{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":9,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":9,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"eb1fac968d1c","filters":{"venue":"Monte Carlo Methods and Applications"}},"results":[{"id":"W2209871569","doi":"10.1515/mcma-2015-0105","title":"Simulating from the Heston model: A gamma approximation scheme","year":2015,"lang":"en","type":"article","venue":"Monte Carlo Methods and Applications","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University; Université de Montréal; HEC Montréal","funders":"","keywords":"Heston model; Stochastic volatility; Applied mathematics; Mathematics; Representation (politics); Scheme (mathematics); Convolution (computer science); Volatility (finance); Mathematical optimization; Computer science; SABR volatility model; Econometrics; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.1032993617794168,"gpt":0.3293199342183674,"spread":0.2260205724389505,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006550195,0.0001305801,0.0002310429,0.00004017511,0.000267878,0.00008844159,0.0002190237,0.00008223757,0.000003694526],"category_scores_gemma":[0.0002158166,0.0001178217,0.00005620282,0.0002934124,0.00007753598,0.0001234832,0.00008342742,0.0001369821,0.00002282779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004351621,"about_ca_system_score_gemma":0.00002809668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005183752,"about_ca_topic_score_gemma":0.00001836922,"domain_scores_codex":[0.9989806,0.00001142138,0.0004060286,0.0003897564,0.00003944072,0.0001727489],"domain_scores_gemma":[0.998936,0.0002152712,0.0002371551,0.0004232269,0.00008069359,0.000107666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004284037,0.00003306806,0.0005327733,0.000006257588,0.00001357688,5.008257e-8,0.0006624039,0.001773748,0.00008565048,0.9671889,0.0001267776,0.02957253],"study_design_scores_gemma":[0.0001821861,0.000008512529,0.0004425683,0.000004483962,0.000009203116,7.312532e-7,0.0001962289,0.4410134,0.00002769262,0.5353346,0.02265337,0.0001269835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004721465,0.003475518,0.986719,0.001371453,0.00003565361,0.0005124338,0.0001588812,0.00006094545,0.002944615],"genre_scores_gemma":[0.3476934,0.0000472656,0.6501632,0.0004356861,0.0002846204,0.001170064,0.00002830785,0.00002693059,0.0001505738],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4392397,"threshold_uncertainty_score":0.4804631,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3125876763","doi":"10.1515/mcma-2020-2079","title":"On the dependence structure and quality of scrambled (<i>t</i>, <i>m</i>, <i>s</i>)-nets","year":2021,"lang":"en","type":"article","venue":"Monte Carlo Methods and Applications","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Austrian Science Fund","keywords":"Combinatorics; Physics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.1008715660718357,"gpt":0.4209549161854095,"spread":0.3200833501135738,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000795355,0.0001177661,0.000248762,0.00002080292,0.0001581263,0.00004470076,0.00009466332,0.00007090817,0.00007444004],"category_scores_gemma":[0.001000576,0.0000751427,0.00005001329,0.0001953531,0.0001058468,0.00004739543,0.00005428418,0.0001540625,5.643861e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008322946,"about_ca_system_score_gemma":0.00002300326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001496418,"about_ca_topic_score_gemma":0.00003210562,"domain_scores_codex":[0.9988075,0.000331223,0.0003662581,0.0002293436,0.000166954,0.00009868378],"domain_scores_gemma":[0.997084,0.002107918,0.0001665027,0.0004031232,0.0001795757,0.00005889553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004270226,0.00004656268,0.00002634583,0.0001007225,0.00001416759,8.650209e-8,0.0002079016,8.183536e-7,0.02398108,0.9664673,0.0002385018,0.008912201],"study_design_scores_gemma":[0.0001699599,0.00001639438,0.0002526457,0.00003660356,0.00003124675,0.000005921187,0.0004269807,0.001223694,0.07591449,0.9198112,0.002005024,0.0001058682],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2989303,0.000562547,0.6888067,0.003050547,0.00003028327,0.0008579963,0.00008643757,0.00005549514,0.007619768],"genre_scores_gemma":[0.3735463,0.0001081618,0.6245024,0.000913036,0.00003158902,0.0002117743,0.000005922032,0.00001753845,0.0006632431],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07461601,"threshold_uncertainty_score":0.306423,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2804758477","doi":"10.1515/mcma-2018-0010","title":"Bayesian estimation of ordinary differential equation models when the likelihood has multiple local modes","year":2018,"lang":"en","type":"article","venue":"Monte Carlo Methods and Applications","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ode; Ordinary differential equation; Likelihood function; Applied mathematics; Mathematical optimization; Function (biology); Mathematics; Bayesian