{"id":"W3204319121","doi":"10.1016/j.euroneuro.2021.08.103","title":"W11. GENOME-WIDE ANALYSIS OF THE ANXIETY DISORDER SPECTRUM","year":2021,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Obsolescence; Contradiction; Computer science; Set (abstract data type); Context (archaeology); Representation (politics); Bayesian network; Toolbox; Identification (biology); Data science; Artificial intelligence; Data mining; Epistemology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004407041,0.00134389,0.001138604,0.002120158,0.0008050497,0.001528239,0.002043998,0.001839501,0.06435503],"category_scores_gemma":[0.02083598,0.001178063,0.001923589,0.002743915,0.0004912756,0.0008273654,0.001617901,0.00154929,0.009334995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003270996,"about_ca_system_score_gemma":0.001446442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006552525,"about_ca_topic_score_gemma":0.009643356,"domain_scores_codex":[0.9982318,0.0007740468,0.0001138052,0.0005387845,0.0001932273,0.000148383],"domain_scores_gemma":[0.991397,0.007049418,0.0003309279,0.0006785824,0.0002076758,0.0003365388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00645734,0.0005013849,0.09676156,0.003231094,0.006012985,0.002508159,0.0006397893,0.03370712,0.01813572,0.02130343,0.5849909,0.2257505],"study_design_scores_gemma":[0.009368779,0.001350936,0.181725,0.0010821,0.00607984,0.002676801,0.0004255909,0.294051,0.01699382,0.1214028,0.3643067,0.0005366732],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1068177,0.00211127,0.2192487,0.004731315,0.001094465,0.0007770457,0.6211356,0.03351007,0.01057377],"genre_scores_gemma":[0.3721811,0.001143416,0.2013553,0.002454038,0.0006328159,0.00274403,0.3837612,0.01306985,0.02265835],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06435503,"threshold_uncertainty_score":0.215289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01438539243579984,"score_gpt":0.2603353981604303,"score_spread":0.2459500057246305,"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."}}