{"id":"W3111058005","doi":"10.1145/3422824","title":"Using Social Media for Mental Health Surveillance","year":2020,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Mental Health via Writing","field":"Psychology","cited_by":148,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; USable; Social media; Mental health; Suicidal ideation; Data science; Field (mathematics); Big data; Public health surveillance; Artificial intelligence; Public health; World Wide Web; Suicide prevention; Poison control; Data mining; Psychiatry; Medicine; Medical emergency","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008412892,0.0006992935,0.003243075,0.0001758437,0.0009130686,0.00006914661,0.001100443,0.0004383283,0.0001041734],"category_scores_gemma":[0.0008972483,0.0007436217,0.0006209866,0.0006149097,0.00009463465,0.00003779971,0.0006052644,0.0008146323,0.0001914742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000810751,"about_ca_system_score_gemma":0.0006990677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003326783,"about_ca_topic_score_gemma":0.000123183,"domain_scores_codex":[0.9888358,0.006420752,0.00184022,0.001177785,0.0003906502,0.001334845],"domain_scores_gemma":[0.9919272,0.005360329,0.001661548,0.0006446482,0.00007837012,0.0003279019],"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":[0.000006407131,0.00004980397,0.0000971859,0.01055876,0.00014315,0.000009273635,0.001753973,1.764771e-7,4.568071e-8,0.000212053,0.007716835,0.9794523],"study_design_scores_gemma":[0.0007245228,0.00009329433,0.0004239119,0.004332975,0.00005565094,0.00009917123,0.0002836325,0.0001273177,4.023167e-8,0.0000487136,0.9930848,0.0007259407],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003915906,0.9865854,0.002943161,0.0003767459,0.00617429,0.002204392,0.001106687,0.0002753186,0.0002948433],"genre_scores_gemma":[0.0006643287,0.9712596,0.01508833,0.0008463881,0.007764353,0.00009554808,0.003676172,0.0005287625,0.00007655769],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.985368,"threshold_uncertainty_score":0.9995015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.319806696540665,"score_gpt":0.5078342189651404,"score_spread":0.1880275224244753,"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."}}