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Record W3047233339 · doi:10.2217/imt-2020-0158

Romosozumab in the Treatment of Osteoporosis

2020· article· en· W3047233339 on OpenAlexaff
Alexandra Kobza, Αλεξάνδρα Παπαϊωάννου, Arthur Lau, Jonathan D. Adachi

Bibliographic record

VenueImmunotherapy · 2020
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsImpactMcMaster University
FundersAmgen
KeywordsSclerostinOsteoporosisMedicineBone resorptionBone mineralBone Density Conservation AgentsWnt signaling pathwayInternal medicineBioinformaticsChemistrySignal transductionBiologyBiochemistry

Abstract

fetched live from OpenAlex

Osteoporosis is a disease characterized by weakening of the bone architecture, which leads to an increased risk of fracture. There has been interest in the development of osteoanabolic agents that can increase bone mass and reverse the deteriorating architecture of osteoporotic bone. Romosozumab is a new agent for osteoporosis that both promotes bone formation and inhibits bone resorption. It is a monoclonal antibody that inhibits the activity of sclerostin, which allows the Wnt pathway to promote osteoblastogenesis and inhibit the activity of bone-resorbing osteoclasts. In clinical trials, it has proven to be superior to other agents in terms of increasing bone mineral density and reducing the incidence of fractures. This review will highlight the pharmacology, clinical efficacy and safety profile of romosozumab and suggest where this medication may fit within our current management of 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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.719
Threshold uncertainty score0.201

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)0.0000.000

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 head0.049
GPT teacher head0.346
Teacher spread0.297 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations21
Published2020
Admission routes1
Has abstractyes

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