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Record W2031385588 · doi:10.3123/jemsge.33.34

Introduction to Epigenetic Toxicology of Chemical Substances

2011· article· en· W2031385588 on OpenAlexfundno aff
Tohru Shibuya, Yukiharu Horiya

Bibliographic record

VenueGenes and Environment · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersInstitute of Genetics
KeywordsEpigeneticsEnvironmental toxicologyBiologySomatic cellMechanism (biology)Gene expressionXenobioticToxicologyGeneticsGeneCell biologyChemistryToxicityBiochemistry

Abstract

fetched live from OpenAlex

Epigenetics (EG) is a highly regulated biochemical mechanism underlying the expression of genes related to development and cellular differentiation that is disrupted by environmental stressors including chemicals and radiation. Studies of these phenomena are known as environmental epigenetics (EEG). Regulation of gene expression by the epigenetic mechanism is deeply involved in the developmental stages of animals and humans. EEG is, therefore, very important in the field of toxicology because it deals with the state of gene expression in all types of somatic and germ cells disrupted by environmental chemicals. We propose here an “Embryo-originated Epigenetic Toxicology Method (EEGT)”. In this method embryonic somatic and germ cells are treated with test substances and various toxicological phenomena in whole bodies are examined. Observations on transgenerational effects are also important in this method. This new method could unite various toxicological phenomena based on EEG.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.030
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.210
Teacher spread0.197 · 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.

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

Citations4
Published2011
Admission routes1
Has abstractyes

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