{"id":"W4407285088","doi":"10.1093/jcag/gwae059.102","title":"A102 NOVICE ENDOSCOPISTS EXPERIENCE AND PERFORMANCE ON A NOVEL PHYSICAL-COMPUTER COLONOSCOPY SIMULATOR","year":2025,"lang":"en","type":"article","venue":"Journal of the Canadian Association of Gastroenterology","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Colonoscopy; Computer science; Simulation; Computer graphics (images); Medicine; Internal medicine; Colorectal cancer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007263598,0.000319385,0.0001936326,0.0005147684,0.0002495124,0.0005545801,0.0002225033,0.0003557771,0.004474085],"category_scores_gemma":[0.004031264,0.0001623228,0.0003173765,0.0001207641,0.0002867242,0.0003448203,0.0009324001,0.0003542376,0.0007225757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003291357,"about_ca_system_score_gemma":0.0002750795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001549649,"about_ca_topic_score_gemma":0.003364391,"domain_scores_codex":[0.9993131,0.0001480524,0.00006126483,0.0001123106,0.0002195376,0.0001458012],"domain_scores_gemma":[0.9975037,0.0005856591,0.0004261361,0.00009689051,0.0004057413,0.0009818355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003529452,0.001051111,0.9531363,0.0001162238,0.00006122743,0.0008470362,0.005180298,0.001098627,0.008567487,0.00003628207,0.001136703,0.02841583],"study_design_scores_gemma":[0.00002027984,0.003147694,0.9855828,0.00003224998,0.0000198074,0.001681231,0.004782236,0.001465301,0.001713671,0.00003309159,0.001487579,0.00003404939],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992238,0.00002906966,0.0001169061,0.00001741706,0.000003122915,0.00001232874,0.00003895635,0.000004967427,0.0005535729],"genre_scores_gemma":[0.9988421,0.00005680466,0.0002875316,0.00004147646,0.00000497093,0.00001216749,0.0001002065,0.000002496975,0.0006522165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004474085,"threshold_uncertainty_score":0.01496726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007403012464328786,"score_gpt":0.2534476095468966,"score_spread":0.2460445970825678,"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."}}