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Record W2062069722 · doi:10.1002/em.20607

Genetics and women's health issues—The commitment of EMS to women scientists and gender‐associated disease topics

2010· article· en· W2062069722 on OpenAlexfundno aff
Patricia G. Moorman, Olga Kovalchuk, Nina Holland, Gladys Block, Paul R. Andreassen

Bibliographic record

VenueEnvironmental and Molecular Mutagenesis · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of HealthNational Cancer InstituteNational Institute of Environmental Health SciencesCanadian Institutes of Health Research
KeywordsCancer geneticsDiseaseGeneticsBiologyGerontologyMedicineCancerPathology

Abstract

fetched live from OpenAlex

This manuscript presents an overview of a symposium held at the 2009 annual meeting of the Environmental Mutagen Society (EMS) in St. Louis, MO. The symposium was sponsored by the Women in the Environmental Mutagen Society (WEMS) special interest group, and it covered current molecular genetics technologies and their impact on diagnosis and treatment of diseases that primarily or differentially affect women. Four speakers presented groundbreaking new information from such areas as cancer genetics, gene-environment interactions, epigenetics, DNA repair, and molecular epidemiology. Although cancer was a primary focus of the symposium, other health issues such as obesity and cardiovascular disease were addressed. The rapid evolution in genomic technologies discussed in this symposium should provide new tools to explore some of the critical questions raised by the research projects described in this article. This symposium demonstrates that EMS provides a forum for the presentation, discussion, and extension of the data generated by the investigators featured in this article and other researchers engaged in the study of the molecular mechanisms and gene-environment interactions that impact women's health.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.528

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 head0.249
Teacher spread0.242 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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