{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005267115,0.0003841529,0.0002334043,0.001708211,0.0006407336,0.0007750386,0.0007136494,0.0003012682,0.001297078],"category_scores_gemma":[0.002232477,0.0001463309,0.0006540474,0.002661546,0.000174321,0.0002848043,0.0003254963,0.0004894249,0.0003849613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01617612,"about_ca_system_score_gemma":0.02096324,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9926783,"about_ca_topic_score_gemma":0.9922454,"domain_scores_codex":[0.9997743,0.00002255428,0.00001076037,0.00003788155,0.00008611107,0.00006843226],"domain_scores_gemma":[0.9991663,0.0001012107,0.00006782595,0.0000237911,0.0005657331,0.00007522132],"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":[0.0002168856,0.00008550325,0.5928594,0.0001794418,0.0001825289,0.0002015422,0.0002457928,0.2812464,0.0005341074,0.002864111,0.02524424,0.09614001],"study_design_scores_gemma":[0.00002298044,0.00004599134,0.3083389,0.0001094422,0.0000860307,0.00006674467,0.0006104675,0.6708212,0.0007590189,0.001264948,0.01783462,0.00003953095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8902485,0.003240107,0.01683769,0.005579864,0.0001623944,0.0001185836,0.06858896,0.0009233968,0.01430049],"genre_scores_gemma":[0.9655076,0.001336037,0.007764302,0.0001881401,0.00002678434,0.00002592291,0.02059548,0.00003142091,0.004524222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01617612,"threshold_uncertainty_score":0.1173665,"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."}}