{"id":"W2314845043","doi":"10.1055/s-0031-1299793","title":"Genetics Meets Environment: Evaluating Gene–Environment Interactions in Neurologic Diseases","year":2011,"lang":"en","type":"article","venue":"Seminars in Neurology","topic":"Genetic Neurodegenerative Diseases","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Disease; Gene–environment interaction; Risk analysis (engineering); Medicine; Complex disease; Computational biology; Management science; Genetics; Biology; Gene; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001703434,0.0003726917,0.0003315972,0.0003565679,0.0001119941,0.00001749537,0.0005868498,0.00008881908,0.0007338583],"category_scores_gemma":[0.0004756161,0.0003999268,0.00009588404,0.0002469215,0.0004078369,0.0001136416,0.0004639917,0.0004792635,0.0002197489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005162708,"about_ca_system_score_gemma":0.00003772819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001794191,"about_ca_topic_score_gemma":0.00001898022,"domain_scores_codex":[0.9957383,0.00129771,0.000588827,0.001296602,0.0003558094,0.0007227918],"domain_scores_gemma":[0.9984432,0.0004667104,0.0001921233,0.000708784,0.000007729634,0.000181444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000472591,0.001518175,0.3270678,0.00001654436,0.000004446676,0.001278162,0.000767345,0.01985182,0.6423416,0.0001839643,0.00008465811,0.006412943],"study_design_scores_gemma":[0.001326823,0.001723155,0.6056747,0.00001318706,0.00005428096,0.0001967384,0.00003397458,0.01004978,0.375963,0.002910677,0.001451467,0.0006021881],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970521,0.0005046245,0.00003883956,0.0004634538,0.0004689416,0.0005970986,0.00004052865,0.00005028577,0.00078413],"genre_scores_gemma":[0.994774,0.001193434,0.0005711253,0.003025664,0.00005104032,0.000242329,0.000006696809,0.00005630115,0.00007937039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.278607,"threshold_uncertainty_score":0.9998453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0740901572050865,"score_gpt":0.2985622142094641,"score_spread":0.2244720570043776,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}