MétaCan
Menu
Back to cohort

Informing food choices and health outcomes by use of the dietary glycemic index

2011· review· en· W2158741283 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNutrition Reviews · 2011
Typereview
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversity of Toronto
FundersU.S. Public Health ServiceNational Institutes of HealthNational Eye InstituteAmerican Health Assistance FoundationU.S. Department of Agriculture
KeywordsGlycemic indexGlycemic loadMedicineGlycemicEnvironmental healthGlycaemic indexEpidemiologyHealth benefitsConsistency (knowledge bases)Food scienceDiabetes mellitusInternal medicineEndocrinologyBiologyTraditional medicineComputer science

Abstract

fetched live from OpenAlex

Considerable epidemiologic evidence links consuming lower glycemic index (GI) diets with good health, particularly upon aging. The GI is a kinetic parameter that reflects the ability of carbohydrate (CHO) contained in consumed foods to raise blood glucose in vivo. Newer nutritional, clinical, and experimental data link intake of lower dietary GI foods to favorable outcomes of chronic diseases, and compel further examination of the record. Based upon the new information there are two specific questions: 1) should the GI concept be promoted as a way to prolong health, and 2) should food labels contain GI information? Further, what are the remaining concerns about methodological issues and consistency of epidemiological data and clinical trials that need to be resolved in order to exploit the benefits of consuming lower GI diets? These issues are addressed in this review.

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.

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 score0.917
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
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 head0.240
GPT teacher head0.393
Teacher spread0.153 · 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