{"id":"W2053926757","doi":"10.1118/1.4884226","title":"Multiparametric 3D<i>in vivo</i>ultrasound vibroelastography imaging of prostate cancer: Preliminary results","year":2014,"lang":"en","type":"article","venue":"Medical Physics","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; BC Cancer Agency; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Prostate cancer; Cancer; Prostate; Medicine; Cancer detection; Ultrasound; Support vector machine; Prostatectomy; Artificial intelligence; Radiology; Biomedical engineering; Computer science; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006613455,0.0002843631,0.0005970746,0.0003812405,0.00006675585,0.00001756943,0.0002143175,0.0001048806,0.00003855111],"category_scores_gemma":[0.001362891,0.0002428262,0.0002410848,0.001834375,0.0005572159,0.0001354678,0.00005324923,0.0006082964,0.00001111621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004067233,"about_ca_system_score_gemma":0.0001495777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005538582,"about_ca_topic_score_gemma":0.00001191724,"domain_scores_codex":[0.9971792,0.00009716481,0.0006616575,0.0005123607,0.0009932689,0.0005563588],"domain_scores_gemma":[0.9979042,0.0009464886,0.0002175086,0.0004088467,0.0001503027,0.0003725967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002497791,0.002084632,0.8066826,0.0007063109,0.0001822157,0.00003168084,0.00207986,0.0002418336,0.01057251,0.0001435671,0.004240918,0.1705361],"study_design_scores_gemma":[0.06022838,0.007992394,0.6624646,0.01168916,0.001680358,0.0008329774,0.001221452,0.04408156,0.06321491,0.006696242,0.1362328,0.003665166],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9775448,0.001373382,0.0112606,0.001394918,0.0005668279,0.0006571618,0.00009913784,0.0002051657,0.00689803],"genre_scores_gemma":[0.9959544,0.0004342886,0.002323755,0.0007026023,0.0003619572,0.00004657991,0.00003299245,0.0000461838,0.00009726894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.166871,"threshold_uncertainty_score":0.9902166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007122064812588168,"score_gpt":0.2547462785402486,"score_spread":0.2476242137276604,"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."}}