{"id":"W2331879234","doi":"10.2514/6.2008-1924","title":"Performance of a Parallel Time Integrator for Noisy Nonlinear System","year":2008,"lang":"en","type":"article","venue":"","topic":"Nonlinear Dynamics and Pattern Formation","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Integrator; Nonlinear system; Computer science; Control theory (sociology); Telecommunications; Artificial intelligence; Physics; Bandwidth (computing); Control (management)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013061,0.00007524141,0.0001267248,0.00005554717,0.00007327395,0.00001381363,0.0003288778,0.0000354951,0.000004453663],"category_scores_gemma":[0.000005082317,0.00005838426,0.00005758262,0.0001203287,0.00001738673,0.0002639842,0.00005035413,0.00004436485,0.00008536597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002058351,"about_ca_system_score_gemma":0.00004270589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001042045,"about_ca_topic_score_gemma":0.000001635305,"domain_scores_codex":[0.9994018,0.00001077611,0.0002204808,0.0001196787,0.0001229762,0.000124278],"domain_scores_gemma":[0.9995155,0.00002829033,0.00008530293,0.0002119295,0.0001223865,0.00003660142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001079392,0.002877125,0.1809547,0.008665797,0.0007606337,0.00007103237,0.01921844,0.03268413,0.0365816,0.4584153,0.01665495,0.2420369],"study_design_scores_gemma":[0.0002378681,0.0001617557,0.0005120808,0.0000224882,0.000001786982,0.00002550595,0.000008128261,0.9969033,0.001067188,0.000008263661,0.0009757191,0.00007588823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5354061,0.000006553859,0.4623502,0.00005137348,0.00009072921,0.0001629385,0.000008399461,0.00008814106,0.001835495],"genre_scores_gemma":[0.7769161,0.000008184232,0.2219106,0.0000456558,0.00004578675,0.00001292444,0.00001733838,0.000005761889,0.001037551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9642192,"threshold_uncertainty_score":0.2380841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200313267282631,"score_gpt":0.2069006824641815,"score_spread":0.1948975497913552,"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."}}