{"id":"W4414540220","doi":"10.1021/acs.iecr.5c02581","title":"Physics-Informed Neural Network with NSGA II and Levenberg–Marquardt Method for Kinetic Modeling in Heavy Oil Hydrocracking","year":2025,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Western University","keywords":"Overfitting; Sorting; Solver; Artificial neural network; Genetic algorithm; Convergence (economics); Matching (statistics); Kinetic energy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001077805,0.001669334,0.001098448,0.0007008314,0.0004352024,0.0009135559,0.001347374,0.001268152,0.00179249],"category_scores_gemma":[0.002311523,0.000735833,0.001070656,0.000581699,0.0005706226,0.0006562315,0.000900411,0.001596319,0.0002294168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173988,"about_ca_system_score_gemma":0.002561821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02530055,"about_ca_topic_score_gemma":0.01793709,"domain_scores_codex":[0.9996462,0.0001161142,0.00002337239,0.00007544918,0.00007931612,0.00005947702],"domain_scores_gemma":[0.9993123,0.0004108111,0.00005768107,0.00002905165,0.0001626089,0.00002762305],"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":[0.0000141484,0.00001194491,0.0001802798,0.00002149507,0.00001252619,0.00001549492,0.000006315654,0.9958237,0.0001653889,0.0004124353,0.0001078047,0.003228415],"study_design_scores_gemma":[0.000002793649,0.000008020264,0.0000331155,0.000002095814,0.000002787704,0.00000100107,0.000002116028,0.9995601,0.00007985246,0.0002359654,0.00007048574,0.000001665427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1611067,0.001383286,0.8271884,0.0005866762,0.0001764769,0.0003173311,0.0003756606,0.001573993,0.007291489],"genre_scores_gemma":[0.8835157,0.0004003342,0.1101488,0.000283786,0.00003809321,0.0008883852,0.000695498,0.0001151716,0.003914146],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02530055,"threshold_uncertainty_score":0.05030662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07842772262340914,"score_gpt":0.3501291869640428,"score_spread":0.2717014643406337,"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."}}