{"id":"W1996067628","doi":"10.1002/cjce.20479","title":"Selection of simplified models: II. Development of a model selection criterion based on mean squared error","year":2011,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Diverse Scientific and Engineering Research","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Mitacs","keywords":"Bayesian information criterion; Univariate; Model selection; Mean squared error; Selection (genetic algorithm); Monte Carlo method; Information Criteria; Multivariate statistics; Set (abstract data type); Mathematics; Statistics; Computer science; Nonlinear system; Deviance information criterion; Estimation theory; Bayesian probability; Algorithm; Applied mathematics; Markov chain Monte Carlo; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003710613,0.0001299257,0.0001960401,0.000367392,0.00005281888,0.00001259022,0.0002359219,0.00008123335,0.00004266231],"category_scores_gemma":[0.00004599686,0.0001127689,0.000079344,0.0003333484,0.0000333313,0.0001128635,0.000009553795,0.0002871061,0.000001000259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002752971,"about_ca_system_score_gemma":0.0002902584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001044744,"about_ca_topic_score_gemma":0.00006726963,"domain_scores_codex":[0.9989915,0.000006739726,0.0003705852,0.00008149247,0.0002759362,0.0002737636],"domain_scores_gemma":[0.9994057,0.0000230706,0.00005747591,0.0001023504,0.000176181,0.0002352658],"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":[0.00001894612,0.00001046448,0.000004602696,0.00007733071,0.0000315017,0.000001039618,0.001120009,0.8712994,0.1266359,0.0001446677,0.0001159463,0.0005402502],"study_design_scores_gemma":[0.0001458884,0.00002903969,0.00002174196,0.00009219733,0.00001102958,0.000005051087,0.00001425762,0.7348373,0.2646703,0.00004442389,0.00004977124,0.0000790134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9003059,0.00003210042,0.09855846,0.00001607235,0.0002322348,0.00009451074,0.000007886905,0.00004091949,0.0007118735],"genre_scores_gemma":[0.9890589,5.749537e-7,0.01086205,0.00000445684,0.00002619896,0.000002815247,0.000001720479,0.00002566461,0.00001758294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1380344,"threshold_uncertainty_score":0.4598583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04980506816039085,"score_gpt":0.2167529483800289,"score_spread":0.1669478802196381,"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."}}