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The Glycemic Index: Physiological Significance

2009· review· en· W2122813533 on OpenAlexaff
Amin Esfahani, Julia MW Wong, Arash Mirrahimi, Korbua Srichaikul, David J.A. Jenkins, Cyril W.C. Kendall

Bibliographic record

VenueJournal of the American College of Nutrition · 2009
Typereview
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversity of TorontoUniversity of SaskatchewanSt. Michael's Hospital
Fundersnot available
KeywordsPostprandialMedicineGlycemic indexGlycemic loadGlycemicInternal medicineDiabetes mellitusCohortEndocrinologyInsulin resistance

Abstract

fetched live from OpenAlex

The glycemic index (GI) is a physiological assessment of a food's carbohydrate content through its effect on postprandial blood glucose concentrations. Evidence from trials and observational studies suggests that this physiological classification may have relevance to those chronic Western diseases associated with overconsumption and inactivity leading to central obesity and insulin resistance. The glycemic index classification of foods has been used as a tool to assess potential prevention and treatment strategies for diseases where glycemic control is of importance, such as diabetes. Low GI diets have also been reported to improve the serum lipid profile, reduce C-reactive protein (CRP) concentrations, and aid in weight control. In cross-sectional studies, low GI or glycemic load diets (mean GI multiplied by total carbohydrate) have been associated with higher levels of high-density lipoprotein cholesterol (HDL-C), with reduced CRP concentrations, and, in cohort studies, with decreased risk of developing diabetes and cardiovascular disease. In addition, some case-control and cohort studies have found positive associations between dietary GI and risk of various cancers, including those of the colon, breast, and prostate. Although inconsistencies in the current findings still need to be resolved, sufficient positive evidence, especially with respect to renewed interest in postprandial events, suggests that the glycemic index may have a role to play in the treatment and prevention of chronic diseases.

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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.910
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.333
Teacher spread0.296 · 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

Citations113
Published2009
Admission routes1
Has abstractyes

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