{"id":"W3086705810","doi":"10.24095/hpcdp.40.9.02","title":"Validation of Canproj for projecting Canadian cancer incidence data","year":2020,"lang":"en","type":"article","venue":"Health Promotion and Chronic Disease Prevention in Canada","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Health Authority; Alberta Health Services; Public Health Agency of Canada","funders":"","keywords":"Cancer incidence; Cancer; Selection (genetic algorithm); Cancer registry; Projection (relational algebra); Incidence (geometry); Computer science; Reliability (semiconductor); Statistics; Medicine; Data mining; Mathematics; Artificial intelligence; Internal medicine; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.02481236,0.002228675,0.0007802411,0.002803121,0.001980474,0.00311284,0.003158213,0.0006947407,0.007387385],"category_scores_gemma":[0.0732769,0.001156146,0.002493653,0.003702569,0.0008406402,0.001284979,0.002495534,0.001903524,0.001860709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009201268,"about_ca_system_score_gemma":0.03390288,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7703286,"about_ca_topic_score_gemma":0.7405092,"domain_scores_codex":[0.9900926,0.004450657,0.0005614302,0.001328908,0.003042002,0.0005242915],"domain_scores_gemma":[0.9619684,0.01534078,0.001408899,0.003284332,0.01731672,0.0006808914],"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":[0.0009343352,0.000209781,0.1709182,0.001179129,0.002050552,0.0002669666,0.0008014484,0.5954658,0.001867178,0.01091071,0.1108736,0.1045223],"study_design_scores_gemma":[0.0002676715,0.0001149428,0.03936846,0.000260711,0.0003042842,0.0001233141,0.0003096941,0.9193071,0.003146711,0.004084568,0.03255054,0.0001620812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3502227,0.001515729,0.4268887,0.003863037,0.0008312901,0.002193896,0.1269543,0.04706541,0.04046496],"genre_scores_gemma":[0.5547923,0.0005813006,0.3584386,0.0005932181,0.0000795255,0.001058585,0.07473265,0.005401338,0.004322614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2296714,"threshold_uncertainty_score":0.462048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2017115586571113,"score_gpt":0.4291529092735073,"score_spread":0.227441350616396,"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."}}