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Record W4210984016 · doi:10.1002/9781118387658.ch45

α‐Glucosidase inhibitors

2015· other· en· W4210984016 on OpenAlexaff
Josée Leroux‐Stewart, Rémi Rabasa‐Lhoret, Jean‐Louis Chiasson

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsUniversité de MontréalMontreal Clinical Research InstituteCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsChemistryMathematics

Abstract

fetched live from OpenAlex

Alpha-glucosidase inhibitors are oral antidiabetic medications that delay the digestion of complex carbohydrates by acting as competitive inhibitors of intestinal α-glucosidases. By delaying glucose absorption, these drugs decrease the postprandial rise in plasma glucose and thus the rise in plasma insulin, whether they are used as monotherapy or in combination for the treatment of diabetes. They show a moderate but constant and sustained reduction of HbA1c (˜0.7%) regardless of concomitant medication in patients with both type 2 and type 1 diabetes. In subjects with impaired glucose tolerance, they decrease the risk of progressing to type 2 diabetes, and are associated with a reduction in new cases of hypertension and cardiovascular events. Alpha-glucosidase inhibitors are not associated with hypoglycemic risk or weight gain. Alhough they are frequently associated with gastrointestinal symptoms due to undigested carbohydrates reaching the colon, they have an excellent safety profile. These side effects can be minimized by the “start low and go slow” policy.

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: Other · Consensus signal: Other
Teacher disagreement score0.045
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0450.018

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 head0.020
GPT teacher head0.318
Teacher spread0.298 · 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

Citations26
Published2015
Admission routes1
Has abstractyes

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