{"id":"W2912438898","doi":"10.21037/atm.2019.01.13","title":"Patient centered care for prostate cancer—how can artificial intelligence and machine learning help make the right decision for the right patient?","year":2019,"lang":"en","type":"letter","venue":"Annals of Translational Medicine","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Prostate cancer; Medicine; Artificial intelligence; Computer science; Cancer; Internal medicine","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":[0.004182431,0.0005010436,0.0009357634,0.0006988452,0.002405973,0.003061642,0.001600109,0.0244229,0.007079133],"category_scores_gemma":[0.02898464,0.000380609,0.0007730769,0.0006413813,0.003411055,0.006309663,0.001736621,0.03535037,0.004936835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003887829,"about_ca_system_score_gemma":0.004239918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003212144,"about_ca_topic_score_gemma":0.006282774,"domain_scores_codex":[0.9967963,0.001543093,0.000239338,0.0002527334,0.0009020537,0.0002665373],"domain_scores_gemma":[0.9848865,0.01042788,0.000699023,0.0003143144,0.00194978,0.001722479],"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":[0.00005887069,0.00007480975,0.001293751,0.0001674712,0.00002440829,0.001685614,0.0002440867,0.0001926695,0.0001925802,0.01272408,0.9181633,0.06517839],"study_design_scores_gemma":[0.0001234125,0.0001601268,0.001606974,0.001404968,0.00003480972,0.005663363,0.0007077293,0.001916941,0.0001863713,0.08221275,0.9059032,0.0000794251],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001274388,0.001856941,0.0001357951,0.9944613,0.002527448,0.000003501314,0.000009368501,0.000007411038,0.000870766],"genre_scores_gemma":[0.006792562,0.009480202,0.0008222988,0.9371971,0.04262014,0.00002669396,0.00003716212,0.00001925722,0.003004532],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0244229,"threshold_uncertainty_score":0.02820832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06959594155420559,"score_gpt":0.3281430103770026,"score_spread":0.258547068822797,"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."}}