{"id":"W2135991726","doi":"","title":"Generating multi-scroll chaotic attractors via switching control","year":2004,"lang":"en","type":"article","venue":"Asian Control Conference","topic":"Chaos control and synchronization","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Scroll; Attractor; Chaotic; Control theory (sociology); Function series; Series (stratigraphy); Computer science; Controller (irrigation); Function (biology); Topology (electrical circuits); Mathematics; Control (management); Engineering; Mathematical analysis; Artificial intelligence; Mechanical engineering; Power series","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":[0.0001341313,0.0002421733,0.0002331454,0.0003016818,0.0001858389,0.0002265441,0.0003776503,0.0001654738,0.001034969],"category_scores_gemma":[0.000287013,0.00008675316,0.000223753,0.000157096,0.0003641204,0.0003796584,0.0003015518,0.0001753699,0.0001495743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001561892,"about_ca_system_score_gemma":0.000148402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002854338,"about_ca_topic_score_gemma":0.0003355396,"domain_scores_codex":[0.9998971,0.00002353746,0.000007779779,0.00001726536,0.00004257313,0.00001173219],"domain_scores_gemma":[0.999872,0.00004870356,0.00001902565,0.00002170097,0.00002678046,0.00001167045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002320417,0.00009443687,0.001185683,0.0003909715,0.00007209602,0.000377968,0.0003422599,0.1685078,0.419303,0.05835582,0.001249082,0.3498889],"study_design_scores_gemma":[0.00004435583,0.0003441836,0.0006055036,0.00001868351,0.00003355656,0.0002318976,0.00004004339,0.8693103,0.1110239,0.01177558,0.006546143,0.00002586175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1287522,0.000240875,0.8617995,0.00006335232,0.00005135292,0.00006935247,0.00002140337,0.0008031746,0.008198836],"genre_scores_gemma":[0.9170785,0.000156805,0.0806812,0.00003905593,0.0000170866,0.00006219125,0.00002511657,0.00003948828,0.001900518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001034969,"threshold_uncertainty_score":0.003462315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01397832280083804,"score_gpt":0.2342168739401743,"score_spread":0.2202385511393362,"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."}}