{"id":"W2047314268","doi":"10.1016/s0019-0578(07)60160-8","title":"Manipulated variable based PI tuning and detection of poor settings: An industrial experience","year":2004,"lang":"en","type":"article","venue":"ISA Transactions","topic":"Advanced Control Systems Design","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"PID controller; Variable (mathematics); Control theory (sociology); Process (computing); Set (abstract data type); Computer science; Constant (computer programming); Order (exchange); Control engineering; Control (management); Mathematics; Engineering; Artificial intelligence; Temperature control","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":[0.003050415,0.0009798234,0.001066415,0.001034727,0.0007302831,0.001271118,0.001659904,0.001519407,0.002513933],"category_scores_gemma":[0.008663818,0.000387949,0.0002776913,0.0009102182,0.001142347,0.0009625279,0.000918289,0.001222056,0.0006841199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003348655,"about_ca_system_score_gemma":0.0003535304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001685276,"about_ca_topic_score_gemma":0.001708531,"domain_scores_codex":[0.9977951,0.0008672201,0.0001061745,0.000288574,0.000818858,0.0001241233],"domain_scores_gemma":[0.9909184,0.005566051,0.0003569882,0.001093368,0.001828501,0.0002367492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003552018,0.001584368,0.01501141,0.0006456369,0.0002041856,0.0009002392,0.002147851,0.05216648,0.1495547,0.003405249,0.003784094,0.7670439],"study_design_scores_gemma":[0.0005954994,0.008871329,0.02878239,0.0001075024,0.0003258706,0.003771685,0.001395515,0.5534943,0.3827081,0.00445462,0.0151359,0.000357202],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4167855,0.001605613,0.5716943,0.0003831639,0.00009861169,0.0002298145,0.0001452048,0.002559262,0.006498508],"genre_scores_gemma":[0.9267556,0.0004003184,0.06990095,0.00006226013,0.00003329229,0.00004017245,0.00005905835,0.0001853098,0.002563094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003050415,"threshold_uncertainty_score":0.01613235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01993655023794202,"score_gpt":0.2162411666631765,"score_spread":0.1963046164252344,"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."}}