{"id":"W2144816266","doi":"10.1109/cdc.2001.914555","title":"A unified approach for stability robustness computation of quasi-polynomials in a convex set","year":2002,"lang":"en","type":"article","venue":"","topic":"Stability and Control of Uncertain Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Robustness (evolution); Regular polygon; Computation; Convex combination; Mathematics; Mathematical optimization; Measure (data warehouse); Convex optimization; Stability (learning theory); Computer science; Applied mathematics; Algorithm; Machine learning","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":[0.0004509462,0.0001099189,0.000361228,0.00006542922,0.00001539265,0.0000122879,0.00009062059,0.00008807866,0.00004474305],"category_scores_gemma":[0.00005735833,0.000105496,0.00006797653,0.0001603855,0.00003628179,0.00008410817,0.000007219003,0.00005858973,0.00000115667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007234175,"about_ca_system_score_gemma":0.000008537766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001148584,"about_ca_topic_score_gemma":0.00008353484,"domain_scores_codex":[0.9990643,0.00006140731,0.0004394269,0.0001604345,0.00009994365,0.0001745394],"domain_scores_gemma":[0.9994688,0.0002258418,0.00004167422,0.0001669353,0.00006086433,0.00003586525],"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":[0.0001231171,0.0003800282,0.004284648,0.00169039,0.00006907123,4.699704e-7,0.003203182,0.9802147,0.002510394,0.001173202,0.0004503845,0.005900422],"study_design_scores_gemma":[0.001223022,0.00005135836,0.0005969413,0.00001272364,0.000006974726,6.325529e-7,0.001209332,0.9959112,0.0007497455,0.00007843347,0.00004406384,0.0001155772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.434485,0.000189177,0.5611384,0.00003951633,0.00009404089,0.0008288809,0.00002423769,0.000102075,0.003098709],"genre_scores_gemma":[0.9967683,0.000002386674,0.003033766,0.000008505758,0.00002593258,0.0001159459,0.00001188231,0.00001220077,0.00002108291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5622833,"threshold_uncertainty_score":0.4302002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05803138241920566,"score_gpt":0.2400243148888004,"score_spread":0.1819929324695947,"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."}}