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Record W2071709898 · doi:10.3389/fendo.2013.00090

Dairy Products and Prevention of Type 2 Diabetes: Implications for Research and Practice

2013· article· en· W2071709898 on OpenAlexaff
Maria Kalergis, Sylvie S.L. Leung Yinko, Roxana Nedelcu

Bibliographic record

VenueFrontiers in Endocrinology · 2013
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsMcGill UniversityMcGill University Health CentreDairy Farmers of OntarioDairy Farmers Of Canada
Fundersnot available
KeywordsType 2 diabetesDairy foodsMedicineObesityDairy cattleEnvironmental healthVitamin D and neurologyScientific evidenceDiabetes mellitusBiotechnologyFood scienceEndocrinologyBiologyAnimal science

Abstract

fetched live from OpenAlex

A growing body of scientific evidence has linked dairy intake to a reduced type 2 diabetes (T2D) risk. Using an evidence-based approach, we reviewed the most recent and strongest evidence on the relationship between dairy intake and the risk of T2D. Evidence indicates that dairy intake is significantly associated with a reduced T2D risk, and likely in a dose-response manner. The association between low-fat dairy and T2D risk reduction appears consistent. A beneficial impact is suggested for regular-fat dairy. The role of specific dairy products needs to be clarified. Potential underlying mechanisms include the role of dairy products in obesity and metabolic syndrome, as well as several dairy components, such as calcium, vitamin D, dairy fat, and specifically trans-palmitoleic acid. To conclude, there is strong, consistent, and accumulating evidence that dairy intake reduces the risk of T2D. More research is needed to better understand the role of regular-fat and specific dairy products. Well-designed randomized controlled trials and mechanistic studies are needed to support these findings. Efforts to translate this evidence into clinical practice and public health guidance are needed.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.152

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.085
GPT teacher head0.392
Teacher spread0.307 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations42
Published2013
Admission routes1
Has abstractyes

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