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Record W4387229392 · doi:10.1016/j.jff.2023.105806

Chia seeds (Salvia hispanica L.), incorporated into cookies, reduce postprandial glycaemic variability but have little or no effect on subjective appetite

2023· article· en· W4387229392 on OpenAlexaff
Thomas M.S. Wolever, Janice Campbell, Fei Au‐Yeung, Elhadji M. Dioum, Varsha Shete, YiFang Chu

Bibliographic record

VenueJournal of Functional Foods · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides Composition and Applications
Canadian institutionsGlycemic Index Laboratories
FundersPepsiCo
KeywordsPostprandialAppetiteFood scienceMedicineAnimal scienceChemistryBiologyInternal medicineEndocrinologyDiabetes mellitus

Abstract

fetched live from OpenAlex

Chia seeds are gaining interest as a potential functional food. We compared the subjective hunger, fullness and glycaemic responses elicited by 30 g cookies containing 0, 3, 5 or 7 g chia seed (CS0, CS3, CS5 or CS7; 140–150 kcal, 7–8 g fat, 4 g protein, 0–2 g dietary-fibre, 16 g available-carbohydrate) using a randomized, double-blind, cross-over design. Overnight-fasted heathy adults (24 male, 22 female) consumed test-cookies with endpoints measured before and intermittently for 3 h after eating. Total areas under the curve (tAUC0-3 h) for hunger were similar among treatments (p = 0.49) but fullness differed (p = 0.019) with tAUC0-3 h after CS3 > CS7 (mean ± SEM) (140 ± 9 vs 122 ± 10 mm × h, p < 0.025), but neither different from CS0 (127 ± 10 mm × h). Mean incremental glucose AUC0-2 h after CS3, CS5 and CS7, respectively, were 22%, 23% and 30% less than CS0 (p < 0.05). Thus, although chia seeds reduced glycaemic responses, we were unable to demonstrate a significant effect on hunger or fullness versus control.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.918
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.256
Teacher spread0.233 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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