{"id":"W4250610482","doi":"10.21203/rs.3.rs-471644/v1","title":"Multivariable Models for Advanced Colorectal Neoplasms in Screen-Eligible Individuals at Low-to-Moderate Risk of Colorectal Cancer: Towards Improving Colonoscopy Prioritization ","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; McMaster University; University of Toronto; Ottawa Hospital","funders":"","keywords":"Colonoscopy; Medicine; Colorectal cancer; Logistic regression; Internal medicine; Population; Prioritization; Cohort; Cancer; Oncology; Environmental health","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":[0.006829189,0.0008995364,0.0009537771,0.001798603,0.0004139858,0.001654367,0.001816575,0.0008050738,0.002841753],"category_scores_gemma":[0.01955096,0.0004967658,0.00230344,0.001361355,0.0002539454,0.0006538894,0.001234698,0.001778773,0.0004608252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358085,"about_ca_system_score_gemma":0.0023835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04400271,"about_ca_topic_score_gemma":0.03762748,"domain_scores_codex":[0.9971339,0.00202499,0.0001185945,0.0003504108,0.0001833786,0.0001886976],"domain_scores_gemma":[0.9893885,0.00805179,0.001041481,0.0003425986,0.0008771273,0.000298443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007903909,0.0005215533,0.4511554,0.0002096683,0.002062063,0.000418321,0.0003802349,0.5037321,0.0007544628,0.002787678,0.005178108,0.03200995],"study_design_scores_gemma":[0.0000550043,0.0001349004,0.02642529,0.00003256927,0.00021857,0.00006873183,0.0001071153,0.9698884,0.0001143179,0.002015859,0.0009135458,0.00002572822],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7943558,0.001263637,0.1914369,0.004645749,0.0001590234,0.0003563627,0.005233923,0.001019226,0.001529304],"genre_scores_gemma":[0.9729121,0.0002679641,0.02297046,0.0002647738,0.00008100551,0.0001414429,0.002198423,0.0000517787,0.00111215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04400271,"threshold_uncertainty_score":0.08749318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03940797075040443,"score_gpt":0.3802197967934677,"score_spread":0.3408118260430633,"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."}}