MétaCan
Menu
Back to cohort
Record W2148732700 · doi:10.1094/cchem-03-12-0031-r

Glycemic Response to Extruded Oat Bran Cereals Processed to Vary in Molecular Weight

2012· article· en· W2148732700 on OpenAlexafffund
Yolanda Brummer, Ruedi Duss, Thomas M.S. Wolever, Susan M. Tosh

Bibliographic record

VenueCereal Chemistry · 2012
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsGlycemic Index LaboratoriesAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsFood scienceBranGlycemic indexChemistryAvenaPalatabilityPostprandialGlycemicAnimal scienceBotanyBiologyInsulinBiotechnology

Abstract

fetched live from OpenAlex

ABSTRACT Oat β‐glucan enriched extruded cereals with molecular weights (MWs) ranging from 2,180,000 to 326,000 were produced. Test meals composed of 31 g of available carbohydrate, 8.3–8.7 grams of β‐glucan, and milk were administered to subjects and their postprandial blood glucose levels monitored for 2 hr. White bread plus milk and a control wheat bran cereal plus milk were administered, and white bread alone served as a reference food for estimation of glycemic index (GI) of the cereals, after adjusting for the effect of adding milk to white bread. Both oat bran and wheat bran cereals significantly reduced peak blood glucose rise (PBGR) and area under the curve (AUC) versus white bread alone or white bread plus milk. There was a significant inverse relationship between AUC and log 10 [weight average MW] ( r 2 = 0.96, P = 0.0192). There was a significant inverse relationship between PBGR and log 10 [viscosity] of in vitro extracts from all cereals, including the wheat control ( r 2 = 0.96, P = 0.0031). However, no significant differences in glycemic responses among the oat bran cereals were found with pairwise comparisons. All cereals were low GI (<55) and were significantly lower than white bread alone or white bread plus milk. Among the oat bran cereals, palatability was positively correlated with MW ( r 2 = 0.98, P = 0.0110).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.911

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 head0.012
GPT teacher head0.257
Teacher spread0.244 · 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 designBench or experimental
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

Citations54
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueCereal ChemistrySame topicFood composition and propertiesFrench-language works237,207