{"id":"W4388768759","doi":"10.1002/cam4.6698","title":"Cancer incidence during the COVID‐19 pandemic by region of residence in Manitoba, Canada: A cancer registry‐based interrupted time series study","year":2023,"lang":"en","type":"article","venue":"Cancer Medicine","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; CancerCare Manitoba","funders":"Canadian Institutes of Health Research; CancerCare Manitoba Foundation; Research Manitoba","keywords":"Incidence (geometry); Demography; Medicine; Pandemic; Cancer registry; Population; Cancer; Context (archaeology); Residence; Breast cancer; Prostate cancer; Lung cancer; Coronavirus disease 2019 (COVID-19); Geography; Environmental health; Oncology; Internal medicine; Disease","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":[0.0007190973,0.0003017763,0.0007710111,0.0002615304,0.0001688911,0.00000770823,0.0003625696,0.0001118476,0.0003990903],"category_scores_gemma":[0.001678777,0.0002095572,0.00004362001,0.001520528,0.000377206,0.0001037549,0.00009169902,0.0005613207,0.000002625918],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004390144,"about_ca_system_score_gemma":0.009263957,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9679653,"about_ca_topic_score_gemma":0.9812999,"domain_scores_codex":[0.9970345,0.0001900794,0.0007435139,0.0005413354,0.0008943378,0.0005961977],"domain_scores_gemma":[0.9976984,0.0004710318,0.0003999241,0.0006920022,0.0002703762,0.0004682325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001323259,0.00003691057,0.9070962,0.001148101,0.00006409661,0.0006794621,0.003469598,0.0002834193,0.005097875,0.000001533162,0.07924326,0.001556287],"study_design_scores_gemma":[0.004866174,0.0005229486,0.9696395,0.004508696,0.0001825273,0.00008410614,0.005930271,0.0003159559,0.0006030969,0.00001701778,0.01305509,0.0002745547],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.900552,0.007336976,0.000008868623,0.09016126,0.0004364714,0.001279256,0.00008488463,0.000104479,0.00003582528],"genre_scores_gemma":[0.9822062,0.004646283,0.000001851324,0.009278757,0.0004395654,0.0005893655,0.00002210158,0.0000403973,0.002775479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08165422,"threshold_uncertainty_score":0.9994318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1313178975070947,"score_gpt":0.4114144208426135,"score_spread":0.2800965233355188,"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."}}