{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":45,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":45,"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","author_layer_release":"2026-06-26"},"query_hash":"d0a945f3f3ec","filters":{"venue":"Studies in Nonlinear Dynamics and Econometrics"}},"results":[{"id":"W2154667799","doi":"10.2202/1558-3708.1155","title":"Nonlinear Monetary Policy Rules: Some New Evidence for the U.S.","year":2004,"lang":"en","type":"preprint","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":64,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Monetary policy; Economics; Inflation (cosmology); Sign (mathematics); Quadratic equation; Equivalence (formal languages); Certainty; Econometrics; Central bank; Monetary economics; Keynesian economics; Mathematics","authors":[{"name":"Juan J. Dolado","is_ca":false},{"name":"Ramón María‐Dolores","is_ca":false},{"name":"Francisco J. Ruge‐Murcia","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2671618679719498,"gpt":0.3364328055007431,"spread":0.06927093752879332,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002603648,0.0002527363,0.0006472616,0.0009864076,0.0007684936,0.003452336,0.0005153356,0.0008740728,0.00506841],"category_scores_gemma":[0.01854277,0.0002621481,0.0003107305,0.001559361,0.00138681,0.001447749,0.000963816,0.001329662,0.0009634541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007722225,"about_ca_system_score_gemma":0.0004743598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01339911,"about_ca_topic_score_gemma":0.009741226,"domain_scores_codex":[0.9991834,0.0003001601,0.00009214532,0.0001662336,0.0001879094,0.00007003859],"domain_scores_gemma":[0.9873897,0.006094116,0.003548313,0.001429104,0.001209278,0.0003293942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00289703,0.0006900929,0.4607828,0.0003937658,0.0007002077,0.001405411,0.001715086,0.08532014,0.001865064,0.2623908,0.01801445,0.1638252],"study_design_scores_gemma":[0.000673783,0.0002907012,0.3547375,0.0003150259,0.000412132,0.0004674675,0.001632727,0.1365677,0.00238284,0.4756434,0.02669379,0.0001829816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9482831,0.002368179,0.006423938,0.004311567,0.0001072373,0.00002132777,0.0008329222,0.00006543423,0.03758631],"genre_scores_gemma":[0.9976071,0.0006004368,0.000660273,0.00022687,0.0000377462,0.00000334118,0.0003062705,0.00001227103,0.0005457042],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01339911,"threshold_uncertainty_score":0.02664226,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2008711664","doi":"10.2202/1558-3708.1580","title":"Option Valuation with Normal Mixture GARCH Models","year":2008,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":45,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University; University of Calgary","funders":"","keywords":"Autoregressive conditional heteroskedasticity; Financial models with long-tailed distributions and volatility clustering; Econometrics; Skewness; Volatility (finance); Economics; Mixture model; Valuation of options; Stock market index; Mathematics; Stock market; Implied volatility; Statistics; SABR volatility model","authors":[{"name":"Alexandru Badescu","is_ca":true},{"name":"Reg Kulperger","is_ca":true},{"name":"Emese Lazar","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09644517132194176,"gpt":0.2681702491074804,"spread":0.1717250777855387,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007121479,0.0008656787,0.001611077,0.001128255,0.0002951591,0.001986115,0.001360765,0.001423499,0.001713127],"category_scores_gemma":[0.0161622,0.0004929514,0.001266561,0.001121406,0.001035565,0.003254314,0.001233955,0.001559849,0.0002529301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007625653,"about_ca_system_score_gemma":0.0004244284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001897605,"about_ca_topic_score_gemma":0.0006978376,"domain_scores_codex":[0.9974334,0.001684333,0.0001014629,0.0002008762,0.0004696936,0.0001103275],"domain_scores_gemma":[0.9917136,0.006059385,0.0006788859,0.0007987285,0.0005160106,0.0002333688],"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":[0.0004097269,0.00008583601,0.003477296,0.00004067061,0.0001106209,0.0001463766,0.00006060331,0.933198,0.002064694,0.0408456,0.0002315491,0.0193291],"study_design_scores_gemma":[0.000009423395,0.00002521182,0.0002287986,0.000001623288,0.000005007095,0.00001507679,0.000003587642,0.990554,0.0002590596,0.008857388,0.00003501029,0.000005689159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4254456,0.0004535393,0.5712326,0.0003237429,0.00004003285,0.0000513238,0.00008388995,0.0003373405,0.00203196],"genre_scores_gemma":[0.9726083,0.00009553255,0.0264501,0.00002205272,0.00002887873,0.000015493,0.00007817183,0.00002055808,0.0006807966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007121479,"threshold_uncertainty_score":0.03766239,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2890498200","doi":"10.1515/snde-2016-0148","title":"Asymmetric