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Record W2498857291 · doi:10.1017/cbo9780511545795.023

Bisphosphonate therapy of osteoporosis

2000· book-chapter· es· W2498857291 on OpenAlexaff
Frederick R. Singer, Payam Minoofar

Bibliographic record

VenueCambridge University Press eBooks · 2000
Typebook-chapter
Languagees
FieldMedicine
TopicBone health and treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsOsteoporosisMedicineBisphosphonateInternal medicine

Abstract

fetched live from OpenAlex

Preclinical history About 100 years ago German chemists discovered that inorganic pyrophosphate could prevent deposition of calcium salts from solution. This observation was the basis of the industrial use of polyphosphates for prevention of calcium carbonate deposition in pipes. The first biological effect of a pyrophosphate analog was demonstrated in 1968 when Fleisch and his associates in Switzerland found that these agents could inhibit vitamin D-induced aortic calcification in rats (Schibler et al., 1968). Subsequent collaboration of the Swiss investigators with Dr M. D. Francis and his colleagues at Procter and Gamble resulted in the development of bisphosphonates which could be applied to the treatment of a variety of human disorders, the most common of which is osteoporosis. Chemistry The bisphosphonates, which were initially termed diphosphonates, are compounds which have two C—P bonds. The compounds are referred to as geminal bisphosphonates if the two bonds are found on the same carbon atom (P—C—P), although this class of compounds is usually simply termed bisphosphonates. The bisphosphonates are analogs of inorganic pyrophosphate whose core structure has a P—O—P structure. The substitution of an alkyl group confers resistance to hydrolysis to the bisphosphonates whereas inorganic pyrophosphate is highly susceptible to hydrolysis by pyrophosphatases such as alkaline phosphatase.

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)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.010

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 head0.026
GPT teacher head0.231
Teacher spread0.205 · 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
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

Citations2
Published2000
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooks→Same topicBone health and treatments→French-language works237,207→