{"id":"W3214321237","doi":"","title":"Design of a predictive targeting error simulator for MRI-guided prostate biopsy","year":2010,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Prostate Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Contouring; Computer science; Segmentation; Prostate biopsy; Computer vision; Workflow; Rendering (computer graphics); Artificial intelligence; Simulation; Prostate cancer; Computer graphics (images); 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":[0.0006937776,0.0005253307,0.0004980084,0.0003114669,0.0002771661,0.0007348722,0.00190297,0.0008688172,0.002598895],"category_scores_gemma":[0.002622296,0.0004542204,0.0004635516,0.0002934724,0.0004127721,0.0003926428,0.0006934809,0.0006687106,0.0004205818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008499168,"about_ca_system_score_gemma":0.001444382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004174577,"about_ca_topic_score_gemma":0.002422771,"domain_scores_codex":[0.9997581,0.00005420545,0.00001537405,0.00003168025,0.0001170448,0.00002364297],"domain_scores_gemma":[0.999156,0.0004574109,0.00008890439,0.00006354909,0.0001748483,0.00005934839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008701235,0.0000514506,0.000684549,0.00004373862,0.00001504202,0.00005715373,0.0000627796,0.9836782,0.005886015,0.001635816,0.0003648474,0.00743341],"study_design_scores_gemma":[0.00001175343,0.00001856777,0.00006111891,0.00000254581,0.000003451554,0.00000985108,0.000004608112,0.997026,0.002105787,0.0001959266,0.0005548414,0.000005550811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05398799,0.0000847425,0.9390998,0.0001381327,0.00005776374,0.0002681629,0.000231243,0.003290425,0.00284164],"genre_scores_gemma":[0.6585454,0.0001934446,0.335783,0.0001158639,0.00001822082,0.0006198754,0.0004557214,0.0006977034,0.003570703],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004174577,"threshold_uncertainty_score":0.008694112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01689996418389193,"score_gpt":0.2634525638360699,"score_spread":0.2465525996521779,"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."}}