{"id":"W4410071166","doi":"10.3390/a18050265","title":"Forecasting Cancer Incidence in Canada by Age, Sex, and Region Until 2026 Using Machine Learning Techniques","year":2025,"lang":"en","type":"article","venue":"Algorithms","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Incidence (geometry); Cancer incidence; Cancer; Computer science; Artificial intelligence; Demography; Medicine; Machine learning; Mathematics; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000515144,0.0001563506,0.0002832513,0.000126259,0.0006978257,0.00001144087,0.0001408163,0.0001545732,0.0000425507],"category_scores_gemma":[0.0003655618,0.0001585246,0.00001556376,0.0004629737,0.00005356038,0.0001239392,0.0001801698,0.001030916,0.000001038793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001501718,"about_ca_system_score_gemma":0.001919012,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942256,"about_ca_topic_score_gemma":0.987668,"domain_scores_codex":[0.998011,0.0003615437,0.0005718505,0.0003426444,0.0001786013,0.0005343723],"domain_scores_gemma":[0.9988366,0.0006139804,0.0001901872,0.0001582852,0.0001086742,0.00009229418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001199046,0.000005612042,0.8761281,0.0002211097,0.000006723131,0.00009823967,0.001184608,0.0001035391,0.0002482927,0.00003225633,0.0008698156,0.1210897],"study_design_scores_gemma":[0.0002194572,0.00005609827,0.004537594,0.004597232,0.00002912436,0.00001655122,0.01369775,0.9417318,0.007032954,0.001496495,0.02603457,0.0005504379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884427,0.003665815,0.003322765,0.001848408,0.0007676799,0.001002398,0.00002721556,0.0001114685,0.0008115544],"genre_scores_gemma":[0.9919086,0.0008222262,0.00326556,0.001503683,0.0001460662,0.0001581909,0.00001333191,0.00003110959,0.002151288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9416282,"threshold_uncertainty_score":0.6464446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1291666087284286,"score_gpt":0.4414684905899365,"score_spread":0.3123018818615079,"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."}}