{"id":"W2899564302","doi":"10.1093/geroni/igy023.1951","title":"ELDERLY SUICIDE PREVENTION POLICY IN SOUTH KOREA: EVIDENCE FROM NEWS BIG DATA ANALYSIS","year":2018,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Aging","funders":"","keywords":"Government (linguistics); Social media; Big data; Psychology; Suicide prevention; Depression (economics); Suicidal behavior; Medicine; Poison control; Political science; Environmental health; Computer science","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":[0.0008564309,0.0001390261,0.0002673927,0.00195009,0.0000717201,0.00005100193,0.0003868559,0.00008166383,0.0002206832],"category_scores_gemma":[0.0005701385,0.0001429024,0.00003187726,0.007626141,0.00006431156,0.0003272087,0.0001765114,0.000186534,0.0001176121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008718427,"about_ca_system_score_gemma":0.00006228944,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02959082,"about_ca_topic_score_gemma":0.01952651,"domain_scores_codex":[0.9980826,0.0001646102,0.0007262917,0.0005539966,0.0001843008,0.000288176],"domain_scores_gemma":[0.9985813,0.0002057904,0.000267566,0.0008118324,0.0001163368,0.00001713411],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003516846,0.00004075605,0.945649,0.000003904192,0.0001827678,0.000007324955,0.01378077,0.00001141203,0.0003595194,0.0007526696,0.0003876637,0.03878902],"study_design_scores_gemma":[0.0005379895,0.00004064215,0.9902822,0.00006149986,0.00007741141,5.501575e-7,0.003774157,0.0003030973,0.0001751113,0.004282136,0.0002896541,0.0001754904],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852039,0.000368114,0.01028053,0.00173735,0.0004053905,0.0001583502,0.00002161123,0.00005069553,0.001774042],"genre_scores_gemma":[0.997369,0.00001842077,0.0007079326,0.0006256442,0.0007424346,0.00002833818,0.0001930083,0.0000129133,0.0003023084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04463324,"threshold_uncertainty_score":0.9983646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1860379692669541,"score_gpt":0.4194719906844275,"score_spread":0.2334340214174734,"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."}}