{"id":"W2093313821","doi":"10.1002/aic.14261","title":"A quality relevant non‐Gaussian latent subspace projection method for chemical process monitoring and fault detection","year":2013,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Covariance; Partial least squares regression; Latent variable; Subspace topology; Gaussian process; Projection (relational algebra); Independent component analysis; Gaussian; Kriging; Statistics; Computer science; Mathematics; Multivariate statistics; Pattern recognition (psychology); Artificial intelligence; Algorithm","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":[0.0005468955,0.000146355,0.0002049131,0.00008761846,0.0001438704,0.0001505946,0.00006124405,0.0001374022,0.00000605209],"category_scores_gemma":[0.00008400134,0.0001237413,0.00007755673,0.0001282988,0.000009225198,0.0002897008,0.00000728387,0.0003617588,0.000006948117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000133314,"about_ca_system_score_gemma":0.00001456422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008417521,"about_ca_topic_score_gemma":0.00001336052,"domain_scores_codex":[0.9990302,0.00005454417,0.0003396207,0.0001493148,0.0001771579,0.0002491196],"domain_scores_gemma":[0.9994845,0.00005660519,0.00009883195,0.00008665855,0.0001357444,0.0001376726],"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":[0.0000566315,0.00001857609,0.0006744637,0.0001963493,0.00009117876,0.000001069641,0.0009432101,0.001235721,0.8982971,0.000004220458,0.0001018762,0.0983796],"study_design_scores_gemma":[0.002057421,0.0001710287,0.008928029,0.0001318526,0.00005665803,0.0006384934,0.002052856,0.578873,0.4046963,0.0004389509,0.001526364,0.0004290247],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.813435,0.0001677616,0.1843961,0.0001862862,0.000957831,0.0005069841,0.000001073431,0.0001613563,0.000187554],"genre_scores_gemma":[0.9955936,0.00003480667,0.003400611,0.000008997213,0.0006592464,0.0001779999,4.015756e-7,0.00002936388,0.00009495459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5776373,"threshold_uncertainty_score":0.5046026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01594920924822274,"score_gpt":0.3020069752634464,"score_spread":0.2860577660152236,"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."}}