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Milk Products, Insulin Resistance Syndrome and Type 2 Diabetes

2009· review· en· W1998542166 on OpenAlexaff
Angelo Tremblay, Jo‐Anne Gilbert

Bibliographic record

VenueJournal of the American College of Nutrition · 2009
Typereview
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsInsulin resistanceMedicineType 2 diabetesVitamin D and neurologyObservational studyDairy foodsInsulinDiabetes mellitusType 2 Diabetes MellitusMetabolic syndromeEndocrinologyInternal medicineEnvironmental healthFood scienceBiology

Abstract

fetched live from OpenAlex

A growing body of evidence suggests an inverse relationship between calcium and vitamin D status and dairy food intake and the development of the insulin resistance syndrome (IRS) and type 2 diabetes mellitus (t2DM). Observational studies show a consistent inverse association between dairy intake and the prevalence of IRS and t2DM. In a systematic review of the observational evidence, the odds for developing the IRS was 0.71 (95% CI, 0,57-0.89) for the highest dairy intake (3-4 servings/d) vs. the lowest intake (0.9-1.7 servings/d). Few interventional studies have been conducted to evaluate the effects of dairy food intake on the management of prevention of IRS or t2DM. Intervention studies that have examined the independent effects of dairy intake on specific metabolic components of the IRS including blood pressure and obesigenic parameters have shown favorable effects that support the observational findings albeit the results have been less consistent. Many metabolic and dietary factors appear to influence the degree to which dairy affects IRS metabolic parameters including calcium and vitamin D intake status, BMI, ethnicity and age. Overall, the intake of low-fat dairy products is a feature of a healthy dietary pattern which has been shown to contribute to a significant extent to the prevention of IRS.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.322
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.290
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 teacher head, 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

Citations124
Published2009
Admission routes1
Has abstractyes

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