probability; Estimation theory; Computer science; Differential equation; Algorithm; Statistics; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.1337522174823785,"gpt":0.3993047817033635,"spread":0.2655525642209851,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007610876,0.0001558957,0.0002701576,0.00004884629,0.0003268279,0.00005620745,0.0001835741,0.00009171626,0.00003248202],"category_scores_gemma":[0.0005063913,0.0001091842,0.00006386216,0.000146634,0.0004744193,0.000095622,0.00009321309,0.0001260858,0.000001127771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002164029,"about_ca_system_score_gemma":0.00003450723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000221322,"about_ca_topic_score_gemma":0.00002999985,"domain_scores_codex":[0.9985927,0.000364209,0.0004124519,0.0002746955,0.0001685378,0.0001874075],"domain_scores_gemma":[0.9969652,0.00212385,0.0001812624,0.0004346922,0.0002098125,0.00008513195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002039038,0.00009035,0.00002241736,0.00005472162,0.00002467984,7.996925e-8,0.0007364611,0.0003617986,0.002164521,0.3139236,0.0001469868,0.682454],"study_design_scores_gemma":[0.0001223098,0.0000486522,0.0001071024,0.00001521405,0.0000558528,0.00000121126,0.0001559476,0.5274525,0.001809917,0.4700363,0.0001252618,0.00006976454],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005941386,0.00008572962,0.9921582,0.00034449,0.00003556207,0.0006206359,0.00005170295,0.00004528833,0.0007170286],"genre_scores_gemma":[0.483673,0.000006390374,0.5159911,0.0000220397,0.0000599008,0.0002089134,0.000003207152,0.00001110227,0.00002435733],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6823843,"threshold_uncertainty_score":0.4452401,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4297995547","doi":"10.1515/mcma-2022-2123","title":"Estimation of entropy and extropy based on right censored data: A Bayesian non-parametric approach","year":2022,"lang":"en","type":"article","venue":"Monte Carlo Methods and Applications","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Estimator; Parametric statistics; Bayesian probability; Mathematics; Entropy (arrow of time); Principle of maximum entropy; Econometrics; Statistics; Applied mathematics; Computer science; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.02316970924384907,"gpt":0.3258430943898142,"spread":0.3026733851459651,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00150654,0.0001731017,0.0003065517,0.0002625287,0.0003705573,0.00008371656,0.0007274987,0.00005205688,0.000004742327],"category_scores_gemma":[0.00005855167,0.0001568764,0.00004977797,0.0009183146,0.00008134376,0.0001806978,0.0004453239,0.0002216178,1.622896e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003165887,"about_ca_system_score_gemma":0.00005124559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004365427,"about_ca_topic_score_gemma":4.563117e-7,"domain_scores_codex":[0.9979581,0.0005440152,0.000310224,0.000733337,0.000250183,0.0002041542],"domain_scores_gemma":[0.9978797,0.0004311727,0.0001864486,0.001328163,0.00004549037,0.0001289845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001672275,0.0002350936,0.00004436282,0.00005350778,0.00002138482,0.000001384104,0.000193317,0.005719633,0.00126901,0.1902471,0.0002744396,0.801924],"study_design_scores_gemma":[0.0003681536,0.00009032336,0.0002728692,0.000004826786,0.00003352241,0.00001067742,0.00002473177,0.9824718,0.0006734554,0.01146389,0.004425247,0.0001605294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003990102,0.0004592193,0.9971431,0.0003894752,0.00004546195,0.0006728334,0.00008538568,0.00004912069,0.0007563681],"genre_scores_gemma":[0.1361954,0.00002783533,0.8630457,0.0001840276,0.00002688722,0.0004180984,0.00002809284,0.00001250122,0.00006147739],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9767522,"threshold_uncertainty_score":0.6397235,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2111112077","doi":"10.1515/mcma.2010.010","title":"Exact simulation of Bessel diffusions","year":2010,"lang":"en","type":"preprint","venue":"Monte Carlo Methods and Applications","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bessel process; Bessel function; Mathematics; Applied mathematics; Hitting time; Markov chain; Mathematical analysis; Statistics; Orthogonal