{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001575373,0.0002250341,0.0004759926,0.000420697,0.00006952072,0.0001939586,0.0002371819,0.00009187605,0.000008945641],"category_scores_gemma":[0.0001833081,0.0001917771,0.0001508392,0.0001150333,0.00005319556,0.0007483017,0.00001338787,0.000456161,0.000002460068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001728659,"about_ca_system_score_gemma":0.00005070134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009944333,"about_ca_topic_score_gemma":0.00001594009,"domain_scores_codex":[0.9981098,0.0001305592,0.0007996275,0.0001623968,0.0004982799,0.0002993882],"domain_scores_gemma":[0.9985065,0.0006173151,0.0002921651,0.00003577301,0.0004334342,0.0001148157],"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":[0.002846749,0.0001277461,0.0332537,0.00003485968,0.001053092,0.001000187,0.00378854,0.5966569,0.1797296,0.0001544683,0.0000778608,0.1812763],"study_design_scores_gemma":[0.01214268,0.0002538071,0.05494734,0.0007767325,0.0000659217,0.0001554505,0.000935871,0.9286673,0.0009416182,0.0003374756,0.0004190398,0.0003567797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1537216,0.003602272,0.8416991,0.0001204088,0.0003870707,0.0001759267,0.000003733115,0.00003334283,0.0002564549],"genre_scores_gemma":[0.9949857,0.0000162691,0.004275916,0.00009734465,0.000547127,0.00000499167,8.00131e-7,0.00003076109,0.00004106758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8412641,"threshold_uncertainty_score":0.7820445,"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."}}