{"id":"W4383108492","doi":"10.1109/icra48891.2023.10160585","title":"Learning State Conditioned Linear Mappings for Low-Dimensional Control of Robotic Manipulators","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Robot manipulator; Control theory (sociology); Computer science; State (computer science); Linear control systems; Control (management); Control engineering; Artificial intelligence; Linear system; Mathematics; Engineering; Algorithm; Mathematical analysis","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003199069,0.0003275974,0.0005915796,0.0003209206,0.00009084452,0.00003843513,0.0001627725,0.000252165,0.0002352297],"category_scores_gemma":[0.0001291326,0.000355243,0.0002548674,0.0001303765,0.0000338115,0.0000673688,0.00009899013,0.0006790308,0.0001314376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007766089,"about_ca_system_score_gemma":0.00004403569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003605341,"about_ca_topic_score_gemma":0.000007645632,"domain_scores_codex":[0.9983177,0.00005008272,0.0006743318,0.0003499403,0.000272844,0.0003351466],"domain_scores_gemma":[0.9989926,0.0002916828,0.0002052093,0.0002351635,0.0001780412,0.00009729517],"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":[0.00001786081,0.00001030414,0.0005555784,0.0007446043,0.0002183672,0.000003125747,0.0001646114,0.9960091,0.001135991,0.0003638303,0.0006668972,0.0001097406],"study_design_scores_gemma":[0.0008082738,0.00003750899,0.00377031,0.0002648242,0.00005761459,0.000001495455,0.00005943421,0.9932293,0.0004005235,0.0007364117,0.0002761968,0.0003581254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06552033,0.00007941286,0.9300944,0.0001314833,0.001435894,0.0009458364,0.00001593835,0.00147141,0.0003053257],"genre_scores_gemma":[0.9916331,0.00001400572,0.003850541,0.00004787652,0.000143854,0.00009103242,0.0005313118,0.0001490689,0.003539231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9262438,"threshold_uncertainty_score":0.99989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03023423662906594,"score_gpt":0.2522355178324995,"score_spread":0.2220012812034335,"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."}}