impact of uncertainty in recessions: are emerging countries more vulnerable?","year":2018,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Emerging markets; Economics; Recession; Openness to experience; Shock (circulatory); Great recession; Volatility (finance); Econometrics; Macro; Monetary economics; Macroeconomics; Keynesian economics","authors":[{"name":"Pratiti Chatterjee","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04639234366820056,"gpt":0.3235647562051036,"spread":0.277172412536903,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001142418,0.0001746457,0.0004827947,0.0006592441,0.000494998,0.00170197,0.0002035496,0.0005089367,0.00381552],"category_scores_gemma":[0.005145984,0.0001442106,0.0003712677,0.0008008078,0.0006784613,0.00124359,0.001652417,0.000906831,0.0002629664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003680858,"about_ca_system_score_gemma":0.0002531617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009848326,"about_ca_topic_score_gemma":0.006354962,"domain_scores_codex":[0.9996362,0.00008057749,0.00002471077,0.00007168796,0.00004546225,0.0001413686],"domain_scores_gemma":[0.9966922,0.0007801604,0.001766753,0.0002148136,0.0002711347,0.0002749431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003631747,0.00004245049,0.979446,0.00003627923,0.0001654061,0.0003764545,0.001859232,0.003025737,0.000853804,0.002593765,0.000879371,0.01035818],"study_design_scores_gemma":[0.00001287041,0.00006651833,0.9840896,0.00004445985,0.00008324043,0.0001428223,0.006774858,0.003131843,0.0003351782,0.003503908,0.001796522,0.00001824251],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965019,0.0001884328,0.0002336083,0.0004608181,0.000005270076,0.000004942127,0.000191399,0.000002729101,0.002410882],"genre_scores_gemma":[0.9994355,0.0001647938,0.00002956416,0.00007263388,0.000007952884,0.000001655819,0.0001127355,0.000001621515,0.0001736213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009848326,"threshold_uncertainty_score":0.01958203,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2989859029","doi":"10.1515/snde-2018-0024","title":"Fiscal policy uncertainty and US output","year":2019,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Group for Research in Decision Analysis","funders":"","keywords":"Economics; Econometrics; Volatility (finance); Vector autoregression; Great recession; Stochastic volatility; Recession; Fiscal policy; Consistency (knowledge bases); Structural vector autoregression; Monetary policy; Macroeconomics; Mathematics; Keynesian economics","authors":[{"name":"Michał Ksawery Popiel","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03927686896540761,"gpt":0.2709712682308484,"spread":0.2316943992654408,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001878086,0.0002523797,0.0004671559,0.0008449809,0.0003196558,0.002151208,0.0002572776,0.0005394881,0.002357565],"category_scores_gemma":[0.01381576,0.0001715763,0.0003498136,0.001972782,0.0004495605,0.0006738793,0.0009576525,0.0009041064,0.0002724942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001460353,"about_ca_system_score_gemma":0.0006711512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01203981,"about_ca_topic_score_gemma":0.005668833,"domain_scores_codex":[0.9995102,0.0001562238,0.00004695549,0.00009344825,0.0001227303,0.00007044231],"domain_scores_gemma":[0.9928731,0.003118891,0.002871509,0.0002503064,0.0006470511,0.0002390692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009617008,0.0001651654,0.774682,0.0002861824,0.0006826136,0.0004392655,0.0008500726,0.1126011,0.001047593,0.05413095,0.01047495,0.04367846],"study_design_scores_gemma":[0.00009305027,0.000229182,0.7240257,0.0004050472,0.0003220072,0.0002159217,0.002032823,0.1251812,0.002475394,0.1233923,0.02150675,0.0001206634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776137,0.002632368,0.002542261,0.004417663,0.00007857315,0.000007392906,0.002362757,0.00006335534,0.01028202],"genre_scores_gemma":[0.998214,0.0005529686,0.0001140483,0.00007889212,0.00003440282,0.000002479911,0.000594239,0.000005310331,0.0004037028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01203981,"threshold_uncertainty_score":0.02393949,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2740008170","doi":"10.1515/snde-2015-0037","title":"Dating