polynomials","retraction":null,"screen_n_in":null,"score":{"opus":0.04791509176371623,"gpt":0.3383240000867005,"spread":0.2904089083229843,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005476191,0.0002590308,0.0006680784,0.0002101,0.000221016,0.00005964235,0.0003628956,0.0004506959,0.00001947346],"category_scores_gemma":[0.000196243,0.0002976424,0.0001819,0.0002898219,0.0001643903,0.00005774459,0.0004084251,0.000586774,0.00000823232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003038255,"about_ca_system_score_gemma":0.00004747193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004603449,"about_ca_topic_score_gemma":0.00003172196,"domain_scores_codex":[0.9981529,0.00001211843,0.00087157,0.0007067813,0.00004423524,0.0002124523],"domain_scores_gemma":[0.9977252,0.0003221284,0.0008221177,0.0008538208,0.0001534345,0.0001233162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000005388978,0.0001814097,0.0003156324,0.000215614,0.00004836262,1.237925e-7,0.0003060062,0.003214146,0.0005476596,0.9426998,0.000028478,0.05243737],"study_design_scores_gemma":[0.0002343501,0.00002337206,0.004228535,0.00004175207,0.00006529008,0.000001376408,0.00006202128,0.08838811,0.0001522471,0.8472976,0.05905085,0.0004544826],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005215688,0.004447607,0.9846664,0.0003463225,0.0001804318,0.0009770786,0.001044947,0.00005629539,0.003065197],"genre_scores_gemma":[0.7306111,0.0005045684,0.2662141,0.0000828436,0.0003332295,0.001895293,0.00007655539,0.00005239053,0.000229863],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7253955,"threshold_uncertainty_score":0.9999475,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4212872317","doi":"10.1515/mcma-2022-2106","title":"Moment matching adaptive importance sampling with skew-student proposals","year":2022,"lang":"en","type":"article","venue":"Monte Carlo Methods and Applications","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"","keywords":"Skew; Matching (statistics); Sampling (signal processing); Moment (physics); Rejection sampling; Class (philosophy); Computer science; Importance sampling; Applied mathematics; Adaptive sampling; Mathematics; Statistics; Artificial intelligence; Monte Carlo method; Physics; Markov chain Monte Carlo","retraction":null,"screen_n_in":null,"score":{"opus":0.1049241116065604,"gpt":0.4550021656866213,"spread":0.3500780540800609,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005908017,0.000160784,0.000227938,0.00004860506,0.0008595519,0.00005445287,0.0001724476,0.00002650578,0.0001319277],"category_scores_gemma":[0.00003423105,0.0001423395,0.00004447623,0.0003306216,0.00008715741,0.00005251027,0.0001415009,0.0002206205,0.000002405996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001268682,"about_ca_system_score_gemma":0.00004404959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002376851,"about_ca_topic_score_gemma":0.000007962719,"domain_scores_codex":[0.9986328,0.0001492717,0.0003558587,0.0003818955,0.0002727134,0.0002074921],"domain_scores_gemma":[0.9987143,0.0005091404,0.0001842284,0.0003592474,0.0001032481,0.0001298408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009789825,0.0001795925,0.0001622843,0.00002007492,0.00003516849,7.679802e-7,0.0004018047,0.000262439,0.0005072717,0.9785805,0.0002794996,0.0195608],"study_design_scores_gemma":[0.00111007,0.0002321204,0.00723734,0.00003609181,0.0002974029,0.00007412709,0.008498413,0.0120997,0.0005492613,0.8746724,0.09434504,0.0008480226],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009549294,0.0001465587,0.9865636,0.0007454822,0.00001416178,0.001173952,0.0003826079,0.0001270552,0.001297342],"genre_scores_gemma":[0.2018358,0.0000127443,0.791526,0.0002011129,0.0000361553,0.00599457,0.0000394102,0.00002585655,0.0003282926],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1950375,"threshold_uncertainty_score":0.6611065,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2970759111","doi":"10.1515/mcma-2019-2045","title":"Quasi-Monte Carlo method for solving Fredholm equations","year":2019,"lang":"en","type":"article","venue":"Monte Carlo Methods and Applications","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Atomic Energy (Canada)","funders":"","keywords":"Monte Carlo method; Fredholm integral equation; Hybrid Monte Carlo; Applied mathematics; Statistical physics; Dynamic Monte Carlo method; Monte Carlo molecular modeling; Monte Carlo method in statistical physics; Fredholm theory; Mathematics; Computer science; Integral equation; Markov chain Monte Carlo; Physics; Mathematical analysis; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.07318058783061929,"gpt":0.4388399506290042,"spread":0.3656593627983848,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001936371,0.0002545938,0.0004776173,0.0001208487,0.0002959906,0.0001300935,0.0002170402,0.0001619126,0.0001175199],"category_scores_gemma":[0.00102734,0.0002175192,0.0001977007,0.000278153,0.00005017447,0.0001995689,0.00006574209,0.0001946694,0.0000187233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005811719,"about_ca_system_score_gemma":0.00005057455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006356138,"about_ca_topic_score_gemma":0.00004385041,"domain_scores_codex":[0.9981704,0.0001951283,0.0006425772,0.0004902923,0.0002048863,0.0002966586],"domain_scores_gemma":[0.9951533,0.003488787,0.0002649637,0.0006310452,0.0003120576,0.0001498294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008289521,0.0001856718,0.00001670274,0.0002473257,0.00004680636,5.938113e-8,0.0007759716,0.00002237012,0.003682779,0.928575,0.0008814199,0.06555755],"study_design_scores_gemma":[0.0006577094,0.0001228687,0.00002230712,0.00005951811,0.0001572826,0.000005551382,0.001306369,0.4363056,0.002474852,0.516704,0.04183456,0.0003494005],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00289454,0.0001946949,0.9875889,0.001054951,0.0000834682,0.002544127,0.00006816246,0.0001737236,0.005397422],"genre_scores_gemma":[0.01328678,0.0000210641,0.9786371,0.0002453172,0.0001404433,0.002544261,0.00001402301,0.00005160768,0.005059413],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4362833,"threshold_uncertainty_score":0.8870174,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1439202096","doi":"10.1515/mcma-2013-0019","title":"Rare