{"id":"W2573541171","doi":"10.1101/099770","title":"Genomic and Environmental Contributions to Chronic Diseases in Urban Populations","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; Université de Montréal; University of Toronto; Statistics Canada; Ontario Institute for Cancer Research","funders":"Medical Research Council; Fonds de Recherche du Québec - Santé; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Genomics; Computational biology; Genome; Biology; Evolutionary biology; Principal (computer security); Genetics; Data science; Computer science; Gene","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":[0.0005314298,0.0005120981,0.0004783429,0.0001802413,0.0005404155,0.0001976496,0.0006057409,0.0003182038,0.0003913114],"category_scores_gemma":[0.0002612643,0.0006195498,0.00008987792,0.0001327542,0.0003895085,0.0002647913,0.001794594,0.000683897,0.0005863553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00358506,"about_ca_system_score_gemma":0.000176185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004810128,"about_ca_topic_score_gemma":0.0001058742,"domain_scores_codex":[0.9966109,0.0001898566,0.0005036753,0.001487578,0.0004066725,0.0008013638],"domain_scores_gemma":[0.9974869,0.00005543153,0.0003215232,0.001456363,0.000009392508,0.0006703908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001167388,0.000180087,0.7963088,0.00005153331,0.00002591975,0.00004901865,0.0000276795,0.000979685,0.2019217,0.00009770638,0.0003236459,0.00002259724],"study_design_scores_gemma":[0.0004755907,0.00004044798,0.9884991,0.0001538645,0.00006840899,2.271077e-8,0.00000326937,0.0008028455,0.002741479,0.00001075786,0.006558341,0.0006458957],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931915,0.001091417,0.0008329422,0.0006530742,0.0003552876,0.001599224,0.002162099,0.00008949165,0.00002489613],"genre_scores_gemma":[0.9977286,0.0004070699,0.0007811008,0.0003052761,0.0002597725,0.0004116746,0.000003966464,0.00008957601,0.00001295982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1991802,"threshold_uncertainty_score":0.9996256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360374772086804,"score_gpt":0.2475488607215164,"score_spread":0.2339451130006483,"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."}}