{"id":"W4408182971","doi":"10.1109/jproc.2025.3542324","title":"Digital Phenotyping and Feature Extraction on Smartphone Data for Depression Detection","year":2024,"lang":"en","type":"article","venue":"Proceedings of the IEEE","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Depression (economics); Feature extraction; Feature (linguistics); Artificial intelligence; Psychology; Data science; Internet privacy","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":[0.0001467407,0.00008312467,0.00007908525,0.00006235881,0.0000912626,0.0001278937,0.0001925041,0.00006892326,0.000005806261],"category_scores_gemma":[0.00007224241,0.00006051383,0.00004817884,0.0001210745,0.00003423194,0.0005905378,0.0000754518,0.0001469396,0.00001558142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003747886,"about_ca_system_score_gemma":0.000005307729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006302423,"about_ca_topic_score_gemma":0.000003441884,"domain_scores_codex":[0.9993332,0.000002225372,0.0001484072,0.0002849668,0.0001006305,0.0001305384],"domain_scores_gemma":[0.9996407,0.000073085,0.00008187671,0.000132576,0.00003826606,0.00003349241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005065835,0.0002145526,0.0004655502,0.0008780151,0.00007802748,4.124587e-7,0.0002614387,5.52032e-7,0.02045156,0.002095297,0.03293506,0.942113],"study_design_scores_gemma":[0.003732779,0.002819946,0.05316804,0.0116715,0.000503652,0.0006785182,0.002672477,0.009509549,0.5709062,0.05010548,0.2929976,0.001234236],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631721,0.0009466762,0.0008558766,0.001893142,0.006831384,0.0009046238,0.0003656668,0.0001748667,0.02485567],"genre_scores_gemma":[0.9948314,0.000002187413,0.00008739568,0.00003938184,0.0001940264,0.00004858031,0.000008062986,0.00001990539,0.004769091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9408787,"threshold_uncertainty_score":0.2467682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04598349180085334,"score_gpt":0.3734550346696959,"score_spread":0.3274715428688426,"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."}}