{"id":"W2912123949","doi":"10.1109/tcds.2019.2897618","title":"Combined Sensing, Cognition, Learning, and Control for Developing Future Neuro-Robotics Systems: A Survey","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Cognitive and Developmental Systems","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Robotics; Artificial intelligence; Cognitive robotics; Computer science; Robot; Embodied cognition; Cognition; Perception; Developmental robotics; Cognitive neuroscience; Human–computer interaction; Cognitive science; Neuroscience; Psychology","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":[0.0003477641,0.0003120597,0.0004102816,0.0001658936,0.0005025505,0.0003037853,0.00007498985,0.0001294832,0.000006108728],"category_scores_gemma":[0.00006486936,0.0002887262,0.00004884936,0.0002045952,0.000102021,0.000199485,0.000004323054,0.000259326,0.00004740493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005131686,"about_ca_system_score_gemma":0.00008807276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004233956,"about_ca_topic_score_gemma":0.00002920488,"domain_scores_codex":[0.9979541,0.0004237963,0.0004084625,0.0006249997,0.0002452081,0.0003433762],"domain_scores_gemma":[0.9973329,0.00210396,0.0001526587,0.00005947255,0.0002352616,0.0001157522],"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":[0.02529594,0.00355178,0.0758477,0.01930995,0.00497994,0.0006176204,0.02978724,0.01539129,0.6778685,0.004603945,0.007923142,0.1348229],"study_design_scores_gemma":[0.07454906,0.01018611,0.02514954,0.01299611,0.001063762,0.005384996,0.04759219,0.280927,0.5105897,0.0002917482,0.02148083,0.009788984],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.447499,0.0001270472,0.5461479,0.0001513035,0.002577744,0.002640687,0.0003296622,0.0001582767,0.0003683757],"genre_scores_gemma":[0.9979767,0.0001002458,0.0001986425,0.0005710747,0.00006789329,0.00007863126,0.00002030301,0.00003886572,0.0009475943],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5504777,"threshold_uncertainty_score":0.9999565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02800951321653945,"score_gpt":0.2596949502957785,"score_spread":0.2316854370792391,"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."}}