{"id":"W2031848479","doi":"10.1016/s0255-2701(02)00203-9","title":"Reinforcing the phenomenological consistency in artificial neural network modeling of multiphase reactors","year":2003,"lang":"en","type":"article","venue":"Chemical Engineering and Processing - Process Intensification","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Overfitting; Artificial neural network; Computer science; Consistency (knowledge bases); Artificial intelligence; A priori and a posteriori; Monotonic function; Machine learning; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00247224,0.000413295,0.0006237425,0.0003566507,0.0005894998,0.001230477,0.001581447,0.00130333,0.001093661],"category_scores_gemma":[0.01297187,0.0004352999,0.0006348735,0.0003266677,0.001884108,0.002793719,0.001423158,0.001686419,0.0001251997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005931431,"about_ca_system_score_gemma":0.0005838667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001678867,"about_ca_topic_score_gemma":0.001614694,"domain_scores_codex":[0.9992964,0.0004034052,0.00003623614,0.00008044617,0.0001425798,0.00004087495],"domain_scores_gemma":[0.9968465,0.002037575,0.0003287945,0.000381141,0.000346706,0.00005914777],"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":[0.0001636946,0.00009388423,0.001785435,0.0001122296,0.00005873719,0.000196505,0.0001636423,0.759374,0.003753642,0.2265685,0.0003864593,0.007343255],"study_design_scores_gemma":[0.00001122199,0.00001340543,0.0001730531,0.000006338332,0.000004228445,0.0000102016,0.00001250902,0.9600871,0.0003238256,0.03920368,0.0001490086,0.000005449766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4330212,0.0008243613,0.5416696,0.004325128,0.0003835779,0.00004656258,0.00007013187,0.0001850701,0.01947444],"genre_scores_gemma":[0.9850744,0.0001866035,0.0133982,0.0001449025,0.00007551745,0.00001878083,0.00002477429,0.0000314559,0.001045414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00247224,"threshold_uncertainty_score":0.01307458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01895872656483496,"score_gpt":0.2261386735296304,"score_spread":0.2071799469647954,"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."}}