{"id":"W2166999007","doi":"10.1287/msom.2014.0484","title":"Optimizing Colonoscopy Screening for Colorectal Cancer Prevention and Surveillance","year":2014,"lang":"en","type":"article","venue":"Manufacturing & Service Operations Management","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Colonoscopy; Medicine; Colorectal cancer; Colorectal cancer screening; Cancer screening; Intensive care medicine; Cancer; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002871729,0.0001638504,0.0002127059,0.0001247722,0.0003876431,0.0001182068,0.00006582786,0.00005505533,0.00003706498],"category_scores_gemma":[0.00001272975,0.0001639294,0.00005372091,0.0001258785,0.00001691628,0.0001405932,0.00008239922,0.0000985151,0.000004308753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009457859,"about_ca_system_score_gemma":0.00001660018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003280389,"about_ca_topic_score_gemma":0.002294245,"domain_scores_codex":[0.998982,0.00003919078,0.0002147935,0.0003763525,0.0001548866,0.0002328162],"domain_scores_gemma":[0.9995613,0.00004338598,0.00005152111,0.0001707276,0.00008767306,0.0000853528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01328647,0.0004895922,0.008327507,0.00406506,0.001416218,0.00001263283,0.002711524,0.3009768,0.0077955,0.001743592,0.001062084,0.6581131],"study_design_scores_gemma":[0.009195635,0.005124831,0.2833632,0.0008477962,0.0005919251,0.00004307372,0.001153497,0.5669099,0.09212697,0.0002320654,0.039343,0.001068097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8622811,0.0001218126,0.1329067,0.001865733,0.0002175765,0.001209888,0.000007090376,0.0001590568,0.001231058],"genre_scores_gemma":[0.952616,0.00006901586,0.04498344,0.0006287615,0.0001781421,0.0006550632,0.00005753716,0.00002744145,0.0007845974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6570449,"threshold_uncertainty_score":0.6684847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799130174477164,"score_gpt":0.285303055462734,"score_spread":0.2673117537179623,"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."}}