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Record W2495346706 · doi:10.1021/bk-2002-0829.ch013

Development of Micropropagation Technologies for St. John's wort (<i>Hypericum perforaturm L.</i>): Relevance on Application

2002· book-chapter· en· W2495346706 on OpenAlexaffabout
Susan J. Murch, Sheila Chiwocha, Prasoon Kumar Saxena

Bibliographic record

VenueACS symposium series · 2002
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHypericumRelevance (law)MicropropagationHypericum perforatumBotanyTraditional medicineBiologyMedicinePolitical scienceIn vitro

Abstract

fetched live from OpenAlex

Introduction Phytopharmaceuticals are medicinal plant preparations with a long history of anecdotal evidence of efficacy, extensive biochemical characterizations, proven effectiveness in placebo-controlled clinical trials and in some cases, standardization and sale with a Drug Identification Number (DIN). Hypericum perforatum (St. John's wort) is a medicinal plant with a long history of use for the treatment of neurological disorders and depression ( 1, 2, 3, 4 ). In 1998, 7.5 million Americans used St. John's wort for the treatment of neurological disorders and depression ( 5 ) based on a demonstrated efficacy in numerous clinical trials ( 3 ). In 1997, the National Institute of Health (NIH), Office of Alternative Medicines, began a 3-year-study costing $4.3 million to compare the effects of H. perforatum, a placebo and a standard anti-depressive drug in patients suffering from mild depression ( 6 ). Regardless of the outcome of the NIH study, it will be necessary to solve several ongoing problems with preparations

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.013

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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 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

Citations0
Published2002
Admission routes2
Has abstractyes

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