{"id":"W2779367538","doi":"10.1093/schbul/sbx178","title":"Mapping Convergent and Divergent Cortical Thinning Patterns in Patients With Deficit and Nondeficit Schizophrenia","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Key Research and Development Program of China; Natural Science Foundation of Beijing Municipality; Fundamental Research Funds for the Central Universities; Government of Jiangsu Province; Six Talent Peaks Project in Jiangsu Province; National Natural Science Foundation of China","keywords":"Schizophrenia (object-oriented programming); Psychology; Neuroscience; Psychosis; Cognition; Cerebral cortex; Thinning; Cortex (anatomy); Audiology; Medicine; Psychiatry; Biology","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":[0.0003328822,0.0003007872,0.0001976486,0.001165879,0.0002356401,0.0003041806,0.0001356223,0.0002194885,0.0006511919],"category_scores_gemma":[0.001081632,0.0001974317,0.0001364441,0.0003587106,0.0003810637,0.0002728821,0.0004119166,0.0001314935,0.0000689581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002222853,"about_ca_system_score_gemma":0.0001580977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002901033,"about_ca_topic_score_gemma":0.007333601,"domain_scores_codex":[0.9998757,0.00002763464,0.00002167838,0.00003094322,0.00002208765,0.00002204666],"domain_scores_gemma":[0.9997227,0.00005603006,0.0001267698,0.00003140545,0.00002259354,0.00004040839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001080412,0.00005297607,0.9537396,0.00004622251,0.000108026,0.001310132,0.001468885,0.0002760626,0.03287331,0.0001175714,0.00007123694,0.008855505],"study_design_scores_gemma":[0.0000118462,0.00006633186,0.9974645,0.000004257904,0.00001615136,0.001136616,0.000383272,0.0001869777,0.0005970614,0.00007228837,0.00005671355,0.000003990017],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998561,0.00002479906,0.00003588472,0.000002856322,3.025782e-7,0.000002036567,0.00002338814,9.073645e-7,0.00005366619],"genre_scores_gemma":[0.9997953,0.00002978636,0.00008585874,0.000003347184,8.475696e-7,0.000002700227,0.00005756153,8.129338e-7,0.00002394415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002901033,"threshold_uncertainty_score":0.005768239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01861396904224372,"score_gpt":0.2240770808787887,"score_spread":0.205463111836545,"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."}}