{"id":"W1998696694","doi":"10.1109/mcse.2013.46","title":"Reveal: An Extensible Reduced-Order Model Builder for Simulation and Modeling","year":2013,"lang":"en","type":"article","venue":"Computing in Science & Engineering","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Pacific Northwest National Laboratory; National Energy Technology Laboratory; Office of Fossil Energy; U.S. Department of Energy","keywords":"Computer science; Extensibility; Domain (mathematical analysis); Fidelity; Range (aeronautics); Sampling (signal processing); Supercomputer; Computational science; Programming language; Software engineering; Parallel computing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002389885,0.00009453617,0.00009876723,0.0001059555,0.0001326909,0.0001133026,0.0001092839,0.00001972453,0.000003297296],"category_scores_gemma":[0.0000162196,0.00009558473,0.00001706434,0.0002759136,0.0000277293,0.0004722382,0.00004845257,0.00009757883,7.073808e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001779023,"about_ca_system_score_gemma":0.00002843524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002658418,"about_ca_topic_score_gemma":1.486812e-7,"domain_scores_codex":[0.9991704,0.000004180023,0.0001642343,0.0002830729,0.00009716258,0.0002809617],"domain_scores_gemma":[0.999618,0.00003091344,0.00002793198,0.0001242424,0.0001136131,0.00008528179],"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":[6.685132e-7,0.000007727485,0.0001843368,0.000002924324,6.988375e-7,2.045633e-8,0.0001538791,0.9818251,0.01021173,0.002215511,0.000004556412,0.005392845],"study_design_scores_gemma":[0.0001174695,0.00000785428,0.0002175886,0.00002926475,0.000001524199,3.791932e-7,0.00004400593,0.9979798,0.0003427098,0.001138951,0.000005281612,0.0001151419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5082322,0.000009301756,0.4914987,0.00001806622,0.00007315756,0.0001089879,1.826504e-7,0.00002409668,0.00003521817],"genre_scores_gemma":[0.9474083,3.545572e-7,0.05238701,0.000018306,0.0001426617,0.000009656664,0.000001511284,0.00001188829,0.00002028289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4391761,"threshold_uncertainty_score":0.3897832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03959801500332878,"score_gpt":0.3103178141763438,"score_spread":0.270719799173015,"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."}}