{"id":"W4386069227","doi":"10.1111/acps.13601","title":"Using polygenic risk scores to investigate the evolution of smoking and mental health outcomes in <scp>UK</scp> biobank participants","year":2023,"lang":"en","type":"article","venue":"Acta Psychiatrica Scandinavica","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"College of Medicine, Catholic University of Korea; Compute Canada; Oracle","keywords":"Biobank; Polygenic risk score; Mental health; Psychology; Psychiatry; Medicine; Clinical psychology; Gerontology; Demography; Bioinformatics; Genetics; Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004613519,0.0004672434,0.0002607957,0.001148331,0.0003965616,0.0007592414,0.0004708105,0.0006468488,0.002357449],"category_scores_gemma":[0.009232795,0.0002404816,0.0009852091,0.001562648,0.0004764457,0.0004483887,0.0007237183,0.0006102947,0.0002368458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000388085,"about_ca_system_score_gemma":0.0004091973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01284314,"about_ca_topic_score_gemma":0.01024237,"domain_scores_codex":[0.9977342,0.001516142,0.0001114654,0.0003697223,0.000140891,0.0001274951],"domain_scores_gemma":[0.9934777,0.002558905,0.00258668,0.0008801341,0.0002167216,0.0002798788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001791286,0.00001474573,0.9972579,0.000007670388,0.0002438485,0.00004695601,0.00009891073,0.0002695787,0.0002565013,0.00007856792,0.00007105688,0.001475032],"study_design_scores_gemma":[0.00001098223,0.000117689,0.9971502,0.000006138785,0.00007290437,0.0001231545,0.00006495036,0.002086594,0.0001030812,0.0001224936,0.0001365229,0.000005301794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975041,0.0001081035,0.001569869,0.0000556046,0.000004981905,0.00001952034,0.0005388049,0.00001046038,0.0001886001],"genre_scores_gemma":[0.9978589,0.00004338552,0.001156325,0.00001779429,0.000006731786,0.00002967831,0.0006278325,0.000004775022,0.00025446],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01284314,"threshold_uncertainty_score":0.02553678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03156626094908636,"score_gpt":0.3273221252926146,"score_spread":0.2957558643435282,"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."}}