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Human Obesity: Is Insufficient Calcium/Dairy Intake Part of the Problem?

2011· review· en· W1999168645 on OpenAlexaff
Angelo Tremblay, Jo‐Anne Gilbert

Bibliographic record

VenueJournal of the American College of Nutrition · 2011
Typereview
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCalciumOverweightWeight lossAppetiteObesityEndocrinologyMedicineInternal medicineRisk factorPhysiologyAnimal scienceBiology

Abstract

fetched live from OpenAlex

Epidemiological data have shown that low calcium intake is a risk factor for overweight and obesity. The clinical implications of this relationship have been confirmed in weight loss studies performed in low calcium consumers in whom calcium or dairy supplementation accentuated body weight and fat loss. Up to now, laboratory studies and clinical trials have demonstrated that this effect may be explained by an increase in fat oxidation and fecal loss as well as a facilitation of appetite control. Taken together, these observations suggest that insufficient calcium intake can be part of the obesity problem in some individuals and that an increase in calcium/dairy intake is part of the solution. Key teaching points: Low dietary calcium intake is a significant risk factor for overweight in adults. Calcium/dairy supplementation may accentuate the impact of a weight-reducing program in obese low calcium consumers. Calcium/dairy supplementation promotes fecal fat loss and fat oxidation. Calcium/dairy supplementation favors a decrease in energy intake and a facilitation of appetite control in obese individuals during weight loss.

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: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.061
GPT teacher head0.329
Teacher spread0.268 · 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

Citations43
Published2011
Admission routes1
Has abstractyes

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