{"id":"W4415396750","doi":"10.14309/ajg.0000000000003812","title":"Impact of Artificial Intelligence Use on Endoscopist Optical Diagnosis of Sessile Serrated Lesions, Traditional Serrated Adenomas, and Advanced Conventional Adenomas","year":2025,"lang":"en","type":"article","venue":"The American Journal of Gastroenterology","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"MEDLINE; Single use; Adenoma; Computer-aided diagnosis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003314624,0.0003187535,0.0003068337,0.000807037,0.0002367158,0.0009603602,0.0002481567,0.0003768124,0.001125596],"category_scores_gemma":[0.01502337,0.0001705832,0.0004494641,0.0004084551,0.0003956697,0.0004777154,0.0004792858,0.0003777207,0.0001977878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004468532,"about_ca_system_score_gemma":0.0003913454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002119407,"about_ca_topic_score_gemma":0.003098907,"domain_scores_codex":[0.997367,0.00127989,0.0002117677,0.0003762885,0.0006380871,0.0001270386],"domain_scores_gemma":[0.9849995,0.01039624,0.002624761,0.0005780435,0.0008839743,0.0005176066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002676555,0.0001744164,0.9710645,0.00007353594,0.0003271779,0.00009143662,0.0001151745,0.0003832848,0.001122019,0.00002714185,0.0002376558,0.02370706],"study_design_scores_gemma":[0.00005813675,0.001839657,0.9919735,0.00003296004,0.0002591986,0.0005313901,0.0001267965,0.003023901,0.001524762,0.0000504601,0.00056635,0.00001294655],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976121,0.000589579,0.0002999526,0.000120795,0.00001208317,0.00001869243,0.0001224278,0.00001699336,0.001207308],"genre_scores_gemma":[0.9991717,0.00009714457,0.0003751779,0.00005116358,0.00001264224,0.000006989695,0.0001321376,0.000002780176,0.000150304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003314624,"threshold_uncertainty_score":0.01752967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03732629458780213,"score_gpt":0.3216163638066487,"score_spread":0.2842900692188466,"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."}}