US business cycles with macro factors","year":2016,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","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":"University of Alberta","funders":"","keywords":"Econometrics; Probit model; Macro; Autoregressive model; Recession; Factor analysis; Probit; Markov chain; Statistics; Dynamic factor; False positives and false negatives; Economics; Sample (material); False positive paradox; Mathematics; Computer science","authors":[{"name":"Sebastian Fossati","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1488632450882654,"gpt":0.265448184026938,"spread":0.1165849389386726,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002336236,0.0003491316,0.0002854986,0.002950733,0.0002263295,0.001161675,0.0002290059,0.0004227506,0.003039924],"category_scores_gemma":[0.02824121,0.0003122244,0.0004087988,0.002614487,0.0003384791,0.0009614772,0.0007842018,0.0008647207,0.0008051064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006663298,"about_ca_system_score_gemma":0.0004297452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01338406,"about_ca_topic_score_gemma":0.009081587,"domain_scores_codex":[0.9992087,0.0003929776,0.00004227947,0.0001740148,0.0001397991,0.000042215],"domain_scores_gemma":[0.991851,0.004888603,0.001066861,0.0009058714,0.00107321,0.0002143326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002395599,0.0000586386,0.6155221,0.00008952992,0.0002354044,0.00009570394,0.0006271424,0.2125997,0.0007415976,0.02478108,0.01234074,0.1326688],"study_design_scores_gemma":[0.00002494195,0.00005907761,0.2527303,0.0001307185,0.00004576165,0.00007223059,0.0002255593,0.6952725,0.001209949,0.03761169,0.01256475,0.00005265688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8233172,0.000790332,0.1533515,0.0007752386,0.0001404191,0.0001170635,0.008850833,0.001020446,0.01163694],"genre_scores_gemma":[0.9751153,0.0002573964,0.01914117,0.00004824528,0.00004870786,0.00005375153,0.004355486,0.00009883064,0.0008811565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01338406,"threshold_uncertainty_score":0.02661228,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2006358329","doi":"10.1515/snde-2013-0020","title":"Bayesian adaptively updated Hamiltonian Monte Carlo with an application to high-dimensional BEKK GARCH models","year":2013,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Financial Risk and Volatility Modeling","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":"University of Toronto","funders":"","keywords":"Markov chain Monte Carlo; Parameter space; Curse of dimensionality; Monte Carlo method; Markov chain; Sample space; Mathematics; Applied mathematics; Statistical physics; Computer science; Mathematical optimization; Statistics; Physics","authors":[{"name":"Martin Burda","is_ca":true},{"name":"John M. Maheu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04481076198546601,"gpt":0.2532914372041248,"spread":0.2084806752186588,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002570671,0.0004190852,0.00100459,0.000627099,0.0005434222,0.0007419381,0.001260916,0.001128085,0.001748811],"category_scores_gemma":[0.01147868,0.0004902395,0.0005293337,0.0008352315,0.001172814,0.001024066,0.001475587,0.001606377,0.0001648672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008401073,"about_ca_system_score_gemma":0.001264126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008913659,"about_ca_topic_score_gemma":0.007454738,"domain_scores_codex":[0.9990726,0.0006158656,0.00002878368,0.00008251364,0.0001600666,0.00004016633],"domain_scores_gemma":[0.9942917,0.00467246,0.0002284957,0.0003160744,0.0003490499,0.0001422599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000584413,0.00002998585,0.001104425,0.00005064025,0.00004980002,0.0001339928,0.0001224331,0.8751388,0.0008704056,0.08900352,0.0004592887,0.03297834],"study_design_scores_gemma":[0.000003861664,0.00000407957,0.00006271152,0.000001982933,0.000002199563,0.000006307876,0.000002520114,0.9919062,0.00008126488,0.007786354,0.0001386172,0.000004015109],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02607428,0.0004239457,0.9718983,0.0002511417,0.00002774758,0.0000348121,0.00003655304,0.0002252716,0.001027892],"genre_scores_gemma":[0.5595534,0.0005138579,0.4372427,0.0001423989,0.00008928122,0.0001620802,0.0001255196,0.000136629,0.002034243],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008913659,"threshold_uncertainty_score":0.01772356,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1729963006","doi":"10.2202/1558-3708.1645","title":"Mixed