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Record W2142699634 · doi:10.1139/h04-006

Exercise and Estrogen or Estrogen Alternatives (Phytoestrogens, Bisphosphonates) for Preservation of Bone Mineral in Postmenopausal Women

2004· review· en· W2142699634 on OpenAlexaff
Philip D. Chilibeck

Bibliographic record

VenueCanadian Journal of Applied Physiology · 2004
Typereview
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhytoestrogensEstrogenMedicineBone mineralOsteoporosisBisphosphonateEndocrinologyPostmenopausal womenInternal medicine

Abstract

fetched live from OpenAlex

Research in animal models indicates that without estrogen, the effectiveness of exercise for increasing bone mineral in females is reduced. With decreased estrogen levels, there is an increase in the threshold at which strains are detected by bone, in turn reducing the transmission of mechanical to biochemical signals for bone formation. Studies combining estrogen replacement and exercise training in postmenopausal women have yielded mixed results but indicate that the combination of interventions may be more effective than either intervention alone for increasing bone mass. Given the continued debate over the risks and benefits of estrogen replacement, other compounds such as bisphosphonates or phytoestrogens may be preferred in combination with exercise training for optimally increasing bone mass and preventing osteoporotic fracture. Studies on animals show that the combination of bisphosphonate or phytoestrogen supplementation with exercise training is effective, but trials in humans are lacking.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.039
GPT teacher head0.339
Teacher spread0.300 · 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 designSystematic review
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

Citations12
Published2004
Admission routes1
Has abstractyes

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