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Record W2016158172 · doi:10.1002/em.10131

Treatment and sampling protocols for transgenic mutation assays

2003· review· en· W2016158172 on OpenAlexaff
John A. Heddle, Hans‐Joerg Martus, George R. Douglas

Bibliographic record

VenueEnvironmental and Molecular Mutagenesis · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsHealth CanadaYork University
FundersNational Cancer Institute
KeywordsMutationSampling (signal processing)Mutation frequencyTransgeneBiologyMutantMutagenesisComputational biologySampling timeGeneticsComputer scienceStatisticsGeneMathematics

Abstract

fetched live from OpenAlex

The standard protocol for testing chemicals with the transgenic mutation assays in vivo includes a period of time between treatment and sampling to permit the mutation frequency to reach a maximum. Recent evidence has shown, however, that for some chemicals the mutant frequency can decline substantially during this period, which would reduce the sensitivity of the assay. Here we discuss alternate protocols to maintain the sensitivity of the assay for both types of mutagens and, in particular, propose that treatments should continue until the time of sampling.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.015

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 head0.034
GPT teacher head0.314
Teacher spread0.279 · 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
GenreMethods

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

Citations51
Published2003
Admission routes1
Has abstractyes

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