Exponential Power Asymmetric Conditional Heteroskedasticity","year":2009,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"","keywords":"Conditional variance; Stylized fact; Heteroscedasticity; Mathematics; Exponential function; Autoregressive conditional heteroskedasticity; Econometrics; Conditional probability distribution; Natural exponential family; Component (thermodynamics); Series (stratigraphy); Applied mathematics; Statistics; Economics; Mathematical analysis; Volatility (finance); Physics","authors":[{"name":"Jeroen V.K. Rombouts","is_ca":true},{"name":"Mohammed Bouaddi","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.081989958988696,"gpt":0.277243565257053,"spread":0.195253606268357,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00322368,0.0007279612,0.001028462,0.001296759,0.0003866381,0.001554041,0.001788458,0.000894236,0.005050561],"category_scores_gemma":[0.0128697,0.0004585391,0.001381845,0.001207246,0.001383565,0.003552762,0.00112484,0.001886387,0.0007960837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008808375,"about_ca_system_score_gemma":0.0005119589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001096743,"about_ca_topic_score_gemma":0.001189914,"domain_scores_codex":[0.9983925,0.0004408312,0.000109698,0.0003782345,0.0004578724,0.0002208491],"domain_scores_gemma":[0.994068,0.003013888,0.0008029356,0.001161061,0.0007711604,0.0001828144],"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":[0.0001303554,0.00007241144,0.006967567,0.00009274698,0.0001514218,0.0006317022,0.000207958,0.1097533,0.005308426,0.8367702,0.001611136,0.03830268],"study_design_scores_gemma":[0.00002649359,0.00004131633,0.002324959,0.00001556476,0.00003135229,0.000430703,0.00003177521,0.7318996,0.001891155,0.2612568,0.002013771,0.0000364888],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07247926,0.0002296371,0.922289,0.0002093471,0.00003968368,0.00004929007,0.0001747588,0.0002810008,0.004247946],"genre_scores_gemma":[0.9414492,0.0002661182,0.05156557,0.0001376345,0.0001316977,0.000105664,0.0003344364,0.00009599451,0.005913825],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005050561,"threshold_uncertainty_score":0.01704872,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4313855166","doi":"10.1515/snde-2022-0029","title":"Volatility and dependence in cryptocurrency and financial markets: a copula approach","year":2023,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Cryptocurrency; Economics; Copula (linguistics); Econometrics; Volatility (finance); Autoregressive conditional heteroskedasticity; Stock (firearms); Tail dependence; Financial market; Financial economics; Statistics; Mathematics; Finance","authors":[{"name":"Jinan Liu","is_ca":false},{"name":"Apostolos Serletis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0606410353323016,"gpt":0.2780736397478486,"spread":0.217432604415547,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002218476,0.0007176002,0.001194787,0.001444866,0.0004524463,0.001926607,0.0009541715,0.001099467,0.003142618],"category_scores_gemma":[0.01102465,0.000663359,0.001525371,0.001030929,0.001029539,0.002027324,0.0009630329,0.001680244,0.0003527682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000835478,"about_ca_system_score_gemma":0.0008835942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01150711,"about_ca_topic_score_gemma":0.004986799,"domain_scores_codex":[0.9993332,0.0003002619,0.00002592338,0.0001243164,0.0001079941,0.000108211],"domain_scores_gemma":[0.9938398,0.004607283,0.0006679151,0.0002912217,0.000347648,0.000246103],"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":[0.0001379475,0.0001974121,0.03435634,0.0001097203,0.0007294768,0.000871562,0.0002819913,0.7865615,0.003201848,0.1562538,0.002230376,0.01506807],"study_design_scores_gemma":[0.00000580515,0.00001780129,0.003714036,0.000007862971,0.00003280002,0.00004537298,0.00002388276,0.9816047,0.0001567568,0.01416332,0.0002133619,0.00001438335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6835865,0.0011902,0.3054752,0.001497483,0.00007020371,0.00006939375,0.00046477,0.0002993545,0.007346877],"genre_scores_gemma":[0.9910773,0.0003877372,0.005615188,0.00007746125,0.0000505391,0.00002518696,0.0001605253,0.00005630134,0.002549812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01150711,"threshold_uncertainty_score":0.02288026,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2336934996","doi":"10.1515/snde-2014-0064","title":"Common