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Record W6990740231

The Effect of Salvia hispanica L. (Salba) on Weight Loss in Overweight and Obese Individuals with Type 2 Diabetes Mellitus

2011· dissertation· en· W6990740231 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace (University of Toronto) · 2011
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsnot available
Fundersnot available
KeywordsOverweightType 2 Diabetes MellitusWeight lossGlycemicObesityDiabetes mellitusType 2 diabetesIncidence (geometry)
DOInot available

Abstract

fetched live from OpenAlex

Canadian statistics indicate that the incidence of obesity is rising, and that the prevalence of type 2 diabetes mellitus (T2DM) within this group is significantly higher than those of a healthy weight. Preliminary evidence has shown that the oil-rich grain, Salvia hispanica L. (Salba), improves glycemic control, suppresses appetite, and affects additional cardiovascular disease (CVD) risk factors. This study followed a randomized, double-blind, placebo-controlled, parallel design in a sub-set population of twenty individuals who were overweight or obese and had T2DM. Participants received supplements of Salba, or an energy- and fibre-matched control, and followed a hypocaloric diet for 24 weeks. Findings of this study reveal that Salba does not significantly affect weight loss, glycemic control or other CVD risk factors. These findings are preliminary and highlight the complexities of weight loss research. Further investigation into the potential health benefits of Salba is currently being carried out.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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