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Record W256048543

St. John's Wort: What You Don't Know Could Hurt You.

2001· article· en· W256048543 on OpenAlexaboutno aff
Elizabeth Manios

Bibliographic record

VenueeScholarship (California Digital Library) · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePharmacologyIndinavirDrugMedical prescriptionHuman immunodeficiency virus (HIV)Traditional medicineIntensive care medicineFamily medicine
DOInot available

Abstract

fetched live from OpenAlex

Despite all the uncertainty surrounding the nature and efficacy of St. John's Wort, its use has skyrocketed in the past decade. This has created great concern among the scientific and healthcare communities, particularly in light of recent research on the numerous potential drug interactions of this herbal supplement. The F.D.A. issued a warning in February 2001 about the possibility of SJW decreasing the effectiveness of numerous prescription drugs, and recent reports show that the concomitant use of SJW lowers the plasma concentrations of some drugs. Decreased serum concentrations of cyclosporin, warfarin, indinavir, Digoxin, oral contraceptives, migraine medications, theophylline, and other HIV-1 protease inhibitors have all been reported. There are two mechanisms of action of SJW that are thought to be responsible for the increased metabolism - and the commensurate decrease in effectiveness - of these drugs: SJW is believed to enhance the activity of Cytochrome P450 enzymes, as well as the activity of the drug efflux transporter P-glycoprotein. Such findings are compelling the F.D.A. to act quickly in requiring herbal manufacturers to begin labeling bottles of SJW with a clear warning about these possible drug interactions. However, much more needs to be done in educating healthcare professionals to actively seek awareness of their patients' use of SJW through routine inquiries about their use of all herbal remedies.

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 categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.007
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.020
GPT teacher head0.233
Teacher spread0.212 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueeScholarship (California Digital Library)Same topicNatural Compound Pharmacology StudiesFrench-language works237,207