{"id":"W4391873649","doi":"10.1093/jcag/gwad061.096","title":"A96 A QUALITY ASSESSMENT STUDY TO DETERMINE IF TISSUE ACQUISTION AND SPECIMEN HANDLING IMPACT THE DIAGNOSTIC YIELD OF ENDOSCOPIC ULTRASOUND-GUIDED FINE NEEDLE ASPIRATION OF SOLID MASS","year":2024,"lang":"en","type":"article","venue":"Journal of the Canadian Association of Gastroenterology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Endoscopic ultrasound; Yield (engineering); Ultrasound; Fine-needle aspiration; Medicine; Quality (philosophy); Radiology; Materials science; Biopsy; Physics; Composite material","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":[0.01779754,0.0003130166,0.0004719741,0.002379149,0.0006393368,0.001498405,0.0005109743,0.0004190964,0.001929888],"category_scores_gemma":[0.05541751,0.0002857783,0.001434746,0.002909868,0.0006599554,0.001415125,0.0007641016,0.0004079927,0.0003057349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001750132,"about_ca_system_score_gemma":0.001139514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002458873,"about_ca_topic_score_gemma":0.001962102,"domain_scores_codex":[0.9873682,0.004703861,0.002933894,0.0009322247,0.003588099,0.0004737538],"domain_scores_gemma":[0.8905586,0.0415605,0.04231617,0.003682246,0.01930474,0.002577704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001022866,0.0001319188,0.9904128,0.00007535689,0.000130412,0.0000621591,0.0002968265,0.00009546566,0.0002975002,0.0000376661,0.0001257124,0.007311353],"study_design_scores_gemma":[0.00006406313,0.003698795,0.9922881,0.00005419175,0.0001958639,0.0003231421,0.0006778594,0.001324846,0.0006357984,0.00006217727,0.0006557,0.00001957997],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953933,0.0008058391,0.001583372,0.00008954528,0.00002468229,0.0003047379,0.0004710868,0.00002600457,0.001301409],"genre_scores_gemma":[0.9984496,0.00009841761,0.0008022977,0.00003120285,0.00001453652,0.0001275551,0.0003241099,0.000006821555,0.0001454318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01779754,"threshold_uncertainty_score":0.09412348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115874959403516,"score_gpt":0.3451491088502497,"score_spread":0.3239903592562146,"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."}}