{"id":"W3005386404","doi":"10.1109/lra.2020.2970944","title":"6-DOF Force Sensing for the Master Tool Manipulator of the da Vinci Surgical System","year":2020,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Joystick; Surgical robot; Haptic technology; Software; Manipulator (device); Interface (matter); Torque; Impedance control; Simulation; Engineering; Robot; Computer science; Embedded system; Artificial intelligence; Operating system; Physics","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":[0.0006505818,0.0005785078,0.0003463996,0.0005958919,0.0001752417,0.0003556249,0.0006568509,0.0004094345,0.003492671],"category_scores_gemma":[0.001138804,0.0002733519,0.0002360944,0.0002483134,0.0001955074,0.0003974777,0.000364218,0.0004192248,0.0008328155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002190369,"about_ca_system_score_gemma":0.0003910905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007237159,"about_ca_topic_score_gemma":0.001216485,"domain_scores_codex":[0.9993647,0.00005635128,0.00004086041,0.0001012693,0.0003847729,0.00005204257],"domain_scores_gemma":[0.9995289,0.0001001187,0.00008826885,0.00006907387,0.0001741589,0.00003950177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003393493,0.00007468811,0.002738385,0.0003049672,0.00002815977,0.000313388,0.0001922304,0.005167928,0.80212,0.002695425,0.003083601,0.1829419],"study_design_scores_gemma":[0.0001247806,0.002717646,0.0275615,0.00009113992,0.00008437203,0.003331407,0.00008944806,0.1145344,0.7862593,0.0009344986,0.06404454,0.0002269677],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1372925,0.0004858867,0.8519946,0.000280095,0.0002036408,0.0002598205,0.0005251645,0.003563319,0.005394874],"genre_scores_gemma":[0.4871026,0.0002725848,0.5047104,0.0001911583,0.00004985116,0.0002081903,0.0002787845,0.000162789,0.007023653],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003492671,"threshold_uncertainty_score":0.01168418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02590618164683748,"score_gpt":0.2033025069550324,"score_spread":0.1773963253081949,"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."}}