{"id":"W4297347715","doi":"10.3390/app12199668","title":"Projection Pursuit Multivariate Sampling of Parameter Uncertainty","year":2022,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Latin hypercube sampling; Projection pursuit; Monte Carlo method; Sampling (signal processing); Multivariate statistics; Rejection sampling; Mathematics; Projection (relational algebra); Statistics; Slice sampling; Algorithm; Computer science; Importance sampling; Markov chain Monte Carlo; Hybrid Monte Carlo","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":[0.005695734,0.000861914,0.001279632,0.0008218059,0.0004245054,0.0009738675,0.0007990737,0.0006664335,0.001187196],"category_scores_gemma":[0.01835446,0.0004710206,0.0009242684,0.001022598,0.001223477,0.001333682,0.001457331,0.00137886,0.0001911506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000688551,"about_ca_system_score_gemma":0.001505704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002237456,"about_ca_topic_score_gemma":0.001155078,"domain_scores_codex":[0.997005,0.001933184,0.00009901012,0.0002693839,0.0005791565,0.000114186],"domain_scores_gemma":[0.992831,0.005592017,0.0003960489,0.0004887541,0.0006242729,0.00006782732],"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":[0.0001639806,0.00003304707,0.001002215,0.0001165109,0.00006329658,0.00006614134,0.00006153795,0.9227395,0.00310686,0.02430893,0.0002918348,0.04804614],"study_design_scores_gemma":[0.000007820177,0.00004049878,0.0001931109,0.000007470766,0.000006150954,0.00002345822,0.000008146951,0.9913119,0.001535438,0.006600922,0.0002571387,0.000007987317],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007142232,0.00006208847,0.9922082,0.0000376849,0.000005156024,0.00002433148,0.00001479323,0.00007366645,0.0004318496],"genre_scores_gemma":[0.5730708,0.0004176429,0.4248446,0.00007457434,0.00003715872,0.0003420829,0.0001766934,0.0000724689,0.0009638979],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005695734,"threshold_uncertainty_score":0.03012228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2053794927832376,"score_gpt":0.375858765116633,"score_spread":0.1704792723333953,"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."}}