important and should begin during childhood. During adulthood, calcium and vitamin D and adequate physical activity play major preventative roles. There is minimal data to suggest treatment of osteoporosis in men on the sole basis of t-score BMD measurement. However, if therapy is necessary, bisphosphonate use should be the first choice for treatment in men.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.023
GPT teacher head0.355
Teacher spread0.333 · 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
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

Citations2
Published2005
Admission routes1
Has abstractyes

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