{"id":"W2000251225","doi":"10.1002/acs.994","title":"Multiple robust track‐following controller design in hard disk drives","year":2007,"lang":"en","type":"article","venue":"International Journal of Adaptive Control and Signal Processing","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Track (disk drive); Computer science; Controller (irrigation); Control theory (sociology); Tracking (education); Set (abstract data type); Robust control; Optimal control; Control engineering; Mathematical optimization; Control (management); Control system; Mathematics; Engineering; Artificial intelligence","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":[0.0008733173,0.0006967451,0.0009547517,0.0003299142,0.0003747333,0.001298307,0.001290755,0.0008489353,0.001152506],"category_scores_gemma":[0.001807136,0.0003612333,0.0004017104,0.0003029281,0.0005238348,0.0006458397,0.0006401852,0.0008387647,0.0004168031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005253304,"about_ca_system_score_gemma":0.0006485392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002144619,"about_ca_topic_score_gemma":0.001249364,"domain_scores_codex":[0.9992149,0.000106965,0.00004916579,0.000245888,0.0003269027,0.00005618193],"domain_scores_gemma":[0.9992367,0.0002278106,0.0001792037,0.00006722864,0.0002585497,0.00003046232],"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":[0.0002709132,0.00008226428,0.000325808,0.0002816691,0.0000957629,0.0001313959,0.0001471688,0.7933379,0.03069961,0.01075403,0.001177916,0.1626956],"study_design_scores_gemma":[0.00002191145,0.00009237494,0.00007738454,0.000006504402,0.000007614802,0.00001628167,0.000004945165,0.9949839,0.003218137,0.0008187738,0.0007454497,0.000006608111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01263081,0.0003733094,0.9850484,0.00007677242,0.00005553709,0.00004197068,0.00001717315,0.0003207114,0.001435396],"genre_scores_gemma":[0.8566281,0.0003299335,0.1389344,0.0001040382,0.00008003718,0.0002156168,0.00007045011,0.00004622519,0.003591068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002144619,"threshold_uncertainty_score":0.004618585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01743370205435852,"score_gpt":0.2367266283664582,"score_spread":0.2192929263120997,"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."}}