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Record W2327581568 · doi:10.1097/nt.0b013e31826c50c6

The Glycemic Response to Ingested Dreamfields Pasta Compared With Traditional Pasta

2012· article· en· W2327581568 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 Today · 2012
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsNutrasource
FundersAmerican Heart AssociationU.S. Department of Energy
KeywordsGlycemicCrossover studyIngestionMedicineMealGlycemic indexFood scienceFingerstickDiabetes mellitusInternal medicineEndocrinologyChemistryPlaceboPathology

Abstract

fetched live from OpenAlex

In Brief Objective Dreamfields pasta is a modified commercially available pasta that is claimed to raise blood glucose much less than standard, unmodified pasta. Our objective was to quantify the blood glucose response to ingested Dreamfields pasta compared with an unmodified pasta. Research Design and Methods Using a blinded, randomized, crossover design, 20 subjects without diabetes ingested 50 g carbohydrate in the form of Dreamfields or traditional pasta at 8:00 AM after a 12- to 14-hour overnight fast. The preparation of both pastas was identical. Fingerstick blood glucose was measured before and at 30, 60, 90, 120, 150, and 180 minutes after ingestion of each pasta meal. Results The glucose response to ingestion of the 2 pasta products was essentially identical. Conclusion The 2 pastas tested had identical taste and mouth feel and resulted in nearly identical blood glucose responses in normal subjects. An eminent diabetologist takes a look at pastas that claim to be special in terms of glycemic index

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.417

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 head0.036
GPT teacher head0.254
Teacher spread0.218 · 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