{"id":"W1999861638","doi":"10.1145/2464576.2464590","title":"Dynamic memory for robot control via delay neural networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Robot; Task (project management); Coincidence; Artificial neural network; Transmission (telecommunications); Limit (mathematics); Coincidence detection in neurobiology; Transmission delay; Control (management); Artificial intelligence; Real-time computing; Control theory (sociology); Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00004281977,0.0001371404,0.0001503997,0.00002506314,0.00007079988,0.00002178824,0.00009993396,0.00005368585,0.00008379737],"category_scores_gemma":[0.000008206124,0.0001206743,0.00006772488,0.0000557475,0.00001305829,0.0001857033,0.00001365982,0.0001328218,0.00002569412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002269581,"about_ca_system_score_gemma":0.000001401865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003201475,"about_ca_topic_score_gemma":0.000006256847,"domain_scores_codex":[0.9993289,0.000009198015,0.0001643238,0.0001333835,0.00004335516,0.0003209088],"domain_scores_gemma":[0.9996046,0.0001455041,0.00001769996,0.0001308541,0.00002784052,0.00007352598],"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":[0.000004743172,0.000002891959,0.00000777443,0.00001212719,0.00001129172,0.000001372647,0.000007092032,0.9335861,0.01027832,0.00001688776,0.0002469392,0.0558245],"study_design_scores_gemma":[0.0004609673,0.00003193488,0.0001470628,0.000004132857,0.000008514592,0.00001310217,0.00000941591,0.9977264,0.001129338,0.0002061336,0.0001046147,0.0001583858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08515874,0.0002078239,0.9126689,0.00006245244,0.0005280655,0.0004087327,7.928226e-7,0.0004708196,0.0004937135],"genre_scores_gemma":[0.9936012,0.000003701325,0.005492845,0.0003454374,0.0001142717,0.00005824212,0.000004637137,0.00003427644,0.0003453947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9084424,"threshold_uncertainty_score":0.4920954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00615277322375553,"score_gpt":0.2090423750509073,"score_spread":0.2028896018271518,"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."}}