{"id":"W2146177659","doi":"10.1109/acc.2006.1656356","title":"Local L2 Gain of Axial-Flow Compressor Control","year":2006,"lang":"en","type":"article","venue":"","topic":"Turbomachinery Performance and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Control theory (sociology); Throttle; Gas compressor; Lyapunov function; Operating point; Computer science; Aerodynamics; Actuator; Mathematics; Engineering; Control (management); Physics; Artificial intelligence; Mechanical engineering; Aerospace engineering; Electrical engineering","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":[0.00003091375,0.00006419192,0.0001006195,0.00003473677,0.00001329912,0.000005834717,0.00004643211,0.00003722766,0.0002712034],"category_scores_gemma":[9.065231e-7,0.00005528707,0.00002708782,0.00004195143,0.00001766744,0.00008005512,0.000004067354,0.00004210647,0.00003977199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001060407,"about_ca_system_score_gemma":0.000002897612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000576554,"about_ca_topic_score_gemma":0.00003367427,"domain_scores_codex":[0.9996449,0.000004631804,0.000136884,0.00004834183,0.00006575596,0.00009942574],"domain_scores_gemma":[0.9998586,0.00001371439,0.00001219012,0.00008332714,0.00001679904,0.00001533967],"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":[0.00000630106,0.00001123373,0.0008807155,0.00002200838,0.000006434459,4.932855e-7,0.000008260862,0.991702,0.001072605,0.000223023,0.0038525,0.002214467],"study_design_scores_gemma":[0.0004974871,0.00001217278,0.003111676,0.0000041685,0.000005987364,9.590883e-7,0.000003599265,0.98748,0.007446098,0.00004049159,0.001328752,0.00006857956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05368053,0.0001937239,0.9192341,0.00002947456,0.0001296424,0.0000868854,0.00001116607,0.0002057503,0.02642876],"genre_scores_gemma":[0.9971738,0.00001054173,0.002364656,0.00003204227,0.00005969869,0.000003721663,0.00002019101,0.00001111515,0.0003242446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9434932,"threshold_uncertainty_score":0.2969487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002710575102054633,"score_gpt":0.1684895350808665,"score_spread":0.1657789599788119,"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."}}