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Efficacy of Garlic Supplementation in Lowering Serum Cholesterol Levels

2009· review· en· W1501729448 on OpenAlexaff
D. Spigelski, Peter J.H. Jones

Bibliographic record

VenueNutrition Reviews · 2009
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicGarlic and Onion Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsGARLIC POWDERCholesterolBlood viscosityMedicineInternal medicineBlood pressureEndocrinologyBlood lipidsFood scienceBlood cholesterolChemistry

Abstract

fetched live from OpenAlex

Previous studies using garlic have found alterations on a number of cardiovascular disease (CVD) risk factors including blood pressure, plasma viscosity, platelet activity, and serum lipid levels. The latest clinical research suggests that consumption of garlic powder does not play a significant role in lowering plasma lipid levels when in conjunction with a low-fat, low-cholesterol diet. Additional well-controlled, long-term studies that explore dosage and preparation type are necessary to confirm the efficacy of garlic in lowering cholesterol levels and to fully understand garlic's potential role in CVD.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.162
GPT teacher head0.372
Teacher spread0.210 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations30
Published2009
Admission routes1
Has abstractyes

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