time variation of parameters in reduced-form macroeconomic models","year":2015,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Econometrics; Stochastic volatility; Economics; Volatility (finance); Yield curve; Dynamic factor; Factor analysis; Vector autoregression; Predictive power; Interest rate; Mathematics; Finance","authors":[{"name":"Dalibor Stevanović","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1889967734190328,"gpt":0.2809049477482292,"spread":0.09190817432919635,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004349953,0.0007813995,0.001086516,0.001326449,0.0003835904,0.00253581,0.00152916,0.001691016,0.002749828],"category_scores_gemma":[0.02568355,0.0008818934,0.001868564,0.001570392,0.001626819,0.00338205,0.00168109,0.002370985,0.0004944399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00123123,"about_ca_system_score_gemma":0.0007483881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006755415,"about_ca_topic_score_gemma":0.003485231,"domain_scores_codex":[0.9974365,0.001206155,0.0001498466,0.0006545581,0.0003511287,0.0002019644],"domain_scores_gemma":[0.9898117,0.006267865,0.001862382,0.001334273,0.0005367561,0.0001869506],"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":[0.00005105141,0.00004016656,0.006618283,0.0000927095,0.0002537957,0.0002681554,0.0003358813,0.5818719,0.0006698903,0.3956113,0.001737857,0.01244901],"study_design_scores_gemma":[0.00001093653,0.00001635741,0.00198046,0.00002765216,0.00003549442,0.0000651635,0.00003682525,0.7785237,0.0001479722,0.2173983,0.001726505,0.0000306636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1452946,0.001122625,0.8436038,0.001562187,0.0001405476,0.00006084756,0.000802143,0.0005008724,0.006912346],"genre_scores_gemma":[0.9704068,0.001050384,0.02358697,0.0001448228,0.0001210803,0.00009461353,0.0007041462,0.0001251579,0.00376587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006755415,"threshold_uncertainty_score":0.02300501,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2749312791","doi":"10.1515/snde-2016-0078","title":"Markov-switching quantile autoregression: a Gibbs sampling approach","year":2017,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Gibbs sampling; Quantile; Mathematics; Markov chain Monte Carlo; Markov chain; Bayesian probability; Conditional probability distribution; Inference; Importance sampling; Econometrics; Applied mathematics; Statistics; Monte Carlo method; Computer science; Artificial intelligence","authors":[{"name":"Xiaochun Liu","is_ca":false},{"name":"Richard Luger","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2932449140420484,"gpt":0.448795607896254,"spread":0.1555506938542056,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004290731,0.0004519338,0.0008881125,0.0007401099,0.0004318385,0.0009292729,0.001686756,0.0007910195,0.003120274],"category_scores_gemma":[0.01199518,0.0005991152,0.000912139,0.0009498631,0.001161664,0.001099917,0.001162269,0.001550679,0.0003949952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009539525,"about_ca_system_score_gemma":0.001065969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005948212,"about_ca_topic_score_gemma":0.005745206,"domain_scores_codex":[0.998535,0.001010772,0.00003537142,0.0001677208,0.0001701058,0.00008103967],"domain_scores_gemma":[0.9948518,0.004194752,0.0001896034,0.0003902681,0.0002802742,0.00009335601],"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":[0.0000891735,0.00007028144,0.002551818,0.00006653903,0.0001063118,0.0001285598,0.0001794502,0.5818846,0.0008036384,0.3596352,0.001610942,0.05287341],"study_design_scores_gemma":[0.00001157497,0.000006756602,0.0001963598,0.000008747154,0.00001033115,0.00001014692,0.000005728563,0.93455,0.000133351,0.06446516,0.0005941533,0.000007600115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007545788,0.0001527809,0.991039,0.0001848688,0.00002400492,0.00002592068,0.00003883881,0.0001384263,0.0008503714],"genre_scores_gemma":[0.5839356,0.0007467113,0.4103277,0.0002780067,0.000224434,0.0003443345,0.0003712691,0.0001863392,0.003585734],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005948212,"threshold_uncertainty_score":0.02269185,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1538303026","doi":"10.1515/snde-2012-0039","title":"Persistence in real exchange rate convergence","year":2013,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Purchasing power parity; Econometrics; Mean reversion; Economics; Convergence (economics); Exchange rate; Pairwise comparison; Long memory; Relative purchasing