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Record W2129443332 · doi:10.1139/h09-080

A meta-analysis of the effects of conjugated linoleic acid on fat-free mass in humans

2009· review· en· W2129443332 on OpenAlexvenueno aff
Dale A. Schoeller, Abigail C. Watras, Leah D. Whigham

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2009
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
Fundersnot available
KeywordsConjugated linoleic acidPlaceboLinoleic acidChemistryMeta-analysisInternal medicineFat massAnimal scienceEndocrinologyFood scienceBody weightMedicineBiologyBiochemistryFatty acidPathology

Abstract

fetched live from OpenAlex

Treatment of laboratory animals with a 50:50 mixture of c9,t11 and t10,c12 conjugated linoleic acid (CLA) results in fat loss and, to a smaller degree, fat-free mass (FFM) gain. In a previous meta-analysis, we found that CLA produced a fat loss, but that humans were not as responsive as mice. We performed a similar meta-analysis in the same 18 studies to test whether CLA increased FFM. Only placebo-controlled trials that measured body composition were included. We found that FFM increased during CLA treatment (0.3 +/- 0.7 kg; p = 0.05), but that the change did not display an effect of length of treatment (0.001 +/- 0.005 kg.week(-1); p = 0.8), or an effect of dosage (0.1 +/- 0.1 kg.g CLA(-1).day(-1); p = 0.3). We conclude that FFM does increase in humans during CLA treatment, but the onset of the increase is rapid and the total increase is small (<1%).

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)0.007
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.015
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.063
GPT teacher head0.345
Teacher spread0.282 · 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 designMeta-analysis
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

Citations36
Published2009
Admission routes1
Has abstractyes

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