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Record W4233034411 · doi:10.14740/jmc3108w

A Delayed Case of Black Cohosh Associated Drug-Induced Liver Injury

2018· article· en· W4233034411 on OpenAlexvenueno aff
Sara Khodor, Max Feldman

Bibliographic record

VenueJournal of Medical Cases · 2018
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsBlack cohoshMedicineLiver injuryDrugAcetaminophenCulpritOver-the-counterMedical prescriptionTraditional medicineInternal medicinePharmacology

Abstract

fetched live from OpenAlex

Drug-induced liver injury is the leading cause of acute liver failure in the United States. While acetaminophen is the most common culprit, there are over 1,000 prescriptions and over the counter medications that have been implicated. Black cohosh is an herbal supplement commonly used for the treatment of menopausal symptoms which has been reported to cause drug-induced liver injury. The latency period of black cohosh drug induced liver injury is highly variable which can make the diagnosis challenging. We present a case of a 59-year-old female who developed drug-induced liver injury after the use of black cohosh products. J Med Cases. 2018;9(9):287-288 doi: https://doi.org/10.14740/jmc3108w

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)0.004
metaresearch head score (Gemma)0.003
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.140
GPT teacher head0.452
Teacher spread0.312 · 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 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

Citations1
Published2018
Admission routes1
Has abstractyes

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