{"id":"W4306176439","doi":"10.1002/cjce.24715","title":"The use of artificial neural network (ANN) in dry flue gas desulphurization modelling: Levenberg–Marquardt (LM) and Bayesian regularization (BR) algorithm comparison","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Industrial Gas Emission Control","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mean squared error; Artificial neural network; Levenberg–Marquardt algorithm; Sigmoid function; Algorithm; Coefficient of determination; Mathematics; Computer science; Machine learning; 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":[0.003002708,0.0008351584,0.0006960708,0.0006261437,0.0002736168,0.0008638083,0.0006249727,0.0009657922,0.0004804042],"category_scores_gemma":[0.004287196,0.0003139339,0.0005621773,0.0004975712,0.0002758824,0.0007032952,0.0003745761,0.0006815955,0.0001674773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007351969,"about_ca_system_score_gemma":0.0007146543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007427723,"about_ca_topic_score_gemma":0.005693241,"domain_scores_codex":[0.9992839,0.0003690482,0.0000491478,0.0001116375,0.0001514327,0.00003484599],"domain_scores_gemma":[0.9981526,0.001147185,0.0001539319,0.00005404105,0.000465921,0.00002624929],"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":[0.0001855032,0.0001093248,0.002632376,0.0001663999,0.0001191737,0.0000421275,0.00005344325,0.8996325,0.006546482,0.001045023,0.0003514392,0.08911625],"study_design_scores_gemma":[0.000002651472,0.00003945499,0.0003768029,0.000007699577,0.000007435138,0.000005985564,0.000004699476,0.9978598,0.001413833,0.0001458333,0.0001309428,0.000004869019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2609548,0.002040282,0.730603,0.0005546352,0.00007386941,0.00009700817,0.00009652479,0.0007644981,0.004815444],"genre_scores_gemma":[0.8320291,0.0006753921,0.1648216,0.00009262366,0.00002047006,0.0001231041,0.0001257406,0.00007032963,0.00204175],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007427723,"threshold_uncertainty_score":0.01587999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02758799116808556,"score_gpt":0.1961316271618178,"score_spread":0.1685436359937322,"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."}}