{"id":"W2964431901","doi":"10.1186/s12963-019-0193-9","title":"Regional variation of premature mortality in Ontario, Canada: a spatial analysis","year":2019,"lang":"en","type":"article","venue":"Population Health Metrics","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Public Health Ontario; University of Toronto","funders":"Canadian Institutes of Health Research; Canada Excellence Research Chairs, Government of Canada; Ontario Ministry of Health and Long-Term Care; Institute for Clinical Evaluative Sciences","keywords":"Demography; Medicine; Population; Public health; Population health; Mortality rate; Epidemiology; Environmental health; Surgery","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006070707,0.00008968756,0.0004957192,0.0006339463,0.00002022209,0.00000403119,0.00005607499,0.00006484344,0.0002366394],"category_scores_gemma":[0.0002980088,0.00008976631,0.0000734693,0.002355913,0.00000571698,0.00006895903,0.00001533262,0.0001670654,0.000002175671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001520435,"about_ca_system_score_gemma":0.002250761,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9967294,"about_ca_topic_score_gemma":0.9978758,"domain_scores_codex":[0.9981681,0.0001208399,0.0006116029,0.0002418374,0.0006842389,0.0001733686],"domain_scores_gemma":[0.9988027,0.00009209573,0.0004307779,0.0003740407,0.0001603169,0.0001401063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006692963,0.00007522469,0.9968674,0.0001663245,0.00009810845,0.00000175292,0.0000932875,0.001667008,0.000002267046,0.0001379012,0.0002772135,0.0005466093],"study_design_scores_gemma":[0.0005398897,0.00003787341,0.9902193,0.0000289289,0.0001024666,6.788613e-7,0.000008668912,0.008285396,8.70605e-7,0.00004308722,0.0006695383,0.00006330862],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977199,0.0001397255,0.00076433,0.0004572126,0.0001569422,0.000533561,0.00009635268,0.00001559369,0.0001163542],"genre_scores_gemma":[0.9958884,0.000009999923,0.0008545448,0.0005764282,0.00002608038,0.000005822275,0.002526395,0.000006986174,0.0001054093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00664808,"threshold_uncertainty_score":0.3992754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03981862156918798,"score_gpt":0.3227579253105676,"score_spread":0.2829393037413796,"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."}}