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Record W1840503574 · doi:10.1139/apnm-2014-0549

Nutrients, satiety, and control of energy intake

2015· review· en· W1840503574 on OpenAlexaffvenue
Angelo Tremblay, France Bellisle

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2015
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAppetiteContext (archaeology)MicronutrientObesityIngestionEnvironmental healthEnergy (signal processing)Food intakeControl (management)Affect (linguistics)MedicinePsychologyEndocrinologyBiologyComputer scienceCommunicationMathematics

Abstract

fetched live from OpenAlex

In the context of the worldwide epidemic of obesity affecting men and women of all ages, it is important to understand the mechanisms that control human appetite, particularly those that allow the adjustment of energy intake to energy needs. Satiety is one important psycho-biological mechanism whose function is to inhibit intake following the ingestion of a food or a beverage. According to the classical theories of appetite control, satiety is influenced by macronutrient intake and/or metabolism. Satiety also seems to be modified by micronutrients, non-nutrients, and some bioactive food constituents. Under optimal conditions, satiety should be well connected with hunger and satiation in a way that spontaneously leads to a close match between energy intake and expenditures. However, the current obesity epidemic suggests that dysfunctions often affect satiety and energy intake. In this regard, this paper presents a conceptual integration that hopefully will help health professionals address satiety issues and provide the public with informed advice to facilitate appetite control.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.279
Teacher spread0.248 · 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

Citations126
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueApplied Physiology Nutrition and MetabolismSame topicRegulation of Appetite and ObesityFrench-language works237,207