{"id":"W2908269613","doi":"10.1109/newcas.2018.8585698","title":"Discriminating Chaos from Non-Gaussian Noise on Analog Circuits","year":2018,"lang":"en","type":"article","venue":"","topic":"Chaos control and synchronization","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Noise (video); Gaussian noise; Chaotic; Computer science; Nonparametric statistics; Gaussian; Algorithm; Mathematics; Artificial intelligence; Statistics; Physics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004432509,0.0001181109,0.000128589,0.00003830203,0.0001467896,0.00005453038,0.000102471,0.00002606185,0.002718425],"category_scores_gemma":[0.000004403648,0.00009470969,0.00005475259,0.00008958339,0.00003334483,0.00009839398,0.0000266581,0.00006871238,0.0004591195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001721468,"about_ca_system_score_gemma":0.0000218791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008364606,"about_ca_topic_score_gemma":0.00006354247,"domain_scores_codex":[0.999314,0.00001635719,0.0001442368,0.0002262303,0.0001123878,0.0001868316],"domain_scores_gemma":[0.9995952,0.00003177047,0.00005752371,0.0002006462,0.00004809939,0.00006675076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002411134,0.0003978601,0.09188941,0.000008902086,0.0001705352,0.000003183169,0.003255284,0.00007125288,0.02140282,0.09814158,0.003598736,0.7810363],"study_design_scores_gemma":[0.008008148,0.001090901,0.5433596,0.0003401159,0.0002543706,8.552983e-7,0.004180254,0.2833453,0.08625148,0.0600168,0.01088182,0.002270408],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4495831,0.000005273605,0.1688585,0.0004555026,0.0003363105,0.0001805824,0.00004567798,0.00005263557,0.3804824],"genre_scores_gemma":[0.9964945,1.913348e-7,0.0001558093,0.0001793637,0.001787229,0.00001047264,0.00009967584,0.00001399468,0.001258755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7787659,"threshold_uncertainty_score":0.9981932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01015458934956137,"score_gpt":0.2378490103452351,"score_spread":0.2276944209956737,"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."}}