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Comparable Dose‐Response Glucose Lowering Effect with Whole vs finely Ground, Novel Omega‐3 rich Grain Salba (Salvia Hispanica L) Baked into White Bread

2009· article· en· W110351993 on OpenAlexaff
Vladimir Vuksan, André H. Dias, Amy S. Lee, Elena Jovanovski, Alex L. Rogovik, Alexandra L. Jenkins

Bibliographic record

VenueThe FASEB Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsPostprandialFood scienceWhole grainsCrossover studyAnimal scienceChemistryMedicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

Objective Oily grains such as flax, sesame and poppy are common additions to bakery products. To evaluate the effect of particle size on postprandial glycemia, whole or finely ground omega‐3 rich grain Salba was baked into white bread in a dose response study. Methods Using an acute randomized, double‐blind, crossover design, 13 healthy subjects (5M; 8F; BMI 26.3 ± 7.3kg/m2) received, on 8 different occasions, either 7, 15 or 24 g of whole or finely ground Salba baked into white bread cotaining 50g available carbohydrate or bread control given twice. Capillary blood was taken fasting and at 15, 30, 45, 60, 90 and 120 minutes after consumption. Results Compared to control, all treatments containing 7,15,or 24g of whole and ground Salba reduced blood glucose iAUC (p=0.03) by 20%, 28% and 35% respectively compared to control (p<0.05), in dose dependent fashion (slope = ‐1.2 ± 0.05). No differences in glucose responses were found between whole vs ground Salba at the same dose levels. Conclusions Addition of either whole or finely ground Salba to white bread lowers postprandial glycemia equally in a dose‐dependent manner making this novel omega‐3 grain versatile for consumption. Baking whole Salba in bread may also extend shelf life by minimizing fat oxidation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.283
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2009
Admission routes1
Has abstractyes

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