{"id":"W3196552464","doi":"10.1109/lra.2021.3102946","title":"Multiobjective Trajectory Tracking of a Flexible Tool During Robotic Percutaneous Nephrolithotomy","year":2021,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Kidney Stones and Urolithiasis Treatments","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot end effector; Percutaneous nephrolithotomy; Path (computing); Artificial intelligence; Trajectory; Computer science; Motion planning; Sorting; Computer vision; Robot; Medicine; Percutaneous; Surgery; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005694241,0.0004887613,0.0003536702,0.0003230337,0.0003488613,0.000428669,0.0003666649,0.0007050107,0.000563453],"category_scores_gemma":[0.0009866552,0.0002641973,0.0003564091,0.0001956846,0.00038967,0.0002392777,0.00044461,0.0002872197,0.00007587878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004537252,"about_ca_system_score_gemma":0.0007253088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00657044,"about_ca_topic_score_gemma":0.004849042,"domain_scores_codex":[0.9998577,0.00004283633,0.000005799711,0.00002618173,0.00003664048,0.00003088553],"domain_scores_gemma":[0.9996705,0.0001787221,0.00005535803,0.00001952218,0.00004717895,0.000028602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008360729,0.00002865861,0.0007038699,0.00003039843,0.00001521129,0.00008773132,0.00006298095,0.977545,0.008205688,0.0003478824,0.00006864492,0.01282034],"study_design_scores_gemma":[0.000005858142,0.00007616207,0.0003868847,0.000003209875,0.000003646239,0.00001152697,0.00001789211,0.9976586,0.001600978,0.0001441018,0.00008641057,0.000004787226],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5866329,0.0001789777,0.4099289,0.0001300712,0.00003156641,0.00008588515,0.00003832368,0.0003004452,0.002672785],"genre_scores_gemma":[0.961831,0.00003517605,0.03720272,0.0000148585,0.000002723923,0.00003928778,0.00001884263,0.00001383758,0.0008415404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00657044,"threshold_uncertainty_score":0.01306438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01458543798685735,"score_gpt":0.2568056130092255,"score_spread":0.2422201750223681,"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."}}