{"id":"W2048856095","doi":"10.1002/(sici)1099-128x(200003/04)14:2<79::aid-cem578>3.0.co;2-o","title":"Choice of latent explanatory variables: a multiobjective optimization approach","year":2000,"lang":"en","type":"article","venue":"Journal of Chemometrics","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Latent variable; Mathematical optimization; Mathematics; Computer science; Multivariable calculus; Set (abstract data type); Data mining; Algorithm; Statistics; Engineering","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":[0.004696929,0.001845895,0.001802165,0.001984585,0.0006626146,0.001707739,0.001700635,0.00192833,0.002322687],"category_scores_gemma":[0.005329316,0.00104271,0.001319772,0.001545765,0.001129422,0.001768978,0.001757409,0.001883966,0.0004599635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174495,"about_ca_system_score_gemma":0.001880457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001754528,"about_ca_topic_score_gemma":0.001673022,"domain_scores_codex":[0.9978225,0.001435972,0.00007868314,0.0002097861,0.0003458326,0.0001072663],"domain_scores_gemma":[0.9978097,0.001635902,0.00019156,0.00008409982,0.0002173563,0.00006144184],"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":[0.00005674685,0.00008622004,0.0004942609,0.0001608833,0.0001300471,0.00006176918,0.0000753742,0.9204461,0.00150627,0.02223979,0.0005859832,0.05415655],"study_design_scores_gemma":[0.000012907,0.00001954618,0.00006978156,0.0000158921,0.00001085563,0.000007241557,0.00001017195,0.9908186,0.0003165446,0.008369796,0.000339659,0.000008985222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00244731,0.00009849085,0.9969901,0.00008931439,0.000005077207,0.00002824083,0.00001805321,0.00005303458,0.0002704102],"genre_scores_gemma":[0.1560854,0.0003686228,0.8410196,0.0001043856,0.00004768197,0.0005508604,0.0001517054,0.0001061742,0.001565573],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004696929,"threshold_uncertainty_score":0.02484006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01235270253731338,"score_gpt":0.2139318708398332,"score_spread":0.2015791683025198,"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."}}