{"id":"W2550790092","doi":"10.1002/cem.2852","title":"Estimation of Flat‐topped Gaussian distribution with application in system identification","year":2016,"lang":"en","type":"article","venue":"Journal of Chemometrics","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gaussian; Gaussian random field; Gaussian process; Probability density function; Mathematics; Gaussian noise; Random variable; Applied mathematics; Gaussian filter; Algorithm; Gaussian function; Mathematical optimization; Statistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004377363,0.00006689359,0.0001817834,0.0004721807,0.00001183743,0.00001440105,0.000080985,0.00006307699,0.000001293221],"category_scores_gemma":[0.0001019283,0.0000449561,0.00003897037,0.001169716,0.00001104882,0.0002113567,0.000002831998,0.00006675132,0.000005466474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003271422,"about_ca_system_score_gemma":0.00001593266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003882183,"about_ca_topic_score_gemma":0.000002900989,"domain_scores_codex":[0.9990193,0.00001857112,0.0005569198,0.00005609335,0.0002684256,0.0000806537],"domain_scores_gemma":[0.9993047,0.00004904814,0.0003585709,0.0001112552,0.0001364406,0.00004003636],"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":[0.000214592,0.00008814321,0.008826143,0.0009053624,0.0001180937,0.000008104034,0.0001968673,0.04345497,0.473801,0.001514237,0.0003163121,0.4705562],"study_design_scores_gemma":[0.004531536,0.0002643834,0.07867151,0.0009236442,0.00009392521,0.0002637018,0.000452063,0.554233,0.3583499,0.0001245743,0.001755182,0.0003365429],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4517516,0.0001032349,0.547691,0.00006343579,0.000146184,0.00009440183,0.000005448393,0.00002421465,0.0001204641],"genre_scores_gemma":[0.9997402,0.00002002725,0.0001490786,8.881922e-7,0.00005053042,0.000006754301,0.000003112499,0.000009229237,0.00002017422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5479885,"threshold_uncertainty_score":0.1833256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004928063804508289,"score_gpt":0.2075558539070093,"score_spread":0.202627790102501,"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."}}