{"id":"W2917789037","doi":"10.1002/nbm.4073","title":"VERDICT MRI validation in fresh and fixed prostate specimens using patient‐specific moulds for histological and MR alignment","year":2019,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Hospital","funders":"Programme Grants for Applied Research; National Health and Medical Research Council; Cancer Research UK; Prostate Cancer UK; Medical Research Council; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; University College London","keywords":"Histology; Ex vivo; Diffusion MRI; Prostatectomy; Verdict; Fixation (population genetics); Prostate; Pathology; Anatomy; Medicine; Biomedical engineering; Chemistry; Materials science; Biology; Magnetic resonance imaging; In vivo; Radiology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001371461,0.0001185211,0.0002559412,0.0001975729,0.00002893782,0.000006127118,0.00003370651,0.00006324893,0.00003196616],"category_scores_gemma":[0.00002804587,0.00009707225,0.00001648569,0.0002122005,0.0001133039,0.00004740583,0.00004354707,0.0001167767,0.00000152411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001409592,"about_ca_system_score_gemma":0.00001738562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001854163,"about_ca_topic_score_gemma":0.000001860578,"domain_scores_codex":[0.9990346,0.00001660698,0.0002891503,0.000337758,0.0001348705,0.000186998],"domain_scores_gemma":[0.9995573,0.0000681057,0.00007622358,0.0001897319,0.00002853269,0.00008009081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007168378,0.0005611538,0.2456668,0.0003333133,0.00001902481,0.00007193119,0.00116278,0.00006200287,0.7237731,0.001879784,0.005195244,0.02055802],"study_design_scores_gemma":[0.03122028,0.007263537,0.3304142,0.002282454,0.0002008347,0.0005676962,0.001723129,0.03198838,0.08248846,0.01214917,0.498385,0.001316862],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920849,0.0005309037,0.002531767,0.002966407,0.000053435,0.001572916,0.00002008033,0.00004333194,0.0001962789],"genre_scores_gemma":[0.9783331,0.0004275688,0.02053968,0.000391392,0.00004335613,0.00008150993,0.00007759018,0.00001663209,0.00008923688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6412846,"threshold_uncertainty_score":0.3958492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06177218552594573,"score_gpt":0.3466322374661471,"score_spread":0.2848600519402014,"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."}}