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Record W4402729372 · doi:10.17952/37eps.2024.p1084

Synthesis of Aza-Amanitins to Enhance Cytotoxicity for Targeted Cancer Therapeutics

2024· article· en· W4402729372 on OpenAlexaff
Kayla C. Newell, F. Cruz Custodinho, Juliette Froelich, Katherine Bessai, Cassandra M. Sgarbi, David M. Perrin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacological Effects of Natural Compounds
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCytotoxicityCancerCancer researchComputer scienceChemistryMedicineInternal medicineBiochemistryIn vitro

Abstract

fetched live from OpenAlex

The development of cancer therapies in which cancer-specific agents can be used to deliver a cytotoxic agent to cancer cells is at the forefront of drug research 1,2 There has been more research into antibody drug conjugates (ADCs) as a method of targeted cancer therapy 3 -amanitin, a highly selective inhibitor of RNA polymerase II (Pol II), produced by the death-cap mushroom targets tumors in a cellcycle independent manner 4 -amanitin as a drug payload for ADCs enhances therapeutic potential and specificity AbstractFigure 1.General reaction scheme to access aza-amanitin analogs.

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)0.001
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.122
GPT teacher head0.495
Teacher spread0.373 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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