{"id":"W4213306506","doi":"10.2196/31006","title":"Predicting Psychotic Relapse in Schizophrenia With Mobile Sensor Data: Routine Cluster Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Schizophrenia research and treatment","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Mental Health; National Institute on Aging","keywords":"Cluster analysis; Mixture model; Computer science; Behavioral pattern; Mobile apps; Schizophrenia (object-oriented programming); Machine learning; 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":[0.001106608,0.0008658078,0.0006251235,0.001950668,0.0003703617,0.0006114799,0.0005831131,0.0005195101,0.0006716842],"category_scores_gemma":[0.003017483,0.0002100272,0.001035534,0.001115516,0.0002662171,0.0004709784,0.0006949685,0.0005014378,0.0002913995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00074635,"about_ca_system_score_gemma":0.0006679393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02003906,"about_ca_topic_score_gemma":0.02221972,"domain_scores_codex":[0.9995354,0.0001356261,0.00004289397,0.0001360918,0.00008105127,0.00006896717],"domain_scores_gemma":[0.998789,0.0005041286,0.0002290858,0.0001329273,0.000255255,0.00008955749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00148497,0.0005253582,0.5634233,0.0003326685,0.0005772083,0.0005401823,0.0007360413,0.2642092,0.01134978,0.001190489,0.003167331,0.1524634],"study_design_scores_gemma":[0.00001634071,0.0002573997,0.1417687,0.00005849596,0.0001035051,0.0001801914,0.0006739978,0.8523362,0.00218558,0.001679368,0.0006848128,0.00005539458],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9274375,0.0004148842,0.06846609,0.0002996355,0.00005069627,0.0001661767,0.002114097,0.0003396199,0.0007112268],"genre_scores_gemma":[0.9807673,0.0001384698,0.0169341,0.00002416219,0.0000164344,0.00006796465,0.001784073,0.00001405497,0.0002533781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02003906,"threshold_uncertainty_score":0.03984481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04952010965165903,"score_gpt":0.3806796008552304,"score_spread":0.3311594912035714,"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."}}