{"id":"W2792984344","doi":"10.1017/gheg.2017.18","title":"Design and content validation of a set of SMS to promote seeking of specialized mental health care within the Allillanchu Project","year":2018,"lang":"en","type":"article","venue":"Global Health","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fogarty International Center; National Heart, Lung, and Blood Institute; National Institute of Mental Health; Medical Research Council; World Diabetes Foundation; National Science Foundation; Grand Challenges Canada; Wellcome Trust; Inter-American Institute for Global Change Research; Alliance for Health Policy and Systems Research; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Cancer Institute","keywords":"Short Message Service; Mental health; Appeal; Set (abstract data type); Psychology; Help-seeking; Applied psychology; Content analysis; Nursing; Medicine; Medical education; Computer science; Psychiatry","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":[],"consensus_categories":[],"category_scores_codex":[0.002995594,0.0001917621,0.0007089005,0.00009304004,0.0008171778,0.00000378777,0.0002247322,0.0001203455,0.00002520859],"category_scores_gemma":[0.0001390516,0.0001433456,0.00004936762,0.0006234288,0.0001796752,0.00004617777,0.0001142388,0.000219179,0.000009544069],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006987328,"about_ca_system_score_gemma":0.005643402,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01125126,"about_ca_topic_score_gemma":0.002392564,"domain_scores_codex":[0.9954049,0.001279417,0.001808537,0.00037549,0.0004407449,0.0006909171],"domain_scores_gemma":[0.9965793,0.0001586313,0.001782985,0.0004892239,0.0005691366,0.0004206657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.008657253,0.0008077252,0.06282338,0.03518341,0.0002346523,0.000001025289,0.3887527,0.00008072431,0.0021578,0.08105183,0.1338125,0.2864371],"study_design_scores_gemma":[0.0332415,0.04470738,0.154856,0.01792312,0.000218971,0.00008175682,0.2441038,0.003468735,0.008207703,0.006246791,0.4848669,0.002077331],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8640983,0.004388778,0.02783516,0.03770736,0.001893174,0.05925472,0.002868063,0.0001615269,0.001792986],"genre_scores_gemma":[0.9719554,0.0005714856,0.02037008,0.005291108,0.0003250453,0.001287154,0.0001423801,0.00002550026,0.00003183992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3510544,"threshold_uncertainty_score":0.9999937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1127133683146968,"score_gpt":0.4691208296548834,"score_spread":0.3564074613401866,"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."}}