{"id":"W4402693522","doi":"10.2196/62725","title":"Assessing Digital Phenotyping for App Recommendations and Sustained Engagement: Cohort Study","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Smartphone app; Mobile apps; Computer science; Data science; World Wide Web","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":[0.004092182,0.0004722889,0.0004444901,0.0007214256,0.00155299,0.001438704,0.0006678906,0.0008958644,0.003475307],"category_scores_gemma":[0.008273331,0.0005969523,0.001230564,0.0006942439,0.0004634941,0.001392378,0.001291979,0.001812814,0.001281784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005793405,"about_ca_system_score_gemma":0.001063649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008071156,"about_ca_topic_score_gemma":0.01210646,"domain_scores_codex":[0.9982607,0.000408362,0.000174652,0.0004403429,0.0004235677,0.0002923512],"domain_scores_gemma":[0.9960609,0.0005917487,0.001140969,0.00075146,0.0008744157,0.0005804541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002321922,0.001957945,0.980767,0.0001127769,0.0004656981,0.0001514973,0.002269133,0.00004584625,0.0004800861,0.00009222716,0.001540155,0.009795764],"study_design_scores_gemma":[0.0003239344,0.004232858,0.9888313,0.000121935,0.0003144132,0.0003264551,0.002465226,0.0004742527,0.0002384355,0.0001423318,0.002479091,0.00004976145],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966055,0.0002186542,0.0005295564,0.00008669712,0.00002573558,0.0006886591,0.0009084486,0.00001247326,0.0009241522],"genre_scores_gemma":[0.9961934,0.0001683968,0.0008056121,0.0001891631,0.00002461076,0.0009731118,0.0006686738,0.00001473409,0.0009623807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008071156,"threshold_uncertainty_score":0.02164179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1732466991364152,"score_gpt":0.5655237120412159,"score_spread":0.3922770129048007,"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."}}