{"id":"W3201388859","doi":"10.3390/pr9101691","title":"Polymethyl Methacrylate Quality Modeling with Missing Data Using Subspace Based Model Identification","year":2021,"lang":"en","type":"article","venue":"Processes","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"McMaster University","keywords":"Partial least squares regression; Subspace topology; Missing data; Principal component analysis; Computer science; Identification (biology); Process (computing); Least-squares function approximation; Polymethyl methacrylate; Component (thermodynamics); Algorithm; Quality (philosophy); Data mining; Artificial intelligence; Mathematics; Machine learning; Statistics; Materials science","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":[0.001047558,0.000781852,0.0006305937,0.0004359471,0.0003403172,0.0006099964,0.0006973658,0.0006447647,0.0005247381],"category_scores_gemma":[0.002623521,0.0003530491,0.0009439848,0.0004841835,0.0004665947,0.0009047368,0.0006602278,0.001027829,0.0001838592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003672256,"about_ca_system_score_gemma":0.0009665582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004306546,"about_ca_topic_score_gemma":0.003372294,"domain_scores_codex":[0.9995047,0.0001585885,0.00002528298,0.000117058,0.0001606237,0.0000337761],"domain_scores_gemma":[0.9987901,0.0006404883,0.000226776,0.0001158119,0.0002052885,0.00002153196],"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":[0.00005345654,0.0000418735,0.0009031905,0.00006271866,0.00004691246,0.00004738992,0.00006185674,0.9386544,0.005595062,0.00197906,0.000219102,0.05233502],"study_design_scores_gemma":[0.00000156458,0.00001888613,0.0001402197,0.000001828001,0.000002968151,0.000008233691,0.000003811857,0.9978054,0.001179699,0.0007033659,0.0001305035,0.00000356754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01528874,0.00006140972,0.9840707,0.00004576606,0.000008302346,0.00001515815,0.00002100208,0.0002089154,0.0002800513],"genre_scores_gemma":[0.7340975,0.0002424734,0.2636516,0.00004733504,0.00002629664,0.0001101125,0.0002135898,0.00007210426,0.001539064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004306546,"threshold_uncertainty_score":0.008562982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1053061967832261,"score_gpt":0.327053911748887,"score_spread":0.221747714965661,"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."}}