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Record W3048866077 · doi:10.14309/crj.0000000000000429

Acute Severe Liver Injury Related to Long-Term Garcinia cambogia Intake

2020· article· en· W3048866077 on OpenAlexaff
Victor H. Ferreira, Alexandre Mathieu, Geneviève Soucy, Jeanne‐Marie Giard, Domitille Erard‐Poinsot

Bibliographic record

VenueACG Case Reports Journal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineLiver transplantationGarciniaLiver injuryLiver failureTraditional medicineDrugGastroenterologyInternal medicinePharmacologyTransplantation

Abstract

fetched live from OpenAlex

ABSTRACT Herbal and dietary supplements are frequently used as weight loss supplements. However, they account for 20% of drug-induced liver injury. Garcinia cambogia 's (GC) active compound, hydroxycitric acid, can be found among those supplements. We report a 26-year-old woman who had been taking GC for 7 months when she presented with subacute liver failure and ultimately required a liver transplantation. This report highlights the risk of liver injury after long-term use of GC and demonstrates the importance of considering a close and prolonged monitoring of patients in a tertiary liver transplant center.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.286
Teacher spread0.258 · 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.

Study designCase report
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

Citations19
Published2020
Admission routes1
Has abstractyes

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