{"id":"W2111658521","doi":"10.1109/icnn.1993.298695","title":"Robotic modeling and control using a fuzzy neural network","year":2002,"lang":"en","type":"article","venue":"IEEE International Conference on Neural Networks","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Space Agency","funders":"","keywords":"Artificial neural network; Robustness (evolution); Computer science; Robot; Backpropagation; Artificial intelligence; Fuzzy logic; Fuzzy control system; Software; Neuro-fuzzy; Control engineering; Machine learning; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001936162,0.0002828775,0.0003283963,0.00008466437,0.0002028767,0.0005162741,0.0009032062,0.0001232629,0.00002369297],"category_scores_gemma":[0.00002385363,0.0002494757,0.0001044015,0.0001750356,0.00005880299,0.0005170836,0.0001041998,0.0003878748,0.0000152271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005485209,"about_ca_system_score_gemma":0.00001261451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005154581,"about_ca_topic_score_gemma":0.00001213153,"domain_scores_codex":[0.9979252,0.0001494259,0.0004147893,0.0005719447,0.000427688,0.0005109149],"domain_scores_gemma":[0.9990051,0.0001424727,0.0001634035,0.0003365881,0.0001817961,0.0001705852],"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":[0.00002438825,0.00002448245,0.0003142022,0.000002255729,0.00003534579,0.0000405372,0.00003511446,0.9545071,0.00006762812,0.03676282,0.0001971911,0.007988991],"study_design_scores_gemma":[0.0007356395,0.0001029392,0.00007611793,0.00005252352,0.00001157758,0.00009787304,0.000007320307,0.9932802,8.11573e-7,0.00536437,0.00001457852,0.0002560102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04999221,0.0007389481,0.9314309,0.003137496,0.005851978,0.0003885925,0.000003007912,0.0002578094,0.008199084],"genre_scores_gemma":[0.995432,0.00005680074,0.001204013,0.001912142,0.001207367,0.00002009867,0.000001621589,0.00001560983,0.0001503089],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9454398,"threshold_uncertainty_score":0.9999958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08167200233173044,"score_gpt":0.2698360813100519,"score_spread":0.1881640789783214,"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."}}