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Record W4402134803 · doi:10.1016/j.ajcnut.2024.07.004

Perspective on the health value of carbohydrate-rich foods: glycemic index and load; fiber and whole grains

2024· article· en· W4402134803 on OpenAlexaff
David J.A. Jenkins, Walter C. Willett

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2024
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsGlycemic loadGlycemic indexWhole grainsDietary fiberCarbohydrateGlycemicFood scienceGlycaemic indexRefined grainsPerspective (graphical)MedicineDiseaseHealth benefitsEnvironmental healthInternal medicineBiologyInsulinTraditional medicineMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: For over 45 y increasingly comprehensive food tables of glycemic index (GI) and glycemic load (GL) have been published in the American Journal of Clinical Nutrition to determine the GI and GL values of diets. Recently the WHO based on a 2019 series of meta-analyses concluded that increases in dietary fiber and whole grains but not reduction in GI or GL warranted recommendations for chronic disease reduction. METHODS AND RESULTS: We therefore provide a perspective on the current evidence that indicates that GI and GL are also determinants of risk of chronic disease outcomes. We are also concerned with the term dietary fiber used in the singular when there are many dietary fibers that may differ in their physiological effects. Furthermore, the term "whole grains" that refers to "whole grain flour" limits the exploration of "intact" grains that are low GI and have useful physiological effects. CONCLUSION: We conclude that all these determinants of the health values of carbohydrate-rich foods should be used in combination to assess the health value of carbohydrate-rich foods.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.032
GPT teacher head0.363
Teacher spread0.331 · 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 designOther design
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

Citations14
Published2024
Admission routes1
Has abstractyes

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