{"id":"W2125793808","doi":"10.1109/robot.2007.363657","title":"Needle Insertion Point and Orientation Optimization in Non-linear Tissue with Application to Brachytherapy","year":2007,"lang":"en","type":"article","venue":"Proceedings - IEEE International Conference on Robotics and Automation/Proceedings","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Brachytherapy; Prostate brachytherapy; Line (geometry); Point (geometry); Rotation (mathematics); Computer science; Finite element method; Orientation (vector space); Compressibility; Algorithm; Computer vision; Mathematics; Geometry; Physics; Mechanics; Surgery; Engineering; Structural engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002822759,0.0002591538,0.0001972894,0.0004768513,0.0001208471,0.000281646,0.0001560506,0.0001218007,0.00001111644],"category_scores_gemma":[0.00002267665,0.0002638186,0.00001715591,0.000536519,0.00004647306,0.000622045,0.00002569703,0.0001912787,0.00001131386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001416399,"about_ca_system_score_gemma":0.00001432803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002251398,"about_ca_topic_score_gemma":0.00001315367,"domain_scores_codex":[0.9985371,8.852813e-7,0.0004463166,0.0004138055,0.0003402898,0.000261562],"domain_scores_gemma":[0.9990377,0.00002356353,0.0001438203,0.00005416309,0.0005881884,0.0001525649],"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":[0.0002313171,0.0003039699,0.02069004,0.0002893108,0.00009283504,0.000001991876,0.005315858,0.5958661,0.1344488,0.221745,0.0005258664,0.02048889],"study_design_scores_gemma":[0.0006535696,0.0001758664,0.02988318,0.0001582275,0.00001534682,0.00001776549,0.0008073497,0.9590678,0.007455704,0.001267518,0.000142494,0.0003551399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6910882,0.000009206246,0.3017585,0.001762487,0.0001420057,0.0007423096,0.000006174551,0.0002561261,0.004235001],"genre_scores_gemma":[0.95559,0.0000935832,0.04368152,0.0002340432,0.0001401993,0.0001287541,0.00003445352,0.00004379657,0.00005371588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3632018,"threshold_uncertainty_score":0.9999814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01488449357164882,"score_gpt":0.2731453046132353,"score_spread":0.2582608110415864,"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."}}