{"id":"W4319333946","doi":"10.1111/den.14531","title":"Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement","year":2023,"lang":"en","type":"review","venue":"Digestive Endoscopy","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal; University of British Columbia","funders":"Olympus; Ipsen; Mitsubishi Tanabe Pharma Corporation; Norgine; Otsuka Pharmaceutical; Braintree Laboratories; Ironwood Pharmaceuticals, Incorporated; Pfizer; Kyorin Pharmaceutical; EA Pharma Co., Ltd.; Japan Society for the Promotion of Science; Boston Scientific Corporation; European Commission","keywords":"Medicine; Colonoscopy; Position statement; Health care; Colorectal cancer; Medical physics; Family 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003337547,0.0003214554,0.00107906,0.001243619,0.00003924904,0.00002123866,0.00007104106,0.0001550352,0.0000390482],"category_scores_gemma":[0.000132354,0.0003224268,0.00006922879,0.001744521,0.00005486704,0.0001140179,0.00006698884,0.0003217582,0.00001430566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006374196,"about_ca_system_score_gemma":0.0003384062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000624118,"about_ca_topic_score_gemma":0.004389662,"domain_scores_codex":[0.9977384,0.0001724092,0.001002069,0.0005351609,0.0002727038,0.0002792829],"domain_scores_gemma":[0.9988824,0.0002972848,0.0004458414,0.0001689605,0.0001297575,0.0000757887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0004468623,0.00009489762,0.00159132,0.005876591,0.00006128896,0.00001738201,0.0006917939,0.00002087435,0.00001659633,0.000711184,0.000004209812,0.990467],"study_design_scores_gemma":[0.01192925,0.05619724,0.2366567,0.4955995,0.007450533,0.0003439952,0.02675835,0.001101856,0.06417223,0.00308957,0.08948302,0.007217731],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01045438,0.9866962,0.0001851092,0.0001412761,0.0002695188,0.002019655,0.00009273167,0.00007478063,0.00006627923],"genre_scores_gemma":[0.01138766,0.987244,0.0005540169,0.000008601061,0.0000806579,0.0002754553,0.0003781275,0.00006158597,0.000009863635],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9832492,"threshold_uncertainty_score":0.9999228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.129175005919323,"score_gpt":0.3961700548162078,"score_spread":0.2669950488968849,"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."}}