{"id":"W4382182054","doi":"10.1148/radiol.231066","title":"Reliability of LI-RADS for MRI and CT: Is Excellence Achievable?","year":2023,"lang":"en","type":"letter","venue":"Radiology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Medicine; Excellence; Nuclear medicine; Medical physics; Magnetic resonance imaging; Radiology","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":[0.03990058,0.000374015,0.001671218,0.001319014,0.002125766,0.005297036,0.003323423,0.03144424,0.005087161],"category_scores_gemma":[0.2335363,0.0007141342,0.001015657,0.001162806,0.007092206,0.00699382,0.002557771,0.02930573,0.007178972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006936263,"about_ca_system_score_gemma":0.008937862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005179492,"about_ca_topic_score_gemma":0.009777789,"domain_scores_codex":[0.9716352,0.01052703,0.004761309,0.001656778,0.009341531,0.002078115],"domain_scores_gemma":[0.7537259,0.1668743,0.009783562,0.01033096,0.04506181,0.01422345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001693881,0.0000458275,0.005685705,0.0001556768,0.00003470747,0.00176298,0.0004656359,0.0002623404,0.0003512066,0.02459315,0.8987697,0.06770363],"study_design_scores_gemma":[0.0001077221,0.0001663056,0.006115759,0.001009799,0.00005470124,0.006850312,0.0009861157,0.002380876,0.000632701,0.09918378,0.882382,0.0001299458],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0006875262,0.001197561,0.0004630614,0.9895055,0.00382307,0.00000484595,0.00002210716,0.00002492509,0.004271513],"genre_scores_gemma":[0.06315134,0.00312156,0.004167922,0.8154489,0.1058477,0.00006574567,0.000145996,0.0001769786,0.007873887],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03990058,"threshold_uncertainty_score":0.211017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01529284050044762,"score_gpt":0.2982801387123396,"score_spread":0.282987298211892,"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."}}