{"id":"W2559525789","doi":"10.1007/s10597-016-0072-9","title":"Mobile Based mhGAP-IG Depression Screening in Kenya","year":2016,"lang":"en","type":"article","venue":"Community Mental Health Journal","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Grand Challenges Canada; World Health Organization","keywords":"Mental health; Public health; Depression (economics); Medicine; Psychiatry; Intervention (counseling); Major depressive disorder; Environmental health; Gerontology; Nursing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007440442,0.0002715103,0.0005330675,0.0004198244,0.007341192,0.00001576939,0.0006792878,0.000252131,0.001019612],"category_scores_gemma":[0.0002386656,0.0001979131,0.0001036787,0.0004382785,0.0001177434,0.0002877982,0.0002721972,0.003714621,0.0002618934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001301953,"about_ca_system_score_gemma":0.002239577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001471514,"about_ca_topic_score_gemma":0.001799896,"domain_scores_codex":[0.9900627,0.005841911,0.00179288,0.0002533776,0.0004683451,0.001580829],"domain_scores_gemma":[0.9950701,0.001448055,0.0009371153,0.0008596017,0.0001725727,0.001512547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006262056,0.0008139565,0.3738992,0.0007632546,0.000009441279,0.000005366799,0.004205561,0.00001471766,0.0002514292,0.0003484533,0.05443446,0.564628],"study_design_scores_gemma":[0.01243117,0.0009748166,0.2185147,0.006788436,0.000007301296,0.0000732019,0.00837008,0.0004979782,0.00007212912,0.00103448,0.7508084,0.0004273963],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8964947,0.008237612,0.03438718,0.03330054,0.003606389,0.01371489,0.0003776563,0.0004829241,0.009398133],"genre_scores_gemma":[0.9756534,0.003633775,0.003855877,0.01324371,0.0003734234,0.002438141,0.00007017024,0.00006302519,0.0006684444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6963739,"threshold_uncertainty_score":0.9998936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0987163506518943,"score_gpt":0.4666489433793904,"score_spread":0.3679325927274961,"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."}}