{"id":"W3158526143","doi":"10.1002/gepi.22383","title":"The Translational Machine: A novel machine‐learning approach to illuminate complex genetic architectures","year":2021,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Waypoint Centre for Mental Health Care; University of Toronto","funders":"","keywords":"Interpretability; Computer science; Artificial intelligence; Machine learning; Pipeline (software); Genetic architecture; Feature (linguistics); Feature selection; Population; Data mining; Quantitative trait locus","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001466558,0.0003922835,0.000601114,0.00007530785,0.00063429,0.00002172793,0.0005422037,0.0003742004,0.00005502173],"category_scores_gemma":[0.003566318,0.0003132321,0.0003087367,0.000256787,0.0003062399,0.000001242905,0.0003026884,0.0004096098,0.00004022645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002520992,"about_ca_system_score_gemma":0.0001886281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000123396,"about_ca_topic_score_gemma":0.0003491323,"domain_scores_codex":[0.9952287,0.00164953,0.0009557037,0.001009142,0.0001642129,0.0009927077],"domain_scores_gemma":[0.9976248,0.0008627541,0.0002795491,0.000737154,0.0002121385,0.00028359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002132603,0.0003476139,0.4123032,0.0000542112,0.0007130011,0.00001120258,0.0004921157,0.4259749,0.08078553,0.001853446,0.008816061,0.06843542],"study_design_scores_gemma":[0.0008339385,0.0002842056,0.7511745,0.000006494579,0.00006911261,0.0004236505,0.00009992051,0.04641958,0.0004299024,0.002877043,0.1968506,0.0005310336],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4547894,0.01431201,0.5177315,0.008315276,0.0004407639,0.0005978043,0.0001531968,0.00005244361,0.00360757],"genre_scores_gemma":[0.7534398,0.0007655298,0.2386286,0.004346127,0.0004689827,0.0001547056,0.0006202094,0.00005852598,0.001517559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3795553,"threshold_uncertainty_score":0.999932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03420251048661162,"score_gpt":0.2902367084708524,"score_spread":0.2560341979842408,"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."}}