{"id":"W3028343310","doi":"10.1093/schbul/sbaa031.171","title":"S105. DIGITAL BIOMARKERS FOR THE ASSESSMENT OF COGNITIVE, BEHAVIORAL AND FUNCTIONAL OUTCOMES IN INDIVIDUALS WITH SCHIZOPHRENIA","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Workflow; Context (archaeology); Leverage (statistics); Analytics; Data collection; Data science; Machine learning; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002379642,0.000648686,0.0006354074,0.001132442,0.0007105982,0.001588807,0.0004856085,0.0009055932,0.01448543],"category_scores_gemma":[0.007317265,0.0002064461,0.001040717,0.0009079389,0.0002688366,0.0008017045,0.001059131,0.000826149,0.003558052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001013079,"about_ca_system_score_gemma":0.001720928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004173047,"about_ca_topic_score_gemma":0.006465557,"domain_scores_codex":[0.9988973,0.0004115296,0.0001888979,0.0001497777,0.0002435288,0.0001090392],"domain_scores_gemma":[0.996008,0.0009480233,0.0009261508,0.0002255576,0.001372145,0.0005200777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01124591,0.002325407,0.6600685,0.002054057,0.0004468875,0.0005031487,0.001084838,0.00124317,0.005344859,0.00179973,0.0248682,0.2890153],"study_design_scores_gemma":[0.0008140825,0.008537726,0.9430541,0.001072303,0.0005691326,0.0008080092,0.00119772,0.004097198,0.006912811,0.001984835,0.03079937,0.0001527183],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9146196,0.002993144,0.005073312,0.004194221,0.0008760944,0.00397661,0.05049282,0.0005596208,0.01721472],"genre_scores_gemma":[0.9545477,0.001367976,0.01826538,0.0009950938,0.0002640745,0.005019045,0.01161161,0.00004577641,0.007883302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01448543,"threshold_uncertainty_score":0.04845864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04431738029771957,"score_gpt":0.353471795584825,"score_spread":0.3091544152871054,"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."}}