{"id":"W2060288087","doi":"10.3748/wjg.v18.i32.4270","title":"Colometer: A real-time quality feedback system for screening colonoscopy","year":2012,"lang":"en","type":"article","venue":"World Journal of Gastroenterology","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Colonoscopy; Medicine; Image quality; Withdrawal time; Visualization; Ambulatory; Colorectal cancer; Computer science; Artificial intelligence; Surgery; Internal medicine; Image (mathematics); Cancer","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":[0.001838901,0.0006057659,0.0005421253,0.0006584868,0.0001755662,0.0006054819,0.0008960903,0.0007261391,0.002658437],"category_scores_gemma":[0.004471856,0.0002396942,0.0002827907,0.0003020127,0.0002606266,0.0005829067,0.0004387847,0.0003319833,0.0006602999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004682973,"about_ca_system_score_gemma":0.0004577887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001027867,"about_ca_topic_score_gemma":0.0009138798,"domain_scores_codex":[0.9988608,0.0002943409,0.00005687734,0.0001966968,0.0005380277,0.00005327409],"domain_scores_gemma":[0.9980214,0.0007408693,0.000330897,0.0001416279,0.0005836833,0.0001816056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.008551229,0.001222667,0.04842155,0.001276427,0.0001953602,0.0005699196,0.0003409737,0.002673707,0.5698374,0.0002720562,0.005141672,0.361497],"study_design_scores_gemma":[0.002793669,0.03546117,0.3091141,0.0002964014,0.0009876809,0.006700478,0.0002466943,0.2155885,0.4052022,0.000277072,0.0228459,0.0004861737],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7096832,0.003188622,0.2642104,0.0005696764,0.0005849812,0.001397781,0.001098219,0.01697876,0.002288264],"genre_scores_gemma":[0.808267,0.0005295093,0.1864194,0.0004905096,0.0001911467,0.0007079156,0.0008709445,0.0002386141,0.00228494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002658437,"threshold_uncertainty_score":0.009725213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02972199724317202,"score_gpt":0.314143211883497,"score_spread":0.284421214640325,"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."}}