{"id":"W2766401386","doi":"10.1007/978-3-319-67361-5_3","title":"Towards Controlling Bucket Fill Factor in Robotic Excavation by Learning Admittance Control Setpoints","year":2017,"lang":"en","type":"book-chapter","venue":"Springer proceedings in advanced robotics","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Setpoint; Engineering; Throttle; Factor (programming language); Control theory (sociology); Simulation; Computer science; Control (management); Automotive engineering; Artificial intelligence","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":[0.0006028923,0.0009151289,0.0008509719,0.0003144008,0.0003728879,0.001092841,0.001355316,0.0009668897,0.003263149],"category_scores_gemma":[0.001703982,0.0004639684,0.0006126754,0.000407726,0.0009035394,0.00118206,0.001559664,0.001695,0.0005577969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003889474,"about_ca_system_score_gemma":0.000459367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00330525,"about_ca_topic_score_gemma":0.003347972,"domain_scores_codex":[0.9997421,0.00003968053,0.00001651467,0.00008598307,0.0000822996,0.00003331156],"domain_scores_gemma":[0.9995692,0.0002088528,0.00005949411,0.00005958007,0.00008192268,0.00002085916],"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":[0.0001680827,0.00009538744,0.0004344601,0.0002405705,0.00005242731,0.00008343042,0.0002666342,0.7104377,0.02470839,0.01390455,0.001588931,0.2480194],"study_design_scores_gemma":[0.00001231118,0.00009802498,0.0001809361,0.00001668758,0.000008630069,0.00002406486,0.00001907156,0.9903134,0.002501273,0.005371159,0.001444059,0.0000104953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01503316,0.0003351358,0.9815593,0.00007111147,0.00004908888,0.00002743733,0.00001726887,0.0005119166,0.002395588],"genre_scores_gemma":[0.8698523,0.0004050266,0.1243595,0.00007718805,0.00005523045,0.0001074507,0.00006504673,0.0001138027,0.004964355],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00330525,"threshold_uncertainty_score":0.01091629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01126751241213908,"score_gpt":0.2209300802954315,"score_spread":0.2096625678832925,"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."}}