{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007049869,0.000910835,0.00111384,0.009997045,0.0007336054,0.003216396,0.001073287,0.001715795,0.007758477],"category_scores_gemma":[0.02547561,0.0003617142,0.001239657,0.005923331,0.0008547772,0.003924862,0.002409673,0.002128854,0.00247527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001267174,"about_ca_system_score_gemma":0.002631172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00380566,"about_ca_topic_score_gemma":0.008233668,"domain_scores_codex":[0.9955729,0.002673091,0.00034041,0.0003497246,0.0009214417,0.0001424245],"domain_scores_gemma":[0.9642873,0.02803877,0.002393472,0.0008722477,0.00370515,0.0007031782],"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":[0.00002678624,0.00004628746,0.001868322,0.01204671,0.0002379637,0.00003842273,0.0003935614,0.00007462468,0.00009347971,0.00424196,0.02895459,0.9519772],"study_design_scores_gemma":[0.00004370411,0.0001423793,0.01370568,0.06829859,0.0006111623,0.0006267251,0.001607809,0.0002604506,0.0004013432,0.009187416,0.9050325,0.00008211098],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009117937,0.9794998,0.001102443,0.006517803,0.001075863,0.00009923602,0.0005853695,0.00005219585,0.01015538],"genre_scores_gemma":[0.01217482,0.9799218,0.001986878,0.002549523,0.001490864,0.0001935224,0.0005366845,0.0000191091,0.001126681],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.009997045,"threshold_uncertainty_score":0.03728372,"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."}}