{"id":"W4396788082","doi":"10.48550/arxiv.2405.03453","title":"A weighted multilevel Monte Carlo method","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Radiative Heat Transfer Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Monte Carlo method; Statistical physics; Computer science; Mathematics; Physics; Statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001337887,0.0005231746,0.0005490275,0.0003660991,0.00008074862,0.00004664352,0.0004669386,0.0003595679,0.00005005983],"category_scores_gemma":[0.00001096332,0.0006007453,0.0003291101,0.0003911505,0.00008446783,0.00007750684,0.0005042608,0.001157289,0.0002588262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004209465,"about_ca_system_score_gemma":0.000061703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002465008,"about_ca_topic_score_gemma":0.0001560904,"domain_scores_codex":[0.9983642,0.00008912394,0.0002187373,0.0008280165,0.00007857913,0.0004213075],"domain_scores_gemma":[0.9990053,0.0001382648,0.0000225877,0.0006016,0.00008407874,0.0001481223],"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":[0.00002759226,0.00003777942,0.0004589516,0.001141961,0.001717823,0.0009068843,0.001656169,0.9755921,0.0001777362,0.01359034,0.002622114,0.002070563],"study_design_scores_gemma":[0.0003892985,0.00001755867,0.0009780194,0.0002335654,0.0004218378,0.000003302242,0.0001370292,0.9826438,0.0005739802,0.01099511,0.002913932,0.0006925953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5791742,0.005736783,0.3751351,0.0001201359,0.003892853,0.001122123,0.0006544666,0.003531043,0.03063322],"genre_scores_gemma":[0.9942695,0.001192135,0.002357058,0.00001831919,0.0001356766,0.000005587587,0.000009106533,0.0001084731,0.001904092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4150953,"threshold_uncertainty_score":0.9996444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06896327648827921,"score_gpt":0.1996113745692582,"score_spread":0.130648098080979,"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."}}