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Record W2343947728 · doi:10.4088/pcc.16l01940

Psychosis Resulting From Herbs Rather Than Nutrients

2016· letter· en· W2343947728 on OpenAlexaff
L. Eugene Arnold, Mary A. Fristad, Barbara Gracious, Jeanette M. Johnstone, Bonnie J. Kaplan, Charles W. Popper, Julia J. Rucklidge

Bibliographic record

VenueThe Primary Care Companion For CNS Disorders · 2016
Typeletter
Languageen
FieldMedicine
TopicMedicinal Plant Extracts Effects
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRubricHarmPsychosisPsychologyProbioticMedicinePsychiatrySocial psychologyBiology

Abstract

fetched live from OpenAlex

Article AbstractBecause this piece does not have an abstract, we have provided for your benefit the first 3 sentences of the full text.To the Editor: The very useful case report by Wong et al illustrates the potential harm of psychosis resulting from concurrent administration of over 50 ingredients, including 18 unregulated herbal agents, 19 digestive enzymes, 6 probiotic strains, and other over-the-counter substances. This is a valuable cautionary message, but the title and abstract lead readers astray. Instead of using specific language to identify the offending agents as herbs, the authors use the general term dietary supplements, an erroneous rubric often used in marketing herbs.

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)0.000
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0100.010
Insufficient payload (model declined to judge)0.0060.002

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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 designCase report
Domainnot available
GenreCommentary

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

Citations3
Published2016
Admission routes1
Has abstractyes

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