{"id":"W4294324898","doi":"10.1002/cjce.24631","title":"Multimode process monitoring strategy based on improved just‐in‐time‐learning associated with locality preserving projections","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Outlier; Locality; Pattern recognition (psychology); Principal component analysis; Computer science; Feature vector; Gaussian process; Artificial intelligence; Feature (linguistics); Mixture model; Process (computing); Algorithm; Gaussian; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008553532,0.0007812938,0.001003186,0.0006818433,0.0006367681,0.0009416214,0.001595869,0.0007482443,0.001323709],"category_scores_gemma":[0.002234849,0.0004489755,0.0006862777,0.000664295,0.0006529404,0.002171039,0.001610981,0.001129984,0.0003727287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005457893,"about_ca_system_score_gemma":0.001039395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003136776,"about_ca_topic_score_gemma":0.002579795,"domain_scores_codex":[0.9989225,0.0001962063,0.00005886334,0.0003186127,0.0004060843,0.00009777721],"domain_scores_gemma":[0.9989531,0.000293963,0.0001433133,0.0001807963,0.0003548003,0.00007408961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004246378,0.0002758037,0.004400029,0.0001285762,0.00009766444,0.0002302027,0.0003299241,0.310464,0.06164388,0.01059869,0.001800986,0.6096056],"study_design_scores_gemma":[0.000007162828,0.00005706683,0.0003110817,0.000002363343,0.00000764289,0.00004845621,0.00001331474,0.9907539,0.006903949,0.001534719,0.0003496346,0.00001076511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01974701,0.00007036333,0.9788054,0.00006910505,0.00001847315,0.0000266681,0.00001640574,0.0005336861,0.0007127578],"genre_scores_gemma":[0.6736413,0.0001020101,0.3229089,0.0001390672,0.00004489541,0.000119538,0.0001184039,0.0001073841,0.002818591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003136776,"threshold_uncertainty_score":0.00623703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009001167608374263,"score_gpt":0.2050654466357147,"score_spread":0.1960642790273404,"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."}}