{"id":"W2780527627","doi":"10.1016/j.puhe.2017.10.016","title":"Google and suicides: what can we learn about the use of internet to prevent suicides?","year":2017,"lang":"en","type":"article","venue":"Public Health","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"The Internet; Suicide prevention; Medical emergency; Poison control; Injury prevention; Occupational safety and health; Human factors and ergonomics; Medicine; Internet privacy; Computer security; World Wide Web; 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":[0.001135086,0.0001522795,0.0004230853,0.00009348593,0.0001743636,0.0003942847,0.000365211,0.00004490358,0.0001184754],"category_scores_gemma":[0.001735269,0.0001065418,0.00006029915,0.00009615943,0.000191748,0.0005315946,0.0003073718,0.0001920984,0.00002964484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001428635,"about_ca_system_score_gemma":0.0006990582,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007220374,"about_ca_topic_score_gemma":0.005719038,"domain_scores_codex":[0.9982345,0.0001971826,0.0004027119,0.0003359057,0.0003330405,0.0004967373],"domain_scores_gemma":[0.9972972,0.0001640892,0.0003272626,0.001316751,0.000148613,0.0007461409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001300872,0.0004668182,0.2548136,0.0008423747,0.0001619604,0.00002127369,0.005384968,0.000004272557,0.00005668448,0.001267945,0.07821021,0.6586398],"study_design_scores_gemma":[0.0005244598,0.0002881233,0.5295709,0.0004932906,0.00001218544,0.00001884099,0.0003977944,0.0001754013,0.00005127316,0.00004928283,0.4683045,0.000114004],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7743123,0.002479422,0.0001765441,0.2208534,0.0003245758,0.001253777,0.0002282554,0.00007158194,0.0003002242],"genre_scores_gemma":[0.9867823,0.002265062,0.0003765515,0.008065392,0.0001129542,0.0000401857,0.00007794509,0.00002868101,0.002250925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6585258,"threshold_uncertainty_score":0.9993906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1367773310598664,"score_gpt":0.3683818486747776,"score_spread":0.2316045176149112,"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."}}