{"id":"W2057683060","doi":"10.1177/0954410011417671","title":"Micro-electromechanical systems gyro performance improvement through bias correction over temperature using an adaptive neural network-trained fuzzy inference system","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Adaptive neuro fuzzy inference system; Fuzzy logic; Control theory (sociology); Artificial neural network; Compensation (psychology); Computer science; Controller (irrigation); Fuzzy control system; Artificial intelligence; Control (management)","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":[0.0002049868,0.0002765207,0.0002355303,0.0001845588,0.0001945584,0.0002144614,0.0003104554,0.0002597901,0.0005778251],"category_scores_gemma":[0.0005133888,0.0001226217,0.0001536725,0.0001291607,0.0001449269,0.0002523734,0.000144364,0.0002213273,0.0001405182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002546961,"about_ca_system_score_gemma":0.0002220388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001705598,"about_ca_topic_score_gemma":0.003626141,"domain_scores_codex":[0.9998817,0.00001236135,0.000008672002,0.00002940002,0.00006086652,0.000006830962],"domain_scores_gemma":[0.9998844,0.00003032002,0.00002083197,0.00001439123,0.00004577345,0.000004229794],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003637598,0.0001275428,0.002619609,0.0002060217,0.00006625081,0.0001124851,0.0001567479,0.1284469,0.5670118,0.001312734,0.001001962,0.2985742],"study_design_scores_gemma":[0.00003806119,0.0002240881,0.005286866,0.00001969283,0.00005551343,0.0001411048,0.00001543412,0.8400791,0.1501662,0.000320318,0.003629236,0.00002451977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2192938,0.0007964843,0.7735209,0.0001950212,0.0001440166,0.00007082646,0.00004643743,0.001325735,0.004606757],"genre_scores_gemma":[0.8827875,0.0001937427,0.1151,0.0000366945,0.00002738952,0.00003513066,0.00003054208,0.00001767627,0.001771234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001705598,"threshold_uncertainty_score":0.003391325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02931440450802622,"score_gpt":0.2088841360238833,"score_spread":0.1795697315158571,"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."}}