{"id":"W3129528580","doi":"10.1109/lra.2021.3060402","title":"Parallelism in Autonomous Robotic Surgery","year":2021,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Intuitive Surgical","keywords":"Computer science; Parallelism (grammar); Task (project management); Automation; Robot; Robotic surgery; Artificial intelligence; State (computer science); Data parallelism; Motion (physics); Distributed computing; Human–computer interaction; Parallel computing; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008004546,0.0001208119,0.0001837797,0.0001030623,0.00004778146,0.00007667806,0.00004826596,0.0000567988,0.0000131066],"category_scores_gemma":[0.00001428635,0.0001393456,0.00004375517,0.0002374335,0.00002341466,0.00009378426,0.0000111156,0.0001097584,0.00002566699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004590504,"about_ca_system_score_gemma":0.00002072548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006239206,"about_ca_topic_score_gemma":0.00001314891,"domain_scores_codex":[0.9992585,0.00001695267,0.0002685882,0.0001611006,0.00009164949,0.0002032676],"domain_scores_gemma":[0.9995998,0.0001240206,0.000028071,0.0001679326,0.00002061836,0.00005952487],"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":[2.018925e-7,0.00001521438,0.001147349,0.00003635388,0.00001156225,0.00001980838,0.00007054679,0.9882494,0.005647605,0.001094813,0.002232685,0.001474415],"study_design_scores_gemma":[0.0001841324,0.00000213644,0.04175062,0.00005086312,0.00001643772,0.00002850128,0.00002265429,0.9552128,0.001282482,0.0003859689,0.0007857564,0.0002776485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6708894,0.0005297006,0.3177489,0.0087718,0.001005725,0.0001794955,0.000004261571,0.0005331488,0.0003374874],"genre_scores_gemma":[0.989889,0.0001634647,0.00910349,0.0006566672,0.00007942459,0.00001977869,0.0000257681,0.00002619755,0.00003616075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3189996,"threshold_uncertainty_score":0.568235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01356445174310811,"score_gpt":0.2105486440149476,"score_spread":0.1969841922718395,"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."}}