{"id":"W2160353853","doi":"10.1148/radiol.12102294","title":"Prostate: Registration of Digital Histopathologic Images to in Vivo MR Images Acquired by Using Endorectal Receive Coil","year":2012,"lang":"en","type":"article","venue":"Radiology","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Lawson Health Research Institute; Western University","funders":"","keywords":"Fiducial marker; Medicine; Magnetic resonance imaging; Image registration; Prostate; Nuclear medicine; Radiology; Artificial intelligence; Computer science; Cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001561067,0.0001401526,0.0003705611,0.0000886179,0.00002370603,0.00000753895,0.00004601749,0.00008186455,0.00004740337],"category_scores_gemma":[0.0001558173,0.0001157409,0.00005063072,0.0001144453,0.0001428099,0.0001374514,0.00002468795,0.00005665393,0.00000674464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003363091,"about_ca_system_score_gemma":0.00005354952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001003422,"about_ca_topic_score_gemma":0.000005518241,"domain_scores_codex":[0.9990152,0.00005731701,0.0002939087,0.0002286909,0.00008526099,0.0003196099],"domain_scores_gemma":[0.9994692,0.00007753685,0.0001273909,0.0001657051,0.00005113904,0.0001090404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004843005,0.0004841247,0.4713098,0.00005669511,0.00003690542,0.0001118204,0.0009193654,0.00001067934,0.5033649,0.00004091445,0.0174292,0.005751377],"study_design_scores_gemma":[0.004319483,0.003460148,0.1609441,0.0001970789,0.000163417,0.001335363,0.0005339135,0.00002707099,0.8197528,0.0001569111,0.008693859,0.0004158621],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932377,0.003368919,0.00005247775,0.0006925634,0.0001851356,0.0005171414,0.0002269288,0.00002454699,0.001694579],"genre_scores_gemma":[0.9982272,0.0003079639,0.0006374086,0.0001379447,0.00008139751,0.00007796368,0.00009289157,0.00001446728,0.0004227974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3163879,"threshold_uncertainty_score":0.4719775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02039862889413888,"score_gpt":0.2852656887598095,"score_spread":0.2648670598656706,"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."}}