event simulation for diffusion processes via two-stage importance sampling","year":2014,"lang":"en","type":"article","venue":"Monte Carlo Methods and Applications","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University; Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Estimator; Brownian motion; Rare events; Importance sampling; Mathematics; Measure (data warehouse); Entropy (arrow of time); Applied mathematics; Event (particle physics); Sampling (signal processing); Large deviations theory; Statistical physics; Path (computing); Computer science; Mathematical optimization; Monte Carlo method; Statistics; Data mining; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.1763937691469354,"gpt":0.5054004319798635,"spread":0.3290066628329281,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003920282,0.000136875,0.0002616855,0.00007813086,0.0005025416,0.0001386865,0.0002988591,0.00007362587,0.00001177877],"category_scores_gemma":[0.002091191,0.00009953311,0.00009286916,0.000407189,0.00007873838,0.0002108734,0.00008929472,0.00008507138,0.000002075191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002319718,"about_ca_system_score_gemma":0.00003529958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002637261,"about_ca_topic_score_gemma":0.00009094111,"domain_scores_codex":[0.9981391,0.0002141449,0.0005671059,0.0005939634,0.0002942992,0.0001913288],"domain_scores_gemma":[0.9947348,0.003828682,0.0002756746,0.0005792176,0.0004667411,0.0001148545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004394382,0.00009223782,0.004117833,0.00007861734,0.00000804412,5.140418e-8,0.0004888746,0.1243922,0.003771019,0.01389782,0.00003880966,0.8530706],"study_design_scores_gemma":[0.000475149,0.00003503861,0.001269582,0.00001185247,0.00002105884,7.985376e-7,0.0001519232,0.6554542,0.0006707941,0.2346054,0.107134,0.0001701808],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05053266,0.000552063,0.9471766,0.0003620018,0.00004505593,0.001052336,0.00004436863,0.00004915193,0.0001857053],"genre_scores_gemma":[0.6714693,0.00003338249,0.3271405,0.0001438144,0.0001193529,0.0006475032,0.000008257507,0.0000111472,0.0004266954],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8529004,"threshold_uncertainty_score":0.4058842,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3044317697","doi":"10.1515/mcma-2020-2067","title":"QMC integration errors and quasi-asymptotics","year":2020,"lang":"en","type":"article","venue":"Monte Carlo Methods and Applications","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Atomic Energy (Canada)","funders":"","keywords":"Applied mathematics; Statistical physics; Mathematics; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.1042611699164301,"gpt":0.4104468060276037,"spread":0.3061856361111736,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004132523,0.0001549517,0.0002494061,0.0000384028,0.0001486491,0.00007791982,0.00008508258,0.00008818536,0.00003852903],"category_scores_gemma":[0.0005734164,0.0001242542,0.00004848164,0.0001961825,0.00008424504,0.00011788,0.00004735327,0.0001592156,0.00000518716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001457015,"about_ca_system_score_gemma":0.00001391482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007763499,"about_ca_topic_score_gemma":0.000008894091,"domain_scores_codex":[0.9989936,0.0001258396,0.0003575942,0.0002785742,0.0001205115,0.0001238908],"domain_scores_gemma":[0.9989883,0.0004215568,0.000120515,0.0001924109,0.0001024112,0.0001748179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006256704,0.00005961244,0.00001976763,0.000110803,0.00001356511,1.292951e-7,0.001586063,7.557334e-7,0.001842615,0.8853061,0.0006418111,0.1104125],"study_design_scores_gemma":[0.0005180434,0.0002186553,0.0001361435,0.00005589997,0.0001484628,0.00001261665,0.003683411,0.2162647,0.006343188,0.7364325,0.03575926,0.0004271115],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01069688,0.0001504331,0.9806956,0.003993794,0.00001621451,0.0006153523,0.00001266556,0.0001274802,0.003691562],"genre_scores_gemma":[0.07650435,0.00008927607,0.921931,0.0007199232,0.0001058058,0.0002925744,0.000008203643,0.00002425707,0.0003246375],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.216264,"threshold_uncertainty_score":0.5066938,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}