{"id":"W2037583987","doi":"10.1002/cncr.25653","title":"A comparison of charlson and elixhauser comorbidity measures to predict colorectal cancer survival using administrative health data","year":2010,"lang":"en","type":"article","venue":"Cancer","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":170,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Comorbidity; Concordance; Cancer; Internal medicine; Statistic; Stage (stratigraphy); Poisson regression; Weight loss; Colorectal cancer; Body mass index; Obesity; Population; Statistics; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003763782,0.0001576607,0.0005129081,0.00007700422,0.0001160254,0.00001785001,0.0001284045,0.00009452052,0.0001056369],"category_scores_gemma":[0.0001286326,0.0001425687,0.00003376565,0.0002411063,0.0001218704,0.00009502383,0.000111258,0.0003699944,8.860328e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000144922,"about_ca_system_score_gemma":0.0008388332,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.009663762,"about_ca_topic_score_gemma":0.03967543,"domain_scores_codex":[0.9986488,0.00004826362,0.0003037755,0.0004081793,0.000346707,0.0002442432],"domain_scores_gemma":[0.9989567,0.00005460361,0.0001801399,0.0003333579,0.0001911009,0.0002841033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006870629,0.0002014325,0.7834084,0.0002932637,0.0002097315,0.000003298533,0.002728872,0.00007996897,0.1247755,0.00002132194,0.004509387,0.07689816],"study_design_scores_gemma":[0.002069305,0.003620733,0.8690448,0.0005821829,0.0002182566,0.00003048642,0.0006886303,0.01189374,0.09801131,0.000008761199,0.0134836,0.0003482013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945361,0.001688921,0.000463659,0.0009617331,0.001144558,0.0005221514,0.000457714,0.00005155352,0.0001735852],"genre_scores_gemma":[0.9984674,0.000182732,0.0005231477,0.0001751841,0.0005131,0.00005098861,0.00002905491,0.00002090207,0.00003751329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08563636,"threshold_uncertainty_score":0.996931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3220617455905329,"score_gpt":0.4867171855359496,"score_spread":0.1646554399454166,"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."}}