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African Mango (Irvingia gabonensis) Extract for Weight Loss: A Systematic Review

2013· review· en· W2169525936 on OpenAlexvenueno aff
A. N. McLendon, Justin Spivey, C. B. Woodis

Bibliographic record

VenueJournal of Nutritional Therapeutics · 2013
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicCocoa and Sweet Potato Agronomy
Canadian institutionsnot available
Fundersnot available
KeywordsTraditional medicineBiologyWeight lossFood scienceObesityMedicineEndocrinology

Abstract

fetched live from OpenAlex

Objective: The objective of this review is to assess the effectiveness and safety of African mango (Irvingia gabonensis) extract on weight loss in humans. Design: A systematic review of articles evaluating the effect of African mango, IGOB131, dikanut, bush mango or Irvingia gabonensis on weight and obesity was conducted. Population: Three randomized, controlled trials were identified and met criteria for inclusion in the review with a total of 214 subjects receiving Irvingia gabonensis at various doses alone or in combination with other dietary supplements versus placebo over a period of four to ten weeks. Results: All studies demonstrated a decrease in weight ranging from 4-12kg (p<0.05). Other measures of weight loss including body fat percentage (p<0.05) and waist circumference (p<0.01) were also significantly decreased by Irvingia gabonensis. Improvements were also seen in total cholesterol, low density lipoprotein and fasting blood glucose. Few adverse events were reported but include insomnia, flatulence and headache. Conclusions: Irvingia gabonensis demonstrates potential for significant weight loss of up to 12 kilograms in overweight and obese subjects over a period of 10 weeks with few reported adverse events. Larger studies including subjects from multiple countries for 6 to 12 months should be conducted to elucidate the long-term effects in various populations.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.739
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.087
GPT teacher head0.314
Teacher spread0.227 · 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 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

Citations4
Published2013
Admission routes1
Has abstractyes

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