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Antitumor Agents: Taxol and Taxanes-Production by Yew Cell Culture

2006· reference-entry· en· W1918344113 on OpenAlexaff
Arthur Germano Fett‐Neto, Hideki Aoyagi, Hideo Tanaka, Frank DiCosmo

Bibliographic record

VenueEncyclopedia of Molecular Cell Biology and Molecular Medicine · 2006
Typereference-entry
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTaxusSemisynthesisBiologyPaclitaxelBotanyCancerBiochemistryGenetics

Abstract

fetched live from OpenAlex

Taxol™ is an anticancer drug increasingly used for the approved treatment of various cancer types, including ovarian, breast, lung, head and neck, bladder and cervix, melanomas, and AIDS-related Karposi's sarcoma. The supply of this compound is limited because of expanding demand and the fact that the only commercial source is the biomass of Taxus species. Yew trees grow relatively slowly, contain low and variable amounts of Taxol™, and in many cases are located in protected, environmentally sensitive areas. The bulk of current Taxol™ production derives from semisynthesis starting from 10-deacetyl baccatin III, a precursor obtained from yew needles. Cell culture of yew species is a viable alternate source of Taxol™ and related taxanes, which can be used for production and/or semisynthesis of the drug. Cell cultures are readily renewable and yield relatively homogeneous, easily manipulated systems for biosynthetic studies on Taxol™, amenable to large-scale commercial production.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.006

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 head0.008
GPT teacher head0.275
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2006
Admission routes1
Has abstractyes

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