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Record W2153012999 · doi:10.1002/mnfr.201400013

Extract of <scp>I</scp>rish potatoes (<i><scp>S</scp>olanum tuberosum</i> L.) decreases body weight gain and adiposity and improves glucose control in the mouse model of diet‐induced obesity

2014· article· en· W2153012999 on OpenAlexafffund
Stan Kubow, Luc Hobson, Michèle M. Iskandar, Kebba Sabally, Danielle J. Donnelly, Luis B. Agellon

Bibliographic record

VenueMolecular Nutrition & Food Research · 2014
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsLeptinGhrelinResistinEndocrinologyInternal medicineObesityWeight gainInsulinDiabetes mellitusChemistryMedicineBody weightBiologyFood scienceHormoneAdipokine

Abstract

fetched live from OpenAlex

Both sexes of mice were fed a high fat diet (HFD) for 10 weeks without and with polyphenolic-rich potato extracts (PRPE) of cultivars Onaway and Russet Burbank. PRPE attenuated weight gain in male and female mice by as much as 63.2%, which was associated mostly with a reduction in adiposity. Mice receiving PRPE showed enhanced capacity for blood glucose clearance. Sex differences regarding the impact of HFD and PRPE on plasma levels of insulin, ghrelin, leptin, gastric inhibitory peptide, and resistin were noted. PRPE may serve as part of a preventative dietary strategy against the development of obesity and type 2 diabetes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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

Citations36
Published2014
Admission routes2
Has abstractyes

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