{"id":"W2603284260","doi":"","title":"PREDICTORS OF WELL-BEING FOR RESIDENTS OF AN EPIDEMIOLOGIC CATCHMENT AREA IN MONTREAL, CANADA","year":2016,"lang":"en","type":"article","venue":"Epidemiology Open Access","topic":"Injury Epidemiology and Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Catchment area; Environmental health; Drainage basin; Environmental science; Geography; Medicine; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004186871,0.0003993564,0.0003648413,0.00108778,0.002808924,0.001375253,0.001627692,0.000719522,0.003037148],"category_scores_gemma":[0.002442141,0.0003157926,0.0007559237,0.002475925,0.000678687,0.00053567,0.00114796,0.001018549,0.0002154084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01812961,"about_ca_system_score_gemma":0.02215727,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9927053,"about_ca_topic_score_gemma":0.9967686,"domain_scores_codex":[0.9992687,0.00007358263,0.00004731067,0.000117086,0.0001508419,0.0003425006],"domain_scores_gemma":[0.9975905,0.00008746947,0.0004221689,0.0000591813,0.0008174917,0.001023166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004651094,0.00004520333,0.9964001,0.00001441196,0.00005346713,0.00005430424,0.0003570361,0.0001111555,0.00007388659,0.00007533259,0.001318585,0.001449918],"study_design_scores_gemma":[0.00000424117,0.00001530798,0.9981773,0.00002095658,0.00001748651,0.00002146818,0.001033881,0.0002283515,0.00001858998,0.0000226792,0.00043216,0.000007519141],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922597,0.0005980051,0.0001099701,0.0008462574,0.00003597697,0.00004686065,0.003527015,0.00001737027,0.002558839],"genre_scores_gemma":[0.9981388,0.0001816173,0.00009035577,0.00006894013,0.00001139037,0.00001129931,0.0008123738,0.000003246772,0.0006818639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01812961,"threshold_uncertainty_score":0.1315402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0834914829329993,"score_gpt":0.4255338996698034,"score_spread":0.3420424167368041,"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."}}