{"id":"W2059615571","doi":"10.3166/jesa.45.575-593","title":"Low-order models. Optimal sampling and linearized control strategies","year":2011,"lang":"fr","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Order (exchange); Sampling (signal processing); Wake; Computer science; Control (management); Control theory (sociology); Optimal control; Stability (learning theory); Mathematical optimization; Applied mathematics; Mathematics; Engineering; Aerospace engineering; Artificial intelligence; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000427007,0.0006598007,0.0005451646,0.0003613921,0.0002942227,0.0007476941,0.000548429,0.0005688052,0.001767032],"category_scores_gemma":[0.001604238,0.0003474576,0.0005115526,0.0001905007,0.000772822,0.0007547389,0.000707284,0.0008559133,0.0003623471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006169092,"about_ca_system_score_gemma":0.0005761395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003941867,"about_ca_topic_score_gemma":0.003120206,"domain_scores_codex":[0.99976,0.00009374219,0.0000117273,0.00003242747,0.00008037081,0.00002188815],"domain_scores_gemma":[0.9995669,0.0002085075,0.0001055704,0.00004142087,0.00005265056,0.00002491343],"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":[0.0000435152,0.00002454506,0.0002479136,0.00007982637,0.00001998775,0.00003939587,0.0000568492,0.9240219,0.006231686,0.05281125,0.0004714129,0.01595177],"study_design_scores_gemma":[0.000003982101,0.00001121759,0.00003560799,0.000002650082,0.000002322814,0.000005373743,0.000002607872,0.9910979,0.000530245,0.0080846,0.0002191902,0.000004297375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01408803,0.0002090801,0.9821713,0.0001834202,0.00001915894,0.00003136502,0.0000414087,0.0002117142,0.003044507],"genre_scores_gemma":[0.8780982,0.0003397783,0.1150025,0.0001040605,0.00004469698,0.0002405551,0.0001275149,0.0000896237,0.005953096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003941867,"threshold_uncertainty_score":0.007837832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04321034668288458,"score_gpt":0.2633161028972303,"score_spread":0.2201057562143457,"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."}}