{"id":"W2099002310","doi":"10.1109/tro.2008.2011415","title":"Needle Insertion Parameter Optimization for Brachytherapy","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Brachytherapy; Imaging phantom; Prostate brachytherapy; Finite element method; Biomedical engineering; Computer science; Algorithm; Physics; Optics; Surgery; Engineering; Radiation therapy; 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":[0.00003508194,0.000128737,0.0001101596,0.00009116112,0.0001238385,0.00004050092,0.00007404284,0.00009107454,0.00002374089],"category_scores_gemma":[0.000002067979,0.0001395007,0.00008395464,0.0001993817,0.00001221917,0.0000945107,9.695478e-8,0.0001107,0.00001691687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004887093,"about_ca_system_score_gemma":0.000008153645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001129843,"about_ca_topic_score_gemma":0.0000022445,"domain_scores_codex":[0.99943,0.000005793128,0.0001798758,0.0001308921,0.00008081309,0.0001726362],"domain_scores_gemma":[0.9996006,0.00007517643,0.00001980129,0.0002008862,0.00004622614,0.00005726264],"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":[0.000008601881,0.00009560918,0.000001009118,0.000006693032,0.00001665617,1.134178e-7,0.00003897673,0.9791582,0.001170019,0.0002941243,0.0002142831,0.01899573],"study_design_scores_gemma":[0.0003415486,0.0001197782,0.00006857735,0.000009764219,0.00003193356,0.00000206125,0.00001070536,0.9922594,0.006109386,0.0006944115,0.000189301,0.0001630631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002502364,0.00002430967,0.9958143,0.000454,0.0003551478,0.0003345645,0.00001509757,0.0003616519,0.0001385948],"genre_scores_gemma":[0.8130463,0.0001102317,0.1862382,0.0003181231,0.0000594575,0.00006740852,0.00001557151,0.00003387589,0.0001108398],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8105439,"threshold_uncertainty_score":0.5688676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01732028416126086,"score_gpt":0.2385731665429268,"score_spread":0.2212528823816659,"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."}}