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Record W1498385043 · doi:10.1002/9781119006039.ch15

PHYTOTHERAPIES FOR THE MANAGEMENT OF OBESITY AND DIABETES

2015· other· en· W1498385043 on OpenAlexaff
Michel Rapinski, Alain Cuerrier

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicNatural Antidiabetic Agents Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsObesityDiabetes mellitusMedicineIntensive care medicineDiseaseChronic diseaseDiabetes managementType 2 diabetesEnvironmental healthInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

World Health Organization (WHO) has cited obesity as a global epidemic and its prevalence is indeed increasing at an alarming rate worldwide. Diabetes, on the other hand, is a chronic affliction characterized by hyperglycemia, an elevated blood glucose concentration, that is caused by a decreased insulin secretion, which is generally related to problems with pancreatic ß cells. As endorsed by WHO in its resolutions for traditional medicines, phytotherapies from local pharmacopoeias should be investigated and employed, that is, in primary health care to alleviate the burden of obesity and diabetes. This chapter provides support for the rightful place of phytotherapies in the management of these problems by demonstrating how developing rigorous platforms for the pharmacological screening of botanical extracts provide empirical evidence to their efficacy in chronic disease treatment. The chapter demonstrates how the necessity of community participation in integrating phytotherapies into culturally adapted treatments can lead to greater compliance.

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: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.003

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 head0.019
GPT teacher head0.271
Teacher spread0.252 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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