{"id":"W2024629186","doi":"10.1115/dscc2010-4163","title":"Parametric Uncertainty Modeling and Multiple Controller Design for Hard Disk Drives","year":2010,"lang":"en","type":"article","venue":"","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Samsung; Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Parametric statistics; Transfer function; Computer science; Control theory (sociology); Controller (irrigation); Set (abstract data type); Partition (number theory); Robust control; Control engineering; Control system; Control (management); Engineering; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005982065,0.0006204389,0.0006425657,0.0003249345,0.0003417947,0.0008026352,0.001035388,0.0006390467,0.00100591],"category_scores_gemma":[0.001758801,0.000404857,0.0005607324,0.0002447746,0.0005576448,0.001010858,0.0007734855,0.001102173,0.0003092304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004352916,"about_ca_system_score_gemma":0.0006670197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001682684,"about_ca_topic_score_gemma":0.00129951,"domain_scores_codex":[0.999229,0.0001715292,0.0000366419,0.0001521949,0.0003744809,0.00003618187],"domain_scores_gemma":[0.9995465,0.0002153039,0.00006502875,0.00006543791,0.00009621907,0.00001148484],"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":[0.00006308068,0.00002881436,0.0001866546,0.0001249584,0.00004251588,0.0000753261,0.0001160243,0.8331164,0.01500387,0.02427929,0.0003849987,0.126578],"study_design_scores_gemma":[0.00000809167,0.00003066945,0.00006777896,0.00000615015,0.00000560001,0.00001951693,0.000006905784,0.9887652,0.003658305,0.006145108,0.001278324,0.000008302262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002465414,0.00009689558,0.9969586,0.00002196034,0.000006551367,0.000008129697,0.000006489259,0.0000995387,0.000336365],"genre_scores_gemma":[0.6248832,0.0005106515,0.3712645,0.00006573346,0.00005624958,0.0002300262,0.00009504351,0.00009806117,0.002796644],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001682684,"threshold_uncertainty_score":0.003365159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193512401833059,"score_gpt":0.2250791488550469,"score_spread":0.205727908671741,"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."}}