{"id":"W2112410387","doi":"10.1191/0142331203tm072oa","title":"Design and tuning of valve position controllers with industrial applications","year":2003,"lang":"en","type":"article","venue":"Transactions of the Institute of Measurement and Control","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Ranging; Position (finance); Control engineering; Computer science; Range (aeronautics); Control theory (sociology); Control (management); Set (abstract data type); Engineering; Telecommunications; 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":[0.0009218301,0.0005440486,0.0005272396,0.0004084658,0.0003860246,0.0009615898,0.001040409,0.001029149,0.001184114],"category_scores_gemma":[0.002256366,0.0004022648,0.0003078954,0.0002683592,0.0004659389,0.0004438637,0.0006947268,0.0008741666,0.000400075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002679356,"about_ca_system_score_gemma":0.0006304288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004560869,"about_ca_topic_score_gemma":0.0004813177,"domain_scores_codex":[0.9992523,0.0001044938,0.00005498489,0.0001485302,0.0003908005,0.00004880371],"domain_scores_gemma":[0.9993405,0.0001904821,0.0001087814,0.0000763647,0.0002426671,0.0000412345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002191415,0.0002057555,0.001238039,0.0005803807,0.00007764697,0.0003204667,0.0005469436,0.3384118,0.2076479,0.01724105,0.001203831,0.432307],"study_design_scores_gemma":[0.0001367632,0.0005258547,0.0008207008,0.00004965232,0.00003214689,0.0002566827,0.00004245215,0.9469562,0.03535374,0.004694398,0.01109665,0.00003476873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008550158,0.0002873214,0.9888268,0.0000452131,0.00004158859,0.00008148415,0.000004471599,0.0003527483,0.001810231],"genre_scores_gemma":[0.5707645,0.0003929391,0.4256027,0.0001081137,0.00007117545,0.0003490076,0.00002871911,0.0000494472,0.002633393],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001184114,"threshold_uncertainty_score":0.004875183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315418887082112,"score_gpt":0.1864343998498018,"score_spread":0.1632802109789807,"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."}}