{"id":"W1976121046","doi":"10.1007/s00791-011-0163-7","title":"Iterant recombination with one-norm minimization for multilevel Markov chain algorithms via the ellipsoid method","year":2011,"lang":"en","type":"article","venue":"Computing and Visualization in Science","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Ellipsoid; Mathematical optimization; Norm (philosophy); Quadratic programming; Uniform norm; Applied mathematics; Mathematical analysis","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":[0.003812634,0.0006920096,0.001624486,0.001037289,0.0007401482,0.001377614,0.002226856,0.001838141,0.004936774],"category_scores_gemma":[0.0136876,0.0007109298,0.001120148,0.0009305284,0.00127151,0.001762508,0.002929739,0.002662889,0.001061417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001037908,"about_ca_system_score_gemma":0.00163184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00363286,"about_ca_topic_score_gemma":0.003561182,"domain_scores_codex":[0.998022,0.001131704,0.00008329548,0.0001712268,0.0004908768,0.0001009784],"domain_scores_gemma":[0.9944354,0.004110539,0.0002462566,0.000440527,0.0005699595,0.0001972739],"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":[0.0001842692,0.0001164264,0.0006829892,0.000181534,0.00009249418,0.00006352783,0.0002549351,0.6487021,0.002854265,0.2579962,0.002553481,0.08631766],"study_design_scores_gemma":[0.000008165559,0.000009592218,0.00002727216,0.000007542068,0.000003067187,0.000006057443,0.000004307077,0.9822198,0.0002449025,0.0169849,0.0004789034,0.000005593496],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002984875,0.00007945386,0.9958642,0.00005998395,0.00001672064,0.00001960582,0.00001546418,0.0001028188,0.0008568946],"genre_scores_gemma":[0.1289744,0.0001643639,0.8672416,0.00009830075,0.00004739187,0.0003264185,0.0001518275,0.0004376475,0.002558133],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004936774,"threshold_uncertainty_score":0.02016342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1251798667458862,"score_gpt":0.4114427424022615,"score_spread":0.2862628756563753,"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."}}