{"id":"W2967478755","doi":"10.3389/fonc.2019.00807","title":"MRI-Derived Radiomics to Guide Post-operative Management for High-Risk Prostate Cancer","year":2019,"lang":"en","type":"article","venue":"Frontiers in Oncology","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Biochemical recurrence; Prostate cancer; Prostatectomy; Nomogram; breakpoint cluster region; Radiation therapy; Proportional hazards model; Stage (stratigraphy); Lymph node; Univariate analysis; Oncology; Univariate; Prostate; Multivariate analysis; Internal medicine; Cancer; Multivariate statistics; Machine learning; Computer science","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":[0.0004352999,0.0003474823,0.0002447662,0.001164935,0.00009655923,0.0003992883,0.0001899353,0.0002393884,0.0007306183],"category_scores_gemma":[0.001628578,0.00009715727,0.0002068169,0.0003689447,0.000131058,0.0001946644,0.0002147071,0.000204282,0.0003533774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001441541,"about_ca_system_score_gemma":0.0002198869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006430326,"about_ca_topic_score_gemma":0.001497959,"domain_scores_codex":[0.9999036,0.00002911517,0.00001415731,0.00001347057,0.0000259732,0.00001369986],"domain_scores_gemma":[0.9996106,0.0000923535,0.0001456968,0.00002408868,0.0000808685,0.00004628184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001402993,0.0001566153,0.7842991,0.0003718658,0.0001513806,0.0004676662,0.00009789714,0.005573414,0.02663069,0.0001373045,0.00206876,0.1786423],"study_design_scores_gemma":[0.00004172218,0.0007896369,0.9410915,0.00007962388,0.0002447105,0.002396415,0.0001503763,0.03909859,0.01234396,0.0004351636,0.003288579,0.00003975239],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804223,0.003229816,0.01385689,0.0001670597,0.00003806198,0.00007217689,0.0007901596,0.0002558869,0.001167584],"genre_scores_gemma":[0.995118,0.000418004,0.003677387,0.00002237345,0.00002655251,0.00001811114,0.0005205008,0.000009796259,0.0001892677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001164935,"threshold_uncertainty_score":0.002444088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008221948976533477,"score_gpt":0.3065009509092829,"score_spread":0.2982790019327494,"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."}}