{"id":"W4320064976","doi":"10.14309/01.ajg.0000859688.90886.39","title":"S762 Evaluation of Clinical Variables, Radiological Visual Analog Scoring, and Radiomics Features on MR Enterography for Characterizing Severe Inflammation and Fibrosis in Stricturing Crohn’s Disease","year":2022,"lang":"en","type":"article","venue":"The American Journal of Gastroenterology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Fibrosis; Radiology; Stenosis; Radiomics; Histopathology; Inflammation; Pathology; Internal medicine","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":[0.003379439,0.0004547345,0.000567828,0.001192114,0.0002953697,0.0007906522,0.0002668898,0.0003626691,0.002623635],"category_scores_gemma":[0.003383584,0.0001560902,0.0005109561,0.0006493473,0.000419273,0.0003415792,0.0004030091,0.0002466791,0.0009311194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000157109,"about_ca_system_score_gemma":0.0003851281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003065749,"about_ca_topic_score_gemma":0.0006822265,"domain_scores_codex":[0.9993303,0.0002609633,0.0001132313,0.0001232738,0.0001338273,0.00003854642],"domain_scores_gemma":[0.9974566,0.0007487276,0.0007612651,0.0002894817,0.0004930719,0.0002508437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002272147,0.0001682538,0.9565556,0.0001311267,0.0001282402,0.0002721677,0.0001068064,0.0004360649,0.01148341,0.00006716698,0.0008283213,0.02755074],"study_design_scores_gemma":[0.00009984225,0.001783394,0.9821948,0.00006613073,0.0001717057,0.001903862,0.0001501524,0.004917772,0.006476995,0.0001590499,0.002055039,0.00002132288],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954652,0.0005395706,0.002005785,0.00004547555,0.00001752408,0.00008997104,0.0008535334,0.00003883406,0.0009441526],"genre_scores_gemma":[0.9948891,0.0001385487,0.002983446,0.00003591841,0.00002553955,0.00005420674,0.001556358,0.00001080862,0.0003061873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003379439,"threshold_uncertainty_score":0.01787239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02172764205499678,"score_gpt":0.3390121564913436,"score_spread":0.3172845144363469,"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."}}