{"id":"W2612864652","doi":"10.1002/cjce.22893","title":"Data reconciliation strategy with time registration for the evaporation process in alumina production","year":2017,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Central South University; National Natural Science Foundation of China","keywords":"Redundancy (engineering); Process (computing); Matching (statistics); Computer science; Production (economics); Matrix (chemical analysis); Data mining; Algorithm; Process engineering; Industrial engineering; Mathematics; Engineering; Materials science; Statistics","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":[0.002351672,0.0009620521,0.001148617,0.00158212,0.001041517,0.001538707,0.002015107,0.0009385066,0.0009488066],"category_scores_gemma":[0.005624366,0.0005322405,0.001649174,0.00145833,0.0008320454,0.003047567,0.002297664,0.0009329995,0.0003461901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009703406,"about_ca_system_score_gemma":0.002292271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006830884,"about_ca_topic_score_gemma":0.003158741,"domain_scores_codex":[0.9975734,0.0005679111,0.0002651948,0.0007292283,0.0006553579,0.0002088206],"domain_scores_gemma":[0.9979439,0.0004612582,0.0004603031,0.0004276994,0.0006309394,0.00007583453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005011057,0.0001822673,0.007419432,0.0001884943,0.0001390006,0.0004628739,0.0006361298,0.6542162,0.0221297,0.01656104,0.001167327,0.2963964],"study_design_scores_gemma":[0.00001550452,0.000105776,0.0008862659,0.000006767075,0.00003562085,0.00009658005,0.00006526103,0.9817755,0.01214094,0.003467056,0.001364771,0.00003997675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02342773,0.0001048811,0.9753097,0.00007672497,0.0000214044,0.00005112223,0.00003745372,0.000595474,0.0003756148],"genre_scores_gemma":[0.677303,0.0001646996,0.3204906,0.00007572219,0.00002481563,0.0001774961,0.0003524311,0.0001016756,0.00130962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006830884,"threshold_uncertainty_score":0.01358223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02449291556346929,"score_gpt":0.2330377422988006,"score_spread":0.2085448267353313,"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."}}