{"id":"W2000122651","doi":"10.1006/mssp.2000.1289","title":"MODEL ORDER SELECTION: A PRACTICAL APPROACH","year":2001,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Akaike information criterion; Autoregressive model; Bayesian information criterion; Minimum description length; Information Criteria; Model selection; Selection (genetic algorithm); Range (aeronautics); Process (computing); Computer science; STAR model; Sample (material); Mathematics; Algorithm; Autoregressive integrated moving average; Statistics; Data mining; Artificial intelligence; Time series; Engineering","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":[0.002087675,0.001327518,0.001521053,0.001289596,0.000845413,0.001452328,0.001249905,0.001176524,0.008277949],"category_scores_gemma":[0.009060384,0.0008034824,0.0008970475,0.0009585028,0.000659225,0.001564919,0.001290409,0.001585579,0.001902116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005036262,"about_ca_system_score_gemma":0.001462744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002199836,"about_ca_topic_score_gemma":0.003808087,"domain_scores_codex":[0.9987891,0.0006049419,0.00005418888,0.0001497442,0.00033135,0.00007067441],"domain_scores_gemma":[0.996031,0.002610683,0.0001313262,0.0005313733,0.0006208349,0.00007471859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003928269,0.0002032697,0.001152688,0.0003566219,0.0001779774,0.0004776561,0.0001700017,0.4736634,0.005079054,0.1408975,0.01108672,0.3663423],"study_design_scores_gemma":[0.00004977604,0.00007249308,0.0001652124,0.00001558845,0.00003857425,0.00008791377,0.00002189625,0.9262251,0.001376461,0.06882084,0.003110239,0.00001591501],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001345783,0.00008749264,0.996878,0.0001519508,0.00002767195,0.00002212441,0.00002538694,0.0002576729,0.001203915],"genre_scores_gemma":[0.3109086,0.0006834113,0.6756386,0.0002923531,0.0003653771,0.0001993694,0.0003872534,0.0003970349,0.01112804],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008277949,"threshold_uncertainty_score":0.0276925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02649120868850038,"score_gpt":0.249239142722078,"score_spread":0.2227479340335776,"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."}}