{"id":"W2022870287","doi":"10.1109/acc.2010.5531362","title":"Accelerated needle steering using partitioned value iteration","year":2010,"lang":"en","type":"article","venue":"","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Solver; Workspace; Computer science; Markov decision process; Motion planning; Curse of dimensionality; Mathematical optimization; Path (computing); Set (abstract data type); Algorithm; Robot; Markov process; Artificial intelligence; Mathematics","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":[0.00003235008,0.00005983186,0.00004832408,0.00003276105,0.00006845518,0.0000734054,0.00004441217,0.00004211219,0.0002034839],"category_scores_gemma":[0.000005148504,0.00006152779,0.00001600699,0.000130054,0.000006849108,0.0001149815,0.000007874074,0.00009101925,0.00004629707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001142228,"about_ca_system_score_gemma":0.000005420143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001584946,"about_ca_topic_score_gemma":0.0000114601,"domain_scores_codex":[0.9996797,0.000002004863,0.0001018554,0.00006761408,0.0000474305,0.0001014355],"domain_scores_gemma":[0.9997953,0.00001188767,0.000008159761,0.0001193921,0.00002622694,0.00003904601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[2.589567e-7,0.000008320903,0.0002465864,0.000005219786,0.000006420054,2.135556e-7,0.00005421706,0.383051,0.6057982,0.01026979,0.0001649759,0.0003947481],"study_design_scores_gemma":[0.00007933116,0.000002200218,0.001290754,0.000002932106,0.00000545274,0.000002754992,0.00001505757,0.9330495,0.06382468,0.0003051525,0.00132842,0.00009376724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8104913,0.000005901899,0.1836292,0.0000367838,0.0002475202,0.00008346866,0.000001770985,0.0003610911,0.005142969],"genre_scores_gemma":[0.9828585,0.000001710904,0.01689161,0.00002937864,0.0001038369,0.00001266747,0.0000139235,0.00001609509,0.00007224875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5499985,"threshold_uncertainty_score":0.250903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02524812558300498,"score_gpt":0.2477309087759517,"score_spread":0.2224827831929467,"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."}}