{"id":"W4283791080","doi":"10.2196/39618","title":"Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review","year":2022,"lang":"en","type":"article","venue":"JMIR Bioinformatics and Biotechnology","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data collection; Data extraction; Novelty; Data science; Wearable computer; Systematic review; Process (computing); Information retrieval; MEDLINE; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005039303,0.0001494915,0.0003397089,0.0003503832,0.0002830439,0.0000402528,0.0001920703,0.00009358994,0.0001136529],"category_scores_gemma":[0.00003218453,0.0001520999,0.00005614312,0.000533834,0.00009856016,0.000189409,0.0004642589,0.0006055417,0.00002373506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001710726,"about_ca_system_score_gemma":0.00005627967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006463075,"about_ca_topic_score_gemma":0.00002622249,"domain_scores_codex":[0.9983009,0.00006607036,0.0008735502,0.0002045203,0.0001238127,0.0004311315],"domain_scores_gemma":[0.9992893,0.00003408162,0.0003847131,0.0002165499,0.000007099394,0.00006820928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003996724,0.0005141583,0.001510756,0.0145777,0.00003900881,0.00001444782,0.00121091,0.00007979904,0.000004049557,0.02183911,0.0001583308,0.9600118],"study_design_scores_gemma":[0.01211531,0.01423214,0.001324525,0.1824787,0.00009383911,0.007083531,0.04951655,0.5526397,0.0001993402,0.006493505,0.1688442,0.004978711],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3383558,0.4309882,0.02706912,0.09427135,0.004783272,0.03062628,0.001287816,0.003328368,0.06928974],"genre_scores_gemma":[0.9896214,0.001358968,0.004692622,0.002798769,0.00002743562,0.0005729957,0.0002342024,0.00005504903,0.0006385721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9550331,"threshold_uncertainty_score":0.6202453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0768237313905145,"score_gpt":0.372408938390437,"score_spread":0.2955852069999225,"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."}}