{"id":"W3124627721","doi":"10.22215/etd/2020-14324","title":"Real-Time Path Planning for Needle Insertion With Multiple Targets","year":2020,"lang":"en","type":"dissertation","venue":"","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Bevel; Motion planning; Nonholonomic system; Path (computing); Kinematics; Computer science; Planner; Engineering; Artificial intelligence; Robot; Mechanical engineering; Physics; Mobile robot","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":[0.0002675433,0.0006718743,0.0003787302,0.0003830945,0.0002847518,0.0004016841,0.0005395632,0.0005326751,0.004823249],"category_scores_gemma":[0.0008815461,0.0003972165,0.0004917439,0.0004077325,0.0002787083,0.0004656867,0.0007542127,0.0007055001,0.001066953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004391709,"about_ca_system_score_gemma":0.0008231939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003958757,"about_ca_topic_score_gemma":0.004587584,"domain_scores_codex":[0.999724,0.00004187867,0.000009752988,0.00007029697,0.0001252427,0.00002878691],"domain_scores_gemma":[0.9997529,0.0001291943,0.00002459528,0.00002252957,0.00005164871,0.00001919849],"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":[0.0002564184,0.00006023523,0.0003849303,0.000194859,0.00003793312,0.0002250901,0.000205202,0.604266,0.03475333,0.006344607,0.00410042,0.349171],"study_design_scores_gemma":[0.00001609033,0.00007736014,0.000246755,0.00001356083,0.0000112209,0.0001053626,0.00002435519,0.9844525,0.008252759,0.002742882,0.004040773,0.0000164527],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0108097,0.0004169976,0.9836713,0.00007211105,0.000051404,0.00005956545,0.00006434973,0.00118795,0.003666573],"genre_scores_gemma":[0.3639511,0.0006911711,0.6257031,0.00004761364,0.00003003424,0.0001698193,0.0003347325,0.0003005727,0.008771894],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004823249,"threshold_uncertainty_score":0.01613533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01082744993529803,"score_gpt":0.2306181233191003,"score_spread":0.2197906733838023,"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."}}