power parity; Statistics; Mathematics; Macroeconomics","authors":[{"name":"Thanasis Stengos","is_ca":true},{"name":"M. Ege Yazgan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08723266715667224,"gpt":0.2685153863046844,"spread":0.1812827191480121,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002871441,0.000172248,0.0003922706,0.001609171,0.0002340961,0.001737182,0.0003349475,0.0005858553,0.003134535],"category_scores_gemma":[0.02050711,0.0001462323,0.0003522461,0.001241714,0.0007513561,0.001573821,0.0009539129,0.0008829104,0.0003365613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003861852,"about_ca_system_score_gemma":0.000206062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001707793,"about_ca_topic_score_gemma":0.0008480072,"domain_scores_codex":[0.9992174,0.0002778806,0.00008613725,0.0002025742,0.0001080085,0.0001080073],"domain_scores_gemma":[0.9871609,0.0061343,0.004232157,0.001265625,0.0008469388,0.0003600439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003697529,0.00007869213,0.894873,0.0001212279,0.0002582308,0.0005562222,0.001402541,0.02354711,0.001235571,0.03041855,0.001193404,0.04594565],"study_design_scores_gemma":[0.00005109811,0.0002058602,0.8677407,0.0001717817,0.0001131969,0.0006548946,0.00165831,0.07076905,0.002237432,0.05231233,0.004013385,0.00007204738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990227,0.000530351,0.004652032,0.0003988658,0.00001295503,0.000006167147,0.0002000027,0.00003008448,0.003942467],"genre_scores_gemma":[0.9994546,0.00005442881,0.0001772803,0.0000163681,0.000008616997,0.000002091998,0.00008784594,0.000003070979,0.0001957316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003134535,"threshold_uncertainty_score":0.01518577,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2901691799","doi":"10.1515/snde-2017-0101","title":"Modeling time-variation over the business cycle (1960–2017): an international perspective","year":2018,"lang":"en","type":"preprint","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Economics; Business cycle; Openness to experience; Globalization; Volatility (finance); Stochastic volatility; Inflation (cosmology); Deflation; Econometrics; Great recession; Monetary economics; Macroeconomics; Monetary policy; Keynesian economics","authors":[{"name":"Enrique Martínez‐García","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1327809250555425,"gpt":0.3072279455550035,"spread":0.174447020499461,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001282294,0.0003798282,0.000432723,0.001193319,0.0002309674,0.002108887,0.0004915703,0.0007235239,0.002082757],"category_scores_gemma":[0.005622862,0.0001884279,0.0006535028,0.002353647,0.0005493401,0.001632977,0.0009262401,0.001349931,0.0002713519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007977001,"about_ca_system_score_gemma":0.0005588814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0160406,"about_ca_topic_score_gemma":0.007071027,"domain_scores_codex":[0.9996605,0.0001521712,0.00002035222,0.00008484905,0.00005469794,0.00002738884],"domain_scores_gemma":[0.9987758,0.000705393,0.0002420057,0.0001069846,0.0001166298,0.00005311483],"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":[0.00008564535,0.00009744806,0.06326453,0.0002047866,0.0003389215,0.0003664753,0.0005555032,0.6062322,0.001004321,0.2528726,0.007361685,0.06761584],"study_design_scores_gemma":[0.00001529718,0.00008271093,0.01817033,0.0003529842,0.0001236886,0.0001229295,0.0004374934,0.8227479,0.0004617237,0.1153789,0.04206297,0.00004309136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4986161,0.02426093,0.3835842,0.01860968,0.0007948818,0.00008017589,0.003392623,0.000353394,0.0703081],"genre_scores_gemma":[0.9713899,0.007971308,0.0163985,0.0003561499,0.0003595711,0.00003927518,0.001003436,0.00007420282,0.002407707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0160406,"threshold_uncertainty_score":0.03189445,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2810067254","doi":"10.1515/snde-2016-0061","title":"A hidden Markov regime-switching smooth transition model","year":2018,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Hidden Markov model; Hidden semi-Markov model; Expectation–maximization algorithm; Series (stratigraphy); Markov chain; Class (philosophy); Parametric statistics; Parametric model; Nonlinear system; Computer science; Markov model; Filter (signal processing); Statistical physics; State (computer science); Variable-order Markov model; Algorithm; Mathematics; Maximum likelihood; Artificial intelligence; Machine