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Record W4281757184 · doi:10.1080/00325481.2022.2069582

The role of osteoanabolic agents in the management of patients with osteoporosis

2022· review· en· W4281757184 on OpenAlexaff
Michael R. McClung, Micol S. Rothman, E. Michael Lewiecki, David A. Hanley, Steven T. Harris, Paul D. Miller, David L. Kendler

Bibliographic record

VenuePostgraduate Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of British ColumbiaAlberta Bone and Joint Health InstituteUniversity of Calgary
FundersRadius Health
KeywordsMedicineOsteoporosisBone remodelingIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Reducing fracture risk is the objective of osteoporosis treatment. Bone-forming osteoporosis drugs increase bone mass, restore bone microarchitecture, and reduce fracture risk more effectively than oral bisphosphonates, providing strong justification for the use of these agents as the initial therapy or after anti-remodeling agents in patients at very high risk of fracture. At the end of a 12-to-24-month course of osteoanabolic therapy, transitioning to a potent anti-remodeling agent maintains and enhances the treatment benefit. This review describes the clinical applications of osteoanabolic therapy for osteoporosis.

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)0.001
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.064
GPT teacher head0.370
Teacher spread0.306 · 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

Citations17
Published2022
Admission routes1
Has abstractyes

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