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Record W2314845043 · doi:10.1055/s-0031-1299793

Genetics Meets Environment: Evaluating Gene–Environment Interactions in Neurologic Diseases

2011· article· en· W2314845043 on OpenAlexafffund
Connie Marras, Samuel M. Goldman

Bibliographic record

VenueSeminars in Neurology · 2011
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsDiseaseGene–environment interactionRisk analysis (engineering)MedicineComplex diseaseComputational biologyManagement scienceGeneticsBiologyGeneEngineering

Abstract

fetched live from OpenAlex

The vast majority of disease is due to complex relationships between genetic and environmental factors. Single genetic or environmental causes are rare. Unfortunately, this presents major challenges for assessing disease risk in individuals. Further complicating the situation is the fact that there are many ways in which genetic and environmental determinants can combine to cause disease. This review explores the concepts of gene-environment interaction to provide a basic understanding of the principles of interactions and approaches to studying them. Collaborations between genetics and environmental experts will be crucial to understand the complex relationships.

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 categoriesMeta-epidemiology (narrow)
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 score0.279
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.299
Teacher spread0.224 · 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

Citations12
Published2011
Admission routes2
Has abstractyes

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