{"id":"W3216282190","doi":"10.1002/ijc.33884","title":"Predicted long‐term impact of <scp>COVID</scp> ‐19 pandemic‐related care delays on cancer mortality in Canada","year":2021,"lang":"en","type":"article","venue":"International Journal of Cancer","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":134,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Partnership Against Cancer; McGill University; McGill University Health Centre","funders":"Partenariat Canadien Contre Le Cancer; Compute Canada; Canada Foundation for Innovation; Ministère de l'Économie, de la Science et de l'Innovation - Québec; Canadian Institutes of Health Research; Ministère de la Santé; Ministère de la Santé et des Services sociaux; Cancer Care Ontario","keywords":"Medicine; Pandemic; Cancer; Incidence (geometry); Cancer registry; Lung cancer; Colorectal cancer; Coronavirus disease 2019 (COVID-19); Demography; Disease; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006737152,0.0008138562,0.000514027,0.0005747522,0.001015354,0.001074153,0.001271696,0.0008589788,0.002369128],"category_scores_gemma":[0.002221004,0.0005079648,0.001009541,0.0006400473,0.0006593585,0.0004357446,0.000631085,0.0008426873,0.0001965714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02580197,"about_ca_system_score_gemma":0.02161839,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9647632,"about_ca_topic_score_gemma":0.9304699,"domain_scores_codex":[0.9996167,0.00005577878,0.00001165784,0.00006720497,0.00005228929,0.0001962402],"domain_scores_gemma":[0.9989617,0.0002695787,0.0001426808,0.00003966605,0.0004035509,0.0001828575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005550705,0.00002168805,0.02011049,0.00001743845,0.00004261783,0.00004964098,0.00003408162,0.9761034,0.0002352067,0.001078087,0.001180464,0.001071499],"study_design_scores_gemma":[0.00004546946,0.00005030209,0.0173303,0.00001730588,0.00004372968,0.00002133643,0.0001888503,0.9801738,0.0002828045,0.0005153069,0.001298839,0.00003203405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828279,0.0002221864,0.003408198,0.001084578,0.00003705682,0.00006798188,0.006647755,0.0001043101,0.005600109],"genre_scores_gemma":[0.993946,0.0001413818,0.001295026,0.0001180025,0.000006129999,0.00003805243,0.002306547,0.00001622656,0.002132643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03523684,"threshold_uncertainty_score":0.1872073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.058641473950114,"score_gpt":0.4460827180956057,"score_spread":0.3874412441454917,"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."}}