{"id":"W4400187978","doi":"10.1109/lra.2024.3421191","title":"Autonomous Blood Suction for Robot-Assisted Surgery: A Sim-to-Real Reinforcement Learning Approach","year":2024,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates; China Scholarship Council; Canada Foundation for Innovation","keywords":"Reinforcement learning; Suction; Robot; Robotic surgery; Autonomous robot; Computer science; Artificial intelligence; Human–computer interaction; Engineering; Mobile robot; Mechanical engineering","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":[0.001074599,0.0006075108,0.000729699,0.0002555221,0.0002682538,0.0004538783,0.001138354,0.0008629934,0.002285315],"category_scores_gemma":[0.001904573,0.0003461766,0.0003470719,0.0001425203,0.0009400616,0.0005963768,0.0009798104,0.000924967,0.0002750831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006957667,"about_ca_system_score_gemma":0.0009490665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004632099,"about_ca_topic_score_gemma":0.003524869,"domain_scores_codex":[0.9997122,0.0001182824,0.00001152038,0.00005959075,0.00004830752,0.00005005651],"domain_scores_gemma":[0.9991196,0.0005008353,0.0001032295,0.00006081421,0.000124377,0.00009113532],"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":[0.00009054565,0.00007319433,0.0005566537,0.00003254261,0.00001821166,0.00006264758,0.00003958899,0.9694142,0.001233155,0.002715279,0.0003632359,0.02540056],"study_design_scores_gemma":[0.000007884954,0.00002343407,0.00003554486,0.000001397155,0.000001407235,0.000004332353,0.000002896135,0.9989411,0.0001217412,0.0007699638,0.00008877277,0.000001481809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07029673,0.0002900339,0.9243718,0.0005344863,0.00005582013,0.00008133702,0.00002999273,0.0009117706,0.003428034],"genre_scores_gemma":[0.9331397,0.00007739718,0.06446386,0.0001591242,0.00002171091,0.00008064229,0.00003646784,0.0000437066,0.001977435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004632099,"threshold_uncertainty_score":0.009210229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01590985089928028,"score_gpt":0.238277447491607,"score_spread":0.2223675965923267,"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."}}