{"id":"W1997506516","doi":"10.1016/j.sste.2012.02.009","title":"Spatio-temporal assessment of food safety risks in Canadian food distribution systems using GIS","year":2012,"lang":"en","type":"article","venue":"Spatial and Spatio-temporal Epidemiology","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Agency of Canada; Université de Moncton; Agriculture and Agri-Food Canada","funders":"Defence Research and Development Canada","keywords":"Geographic information system; Scale (ratio); Computer science; Event (particle physics); Visualization; Product (mathematics); Distribution (mathematics); Food safety; Index (typography); Risk analysis (engineering); Environmental resource management; Data science; Data mining; Geography; Cartography; Business; Environmental science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0032039,0.0003672893,0.001457606,0.0002785435,0.0001422956,0.0000106315,0.0001419659,0.0003645211,0.00009147719],"category_scores_gemma":[0.00131594,0.0003371988,0.00015317,0.0003329597,0.0002623868,0.0002061144,0.00009836874,0.0003822567,0.000005849965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007023084,"about_ca_system_score_gemma":0.0008730947,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7210464,"about_ca_topic_score_gemma":0.6114263,"domain_scores_codex":[0.9954999,0.001133924,0.001547775,0.0005226728,0.0002618668,0.001033829],"domain_scores_gemma":[0.9972274,0.0004189299,0.0007357409,0.0005022521,0.000198123,0.000917584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002249496,0.0001446547,0.9928564,0.0002348419,0.0001117194,0.000008975065,0.0000684188,0.0004324516,0.00001667633,0.003740081,0.0002298544,0.00193097],"study_design_scores_gemma":[0.001481583,0.0007286147,0.9482883,0.0001719491,0.00008636856,0.00003488376,0.00006413606,0.03948971,0.00001807783,0.0002321404,0.009106217,0.0002980765],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824171,0.0014958,0.009721397,0.0006275364,0.0007318248,0.001052914,0.00359777,0.00005067448,0.0003049926],"genre_scores_gemma":[0.9875985,0.00008050858,0.001400944,0.0001826275,0.00039369,0.00004812999,0.01025022,0.00003341233,0.0000119943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1096201,"threshold_uncertainty_score":0.999908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08274500168597523,"score_gpt":0.3591589759409353,"score_spread":0.2764139742549601,"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."}}