{"id":"W4399839403","doi":"10.1016/j.habitatint.2024.103119","title":"Faith, policy, and suicide: A Machine learning and spatial analysis approach of religious affiliation and suicide rates in Toronto","year":2024,"lang":"en","type":"article","venue":"Habitat International","topic":"Suicide and Self-Harm Studies","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Faith; Suicide rates; Suicide prevention; Sociology; Criminology; Psychology; Poison control; Political science; Medical emergency; Medicine; Theology; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002770307,0.0001381876,0.0002552832,0.0003868192,0.00003993585,0.00005985762,0.00006269619,0.00006738125,0.000129532],"category_scores_gemma":[0.0001514218,0.000126289,0.00005220309,0.0002155865,0.0000864274,0.0001201158,0.00008555689,0.0001296816,0.000003258452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008970265,"about_ca_system_score_gemma":0.00001796855,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04615966,"about_ca_topic_score_gemma":0.02898327,"domain_scores_codex":[0.9989589,0.00008468793,0.0002916615,0.0003416729,0.0001697683,0.0001532391],"domain_scores_gemma":[0.9994128,0.0003469306,0.00006896741,0.00006978471,0.00006012632,0.0000414434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001212176,0.00005369358,0.9796785,0.00003766188,0.0008622293,0.00001691406,0.006093527,0.0000381603,0.000320232,0.006499675,0.000151662,0.006126487],"study_design_scores_gemma":[0.0008712098,0.0001403124,0.9639229,0.00002355376,0.0002102552,0.00004110934,0.003170472,0.02965811,0.00007666605,0.001143932,0.0005348231,0.0002066054],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.969922,0.01801519,0.001164313,0.0006780844,0.0001664848,0.0001355127,0.00004809271,0.00004181038,0.009828498],"genre_scores_gemma":[0.9976283,0.001124624,0.0003833409,0.00006856574,0.0001092675,0.00002702857,0.00008902114,0.00001347357,0.0005564127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02961995,"threshold_uncertainty_score":0.9887353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01862426690380331,"score_gpt":0.3446956334953777,"score_spread":0.3260713665915744,"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."}}