{"id":"W2996627455","doi":"10.2196/15028","title":"Forecasting Mood in Bipolar Disorder From Smartphone Self-assessments: Hierarchical Bayesian Approach","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Innovationsfonden","keywords":"Bipolar disorder; Mood; Bayesian probability; Psychology; Clinical psychology; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002643038,0.0009266982,0.001027685,0.0009443464,0.0003160874,0.0006281009,0.0008941372,0.0007868741,0.001075837],"category_scores_gemma":[0.005881306,0.0006377523,0.001026816,0.0004673292,0.000215191,0.0006217737,0.0004655247,0.001013014,0.000334263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006563847,"about_ca_system_score_gemma":0.0008375344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03737346,"about_ca_topic_score_gemma":0.03628969,"domain_scores_codex":[0.9994078,0.0002757693,0.00003897853,0.0001388586,0.0000758589,0.0000628163],"domain_scores_gemma":[0.9982346,0.001196235,0.0001929993,0.00005717124,0.0002563767,0.00006256211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004907651,0.0002508855,0.02476152,0.0001181214,0.0002494198,0.0001001519,0.0001271399,0.8861741,0.001393372,0.001384156,0.001842669,0.08310755],"study_design_scores_gemma":[0.00001447465,0.00004368369,0.003094643,0.00001409798,0.00002929102,0.000009662269,0.00001008056,0.9957065,0.0001277118,0.0008040342,0.0001349436,0.00001089465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5665191,0.00233794,0.4236183,0.001346262,0.0001621968,0.0002838734,0.001769865,0.0009283351,0.003034224],"genre_scores_gemma":[0.9535643,0.0006208467,0.04256373,0.0001987142,0.0001068547,0.0001457827,0.001307499,0.00003207489,0.001460262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03737346,"threshold_uncertainty_score":0.07431185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0482008850788447,"score_gpt":0.3960958298332389,"score_spread":0.3478949447543942,"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."}}