{"id":"W2055895811","doi":"10.1186/1476-072x-7-28","title":"Cluster of liver cancer and immigration: A geographic analysis of incidence data for Ontario 1998–2002","year":2008,"lang":"en","type":"article","venue":"International Journal of Health Geographics","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; University of Ottawa","funders":"Public Health Agency; Public Health Agency of Canada","keywords":"Demography; Poisson regression; Liver cancer; Medicine; Public health; Incidence (geometry); Epidemiology; Cancer registry; Health geography; Cancer; Immigration; Environmental health; Gerontology; Geography; Population; Health education; Pathology; Internal medicine; International health","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":[0.001073662,0.0001131239,0.0005874389,0.001043021,0.00007064411,0.000009596624,0.0003885479,0.00006969913,0.00005037493],"category_scores_gemma":[0.0001235907,0.00009599958,0.0002646383,0.0005990902,0.000192481,0.0003101407,0.0000919911,0.0002236066,1.558517e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009396003,"about_ca_system_score_gemma":0.0009079023,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04270933,"about_ca_topic_score_gemma":0.06245934,"domain_scores_codex":[0.9976656,0.00004120133,0.001063352,0.0001856449,0.0008794224,0.0001647603],"domain_scores_gemma":[0.9968544,0.000162936,0.001233018,0.0002554262,0.001362795,0.0001313715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007129783,0.0001051007,0.9897223,0.00008083154,0.002005086,0.00002898225,0.001211602,0.0003025759,0.00002962417,0.00009617984,0.0009558701,0.004748889],"study_design_scores_gemma":[0.00128746,0.0005841063,0.9856711,0.0004863708,0.0008386849,0.0003025837,0.0001583683,0.004586474,0.00002124456,0.00006845273,0.005911115,0.00008403054],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817298,0.01079687,0.004369226,0.002418732,0.0002562999,0.0001994843,0.0002066551,0.000003489964,0.00001942819],"genre_scores_gemma":[0.983189,0.01073336,0.004625774,0.001220684,0.0001245305,0.000004287833,0.00006529628,0.000006594576,0.00003049859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01975001,"threshold_uncertainty_score":0.9636654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1296545054268164,"score_gpt":0.3980055763174357,"score_spread":0.2683510708906193,"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."}}