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Record W3093149853 · doi:10.1002/em.22412

Heritable hazards of smoking: Applying the “clean sheet” framework to further science and policy

2020· article· en· W3093149853 on OpenAlexaff
Abigail P. Bline, Kerry L. Dearfield, David M. DeMarini, Francesco Marchetti, Carole L. Yauk, Jill Escher

Bibliographic record

VenueEnvironmental and Molecular Mutagenesis · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsUniversity of OttawaHealth Canada
FundersNational Institutes of HealthNational Institute of Environmental Health SciencesSilicon Valley Community Foundation
KeywordsHazardGerm cellRegulatory scienceMutagenesisBiologyTobacco smokeEnvironmental healthHuman healthBiotechnologyRisk analysis (engineering)Political scienceEnvironmental planningGeneticsBusinessMedicineGeneMutationEcologyEnvironmental science

Abstract

fetched live from OpenAlex

All the cells in our bodies are derived from the germ cells of our parents, just as our own germ cells become the bodies of our children. The integrity of the genetic information inherited from these germ cells is of paramount importance in establishing the health of each generation and perpetuating our species into the future. There is a large and growing body of evidence strongly suggesting the existence of substances that may threaten this integrity by acting as human germ cell mutagens. However, there generally are no absolute regulatory requirements to test agents for germ cell effects. In addition, the current regulatory testing paradigms do not evaluate the impacts of epigenetically mediated intergenerational effects, and there is no regulatory framework to apply new and emerging tests in regulatory decision making. At the 50th annual meeting of the Environmental Mutagenesis and Genomics Society held in Washington, DC, in September 2019, a workshop took place that examined the heritable effects of hazardous exposures to germ cells, using tobacco smoke as the example hazard. This synopsis provides a summary of areas of concern regarding heritable hazards from tobacco smoke exposures identified at the workshop and the value of the Clean Sheet framework in organizing information to address knowledge and testing gaps.

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 score0.020
Threshold uncertainty score0.446

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 head0.007
GPT teacher head0.232
Teacher spread0.225 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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