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Record W4239873580 · doi:10.17925/use.2013.09.02.128

The Role of Fructose, Sucrose, and High-fructose Corn Syrup in Diabetes

2013· article· en· W4239873580 on OpenAlexafffund
Adrian I. Cozma, John L. Sievenpiper

Bibliographic record

VenueUS Endocrinology · 2013
Typearticle
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsMcMaster UniversityUniversity of TorontoSt. Michael's Hospital
FundersCanadian Institutes of Health ResearchNational Institutes of HealthEuropean Association for the Study of DiabetesEuropean Foundation for the Study of DiabetesCanadian Diabetes AssociationNational Institute of Diabetes and Digestive and Kidney DiseasesCoca-Cola FoundationAbbott LaboratoriesAmerican Heart Association
KeywordsFructoseHigh-fructose corn syrupSucroseMedicineCorn syrupSugarAdded sugarFood scienceDiabetes mellitusDietary SucroseAdverse effectObesityEndocrinologyInternal medicineChemistry

Abstract

fetched live from OpenAlex

Concerns are growing regarding the role of dietary sugars in the development of obesity and cardiometabolic diseases, including diabetes. High-fructose corn syrup (HFCS) and sucrose are the most important dietary sweeteners. Both HFCS and sucrose have overlapping metabolic actions with adverse effects attributed to their fructose moiety. Ecologic studies have linked the rise in fructose availability with the increases in obesity and diabetes worldwide. This link has been largely underpinned by animal models and select human trials of fructose overfeeding at high levels of exposure. Although prospective cohort studies have shown significant associations comparing the highest with the lowest levels of intake sugar-sweetened beverages, these associations are small, do not hold at moderate levels of intake, and are subject to collinearity effects from related dietary and lifestyle factors. Most systematic reviews and meta-analyses from controlled feeding trials have shown that fructosecontaining sugars in isocaloric exchange for other carbohydrates do not show evidence of harm and, in the case of fructose, may even have advantages for glycemic control, especially at small doses. Nevertheless, trials in which fructose-containing sugars supplement diets with excess energy have shown adverse effects, effects that appear more attributable to the excess energy than the sugar. There is no unequivocal evidence that fructose intake at moderate doses is directly related with adverse metabolic effects, although there is potentially cause for concern where fructose is provided at high doses or contributes excess energy to diets. Further investigation is warranted due to the significant knowledge gaps and weaknesses in existing research.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.004
GPT teacher head0.216
Teacher spread0.212 · 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

Citations7
Published2013
Admission routes2
Has abstractyes

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