{"id":"W4413794841","doi":"10.3390/act14090419","title":"Stability Optimization of an Oil Sampling Machine Control System Based on Improved Sparrow Search Algorithm PID","year":2025,"lang":"en","type":"article","venue":"Actuators","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"PID controller; Stability (learning theory); Sampling (signal processing); Sparrow; Algorithm; Computer science; Control theory (sociology); Mathematical optimization; Control (management); Control engineering; Artificial intelligence; Engineering; Mathematics; Machine learning; Temperature control; Biology","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":[0.0004499082,0.0005386006,0.0005833308,0.0003379008,0.0003799521,0.0005534316,0.0005118445,0.0004180412,0.001016452],"category_scores_gemma":[0.0005073707,0.0002560721,0.0003716608,0.0002754203,0.0003462323,0.0003243886,0.0003513889,0.0003362771,0.0001798559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004325208,"about_ca_system_score_gemma":0.001103221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005569769,"about_ca_topic_score_gemma":0.003522434,"domain_scores_codex":[0.9997081,0.00005284222,0.00001714234,0.0000772546,0.0001126728,0.00003193278],"domain_scores_gemma":[0.9997756,0.00006457984,0.00004519191,0.00001584239,0.00008860096,0.00001031496],"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":[0.0001770988,0.00004384925,0.001102315,0.0001345318,0.00004755054,0.00007164568,0.0001307867,0.877152,0.03484494,0.004688433,0.0005831128,0.08102376],"study_design_scores_gemma":[0.000009625438,0.00005310035,0.0001920633,0.00000223487,0.00000450425,0.00001027003,0.000004780085,0.9970086,0.002232353,0.0001434069,0.0003355649,0.000003522745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1200496,0.0003506998,0.8737391,0.00008140663,0.0000298342,0.00007027367,0.00002622369,0.0005879299,0.005064868],"genre_scores_gemma":[0.9315903,0.0001303574,0.06549594,0.00002726207,0.00001069885,0.0001033131,0.00005067591,0.00002851787,0.002563025],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005569769,"threshold_uncertainty_score":0.01107466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008750435494482834,"score_gpt":0.2429320689253384,"score_spread":0.2341816334308555,"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."}}