{"id":"W2769425620","doi":"10.1016/j.cgh.2017.11.036","title":"Simplifying Resect and Discard Strategies for Real-Time Assessment of Diminutive Colorectal Polyps","year":2017,"lang":"en","type":"article","venue":"Clinical Gastroenterology and Hepatology","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Diminutive; Medicine; Hyperplastic Polyp; Narrow-band imaging; Colonoscopy; Confidence interval; Sigmoid function; Colorectal Polyp; Sigmoid colon; Radiology; Endoscopy; Internal medicine; Gastroenterology; General surgery; Colorectal cancer; Rectum; Artificial intelligence; Cancer; Computer science","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":[0.001861169,0.001000375,0.0008474078,0.001893,0.0005293312,0.001679308,0.0009151554,0.0008233955,0.003065666],"category_scores_gemma":[0.008589736,0.0005278232,0.0005982105,0.0005166607,0.0003286059,0.001386533,0.0008820313,0.001065922,0.001523182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002975466,"about_ca_system_score_gemma":0.0009794697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002223429,"about_ca_topic_score_gemma":0.006235031,"domain_scores_codex":[0.999106,0.0002682468,0.0001112336,0.0001471019,0.0002683,0.00009907409],"domain_scores_gemma":[0.9968791,0.001764626,0.0003548231,0.0003043949,0.0004679533,0.0002290351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003368388,0.0003732278,0.09752051,0.0008669791,0.000153938,0.00426182,0.0008252276,0.006542127,0.1977582,0.0008562641,0.005741564,0.6817317],"study_design_scores_gemma":[0.0006031548,0.006107552,0.3983608,0.0009605563,0.001824992,0.05168604,0.003212825,0.2134131,0.262877,0.006503232,0.05387078,0.0005800024],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.494058,0.01159292,0.4774705,0.002541147,0.0007387663,0.0007980605,0.0007510657,0.004075742,0.007973781],"genre_scores_gemma":[0.6007488,0.002688799,0.3916345,0.0008852783,0.0005173893,0.0002252094,0.0005484068,0.000661368,0.002090168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003065666,"threshold_uncertainty_score":0.01025569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.058272106586084,"score_gpt":0.4201189140302564,"score_spread":0.3618468074441724,"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."}}