{"id":"W3103897922","doi":"10.1016/j.euroneuro.2020.11.012","title":"Digital phenotyping and the COVID-19 pandemic: Capturing behavioral change in patients with psychiatric disorders","year":2020,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"Hersenstichting; Leids Universitair Medisch Centrum; Universitair Medisch Centrum Groningen; ZonMw; GGZ Drenthe; GGZ Friesland; GGZ inGeest; Universiteit Leiden; Rijksuniversiteit Groningen; Amsterdam University Medical Centers","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Depression (economics); Schizophrenia (object-oriented programming); Major depressive disorder; Bipolar disorder; Medicine; Psychiatry; Telehealth; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Psychology; Telemedicine; Internal medicine; Health care","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":[],"consensus_categories":[],"category_scores_codex":[0.0002253459,0.0002705698,0.0002647704,0.0001398371,0.0001287474,0.00007494853,0.0003794671,0.00004003198,0.0001699473],"category_scores_gemma":[0.00004101352,0.0002065814,0.0000774391,0.0004340716,0.0003719358,0.0002604359,0.0001886474,0.000519014,0.0001937973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005031919,"about_ca_system_score_gemma":0.00001546362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006351236,"about_ca_topic_score_gemma":0.00003585388,"domain_scores_codex":[0.9974713,0.0007422373,0.00049221,0.0006386657,0.0001560309,0.0004995198],"domain_scores_gemma":[0.9989828,0.0001512565,0.0002058187,0.0002186631,0.00001961495,0.0004218499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006687265,0.001202676,0.8777682,0.00008047026,0.00005806226,0.0001220335,0.006249416,0.0000133539,0.000007409722,0.0006220302,0.002033457,0.1051556],"study_design_scores_gemma":[0.02660169,0.001518656,0.9425563,0.00001420166,0.00006783134,0.00003618352,0.0002277305,0.00003906855,1.092122e-7,0.0000823208,0.02848127,0.0003746186],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9753504,0.0003177544,0.00005487648,0.009345837,0.001462676,0.001373417,0.00006399706,0.0002754816,0.01175558],"genre_scores_gemma":[0.9780016,0.00001665412,0.00001479398,0.02143362,0.0002112606,0.00009839374,0.00001957068,0.0001109564,0.0000931636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.104781,"threshold_uncertainty_score":0.8424147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06074174370984261,"score_gpt":0.3647617479920011,"score_spread":0.3040200042821585,"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."}}