{"id":"W2755180333","doi":"10.1016/j.jcct.2017.09.008","title":"Structured reporting platform improves CAD-RADS assessment","year":2017,"lang":"en","type":"article","venue":"Journal of cardiovascular computed tomography","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Paul's Hospital","funders":"National Research, Development and Innovation Office; Nemzeti Kutatási, Fejlesztési és Innovaciós Alap; GE Healthcare","keywords":"Medicine; CAD; Coronary artery disease; Consistency (knowledge bases); Medical physics; Radiology; Stenosis; Standardization; Artificial intelligence; Computer science; Internal medicine; Engineering drawing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001901909,0.0002568762,0.00130673,0.0004623187,0.0003569832,0.0002824358,0.000306439,0.0001335276,0.000003723715],"category_scores_gemma":[0.000961463,0.000207283,0.004355203,0.0001936393,0.0001507122,0.0003023652,0.0001246513,0.0006966237,0.000001034621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000761609,"about_ca_system_score_gemma":0.0002884233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000444434,"about_ca_topic_score_gemma":7.648691e-7,"domain_scores_codex":[0.9968853,0.0000539139,0.001275414,0.0002593086,0.001187244,0.0003388374],"domain_scores_gemma":[0.9950333,0.00006899607,0.002373242,0.001318109,0.0008818276,0.0003244992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003006587,0.0003473624,0.646695,0.0005623896,0.04045486,0.01057652,0.0003237852,0.003971118,0.003433487,0.0003240989,0.00677892,0.2862318],"study_design_scores_gemma":[0.004299399,0.0002894687,0.9619097,0.0004702345,0.003182042,0.006142662,0.00006915956,0.0005282504,0.001606186,0.0003491953,0.02089075,0.0002629739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9238127,0.02430045,0.04036264,0.000574483,0.004657342,0.0004507861,0.000009540114,0.00009739362,0.005734592],"genre_scores_gemma":[0.9811234,0.0001926645,0.01691064,0.0001072216,0.001611987,0.000002157625,0.000005880933,0.00003591366,0.00001010542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3152147,"threshold_uncertainty_score":0.8452757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02052925621960106,"score_gpt":0.2967384922093636,"score_spread":0.2762092359897625,"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."}}