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Record W1973109904 · doi:10.1055/s-2004-826159

Nutrient, Neural and Endocrine Control of Glucagon-like Peptide Secretion

2004· review· en· W1973109904 on OpenAlexafffund
P. Dubé, P. L. Brubaker

Bibliographic record

VenueHormone and Metabolic Research · 2004
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchHealth CanadaCanada Research ChairsCanadian Diabetes Association
KeywordsGlucagon-like peptide-1SecretionEndocrinologyInternal medicineEndocrine systemGlucagon-like peptide-2Enteroendocrine cellGlucagonDigestion (alchemy)MetabolismBiologyChemistryDiabetes mellitusMedicinePeptideInsulinType 2 diabetesHormoneBiochemistry

Abstract

fetched live from OpenAlex

The intestinal glucagon-like peptides, GLP-1 and GLP-2, are important regulators of nutrient intake, digestion, absorption and metabolism. Extensive studies have shown that the co-secretion of GLP-1 and GLP-2 is regulated by a variety of dietary nutrient, neural and endocrine inputs. Furthermore, secretion of these peptides is altered in a number of pathological conditions, including type 2 diabetes and obesity. The purpose of this review is to discuss the regulation of GLP-1 and GLP-2 secretion in both health and disease.

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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.072
GPT teacher head0.387
Teacher spread0.316 · 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

Citations99
Published2004
Admission routes2
Has abstractyes

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