{"id":"W2324172070","doi":"10.1016/j.gie.2014.02.307","title":"Su1563 Automated Stool Detection for Assessment of Bowel Preparation Quality in Screening Colonoscopy","year":2014,"lang":"en","type":"article","venue":"Gastrointestinal Endoscopy","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Colonoscopy; Bowel preparation; Colorectal cancer screening; Colorectal cancer; Quality assessment; Gastroenterology; Internal medicine; Quality (philosophy); Medical physics; Cancer; External quality assessment; Pathology","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":[0.0007163925,0.00048924,0.0007937896,0.001043921,0.0002595361,0.0007243752,0.0004220643,0.0009764922,0.002367983],"category_scores_gemma":[0.001583327,0.0002650147,0.0006019389,0.0008032125,0.0001540282,0.0002776699,0.0002853272,0.0005117823,0.0008360713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003506162,"about_ca_system_score_gemma":0.0002979746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001489025,"about_ca_topic_score_gemma":0.003367424,"domain_scores_codex":[0.9993814,0.000151778,0.0000548475,0.0001154846,0.0002382055,0.00005837366],"domain_scores_gemma":[0.9992803,0.0002330004,0.0001699184,0.0000456004,0.0001951531,0.0000762005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01123955,0.0006274227,0.4693387,0.0005113077,0.0006501667,0.0008074804,0.0001093907,0.001564479,0.3097295,0.0002376929,0.004746998,0.2004374],"study_design_scores_gemma":[0.000427768,0.004617252,0.6399743,0.0001156741,0.0006644434,0.004581172,0.0001565548,0.05555503,0.2865126,0.0002880679,0.006953118,0.0001540619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875883,0.003368845,0.004514367,0.0002098507,0.0001245681,0.00006439598,0.001552479,0.0004421726,0.002135007],"genre_scores_gemma":[0.9845888,0.0006557545,0.01064469,0.0001810352,0.00003798266,0.00004999407,0.001614331,0.00005330181,0.002174057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002367983,"threshold_uncertainty_score":0.007921636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0346184495268792,"score_gpt":0.3762625407608123,"score_spread":0.3416440912339331,"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."}}