{"id":"W4385987628","doi":"10.32920/23989449","title":"Inverse Kinematics of Concentric Tube Robots in the Presence of Environmental Constraints","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Inverse kinematics; Kinematics; Robot; Concentric; Tube (container); Displacement (psychology); Computer science; Inverse; Control theory (sociology); Robot end effector; Simulation; Physics; Mathematics; Artificial intelligence; Engineering; Mechanical engineering; Geometry; Classical mechanics","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":[0.0004426394,0.0004257776,0.0005092677,0.0002173613,0.0002166289,0.0004353887,0.0005165832,0.0006404342,0.001020769],"category_scores_gemma":[0.0009075009,0.0003550534,0.0004046658,0.0002304057,0.0008387875,0.0005140011,0.0008657529,0.0004356177,0.0002394909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002999807,"about_ca_system_score_gemma":0.0006515236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001589037,"about_ca_topic_score_gemma":0.0009193838,"domain_scores_codex":[0.9996995,0.00008095935,0.0000121594,0.00005860726,0.0001239741,0.00002485292],"domain_scores_gemma":[0.9997002,0.0001339947,0.00007465503,0.0000277121,0.00004999432,0.00001343819],"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":[0.00006990014,0.00001499802,0.0003971466,0.00008641702,0.00001581165,0.0002363032,0.0001688103,0.9397225,0.02334678,0.01351527,0.0002053654,0.02222066],"study_design_scores_gemma":[0.000004675998,0.0000336446,0.0001539145,0.000007169751,0.00000379479,0.00007869623,0.00002617224,0.9925348,0.003725634,0.002628666,0.0007956236,0.000007209685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03653873,0.0001119458,0.9604359,0.0000485958,0.00001432803,0.00001585412,0.00001571572,0.000206835,0.002612205],"genre_scores_gemma":[0.7785041,0.0002159109,0.2161365,0.00002823779,0.00001078685,0.00008957792,0.00006004257,0.00006239964,0.004892435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001589037,"threshold_uncertainty_score":0.00341481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02926430601220897,"score_gpt":0.2399871178892305,"score_spread":0.2107228118770215,"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."}}