learning; Physics; Statistics","authors":[{"name":"Robert J. Elliott","is_ca":true},{"name":"Tak Kuen Siu","is_ca":false},{"name":"John W. Lau","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06591911510982278,"gpt":0.2781397815892375,"spread":0.2122206664794147,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001200603,0.0003808358,0.0007893882,0.0007426615,0.0003414877,0.001197735,0.001049443,0.001083052,0.00335133],"category_scores_gemma":[0.003440037,0.0002963052,0.0008685929,0.0006968892,0.0009420046,0.001238862,0.0008503643,0.001300131,0.0004266609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006100086,"about_ca_system_score_gemma":0.0006511193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00391169,"about_ca_topic_score_gemma":0.002045754,"domain_scores_codex":[0.9993939,0.0002211217,0.00002397594,0.000138586,0.0001381136,0.00008434814],"domain_scores_gemma":[0.9985562,0.0009476453,0.0001915032,0.0001043737,0.0001365789,0.0000637137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008993473,0.00006770152,0.003406817,0.00009112286,0.0001098108,0.0003512025,0.0002101243,0.610127,0.002621548,0.359725,0.002201839,0.02099796],"study_design_scores_gemma":[0.000007351195,0.00001185159,0.0003331545,0.000004979635,0.00001041776,0.000026354,0.000006845973,0.9630899,0.0001105352,0.03569745,0.0006933836,0.000007805689],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07973021,0.0004283107,0.9101219,0.0009150149,0.0001267593,0.00004430764,0.0003883661,0.0003396211,0.007905488],"genre_scores_gemma":[0.9639367,0.000345034,0.02758607,0.0001199396,0.00008188604,0.00006477787,0.0002543137,0.00003975571,0.007571565],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00391169,"threshold_uncertainty_score":0.01121134,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1999245127","doi":"10.2202/1558-3708.1376","title":"A New Application of Exact Nonparametric Methods to Long-Horizon Predictability Tests","year":2007,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":7,"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":"Predictability; Econometrics; Nonparametric statistics; Unit root; Horizon; Inference; Autoregressive model; Estimator; Statistical hypothesis testing; Statistics; Mathematics; Computer science; Artificial intelligence","authors":[{"name":"Wei Liu","is_ca":true},{"name":"Alex Maynard","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04833392276072366,"gpt":0.330978773919571,"spread":0.2826448511588474,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01171476,0.0008722895,0.001456424,0.00277068,0.000649836,0.001760356,0.002530502,0.001605341,0.004459933],"category_scores_gemma":[0.1075152,0.0005718008,0.001259792,0.002909531,0.002569707,0.004110667,0.002988465,0.003283021,0.0006767845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006046065,"about_ca_system_score_gemma":0.001828003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001600515,"about_ca_topic_score_gemma":0.001745151,"domain_scores_codex":[0.9894662,0.006595799,0.0005250814,0.001003341,0.002118509,0.0002908533],"domain_scores_gemma":[0.9247472,0.05925556,0.003708813,0.008492221,0.00333368,0.0004624743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002761234,0.0002769423,0.01028336,0.0003083233,0.0003941451,0.0007125443,0.0003939519,0.100832,0.004221579,0.3785947,0.003995735,0.4997106],"study_design_scores_gemma":[0.00007477844,0.000243242,0.004904625,0.0000612094,0.0000695765,0.0004841621,0.00006757466,0.5968599,0.001947177,0.3894848,0.005708242,0.00009474242],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00575195,0.0001568817,0.9922854,0.0001449811,0.00006714297,0.00003172351,0.0000752513,0.0003232793,0.001163408],"genre_scores_gemma":[0.3499167,0.0003948266,0.6448314,0.0003967112,0.0004296791,0.0003458649,0.0003143237,0.0003212867,0.003049202],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01171476,"threshold_uncertainty_score":0.06195432,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3125402642","doi":"10.1515/snde-2019-0106","title":"Money growth variability and output: evidence with credit card-augmented Divisia monetary aggregates","year":2020,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Divisia index; Divisia monetary aggregates index; Economics; Volatility (finance); Credit card; Monetary economics; Monetary policy; Aggregate demand; Bivariate analysis; Econometrics; Payment; Central bank; Finance; Quantitative easing","authors":[{"name":"Jinan Liu","is_ca":true},{"name":"Apostolos Serletis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.153251403867766,"gpt":0.2573898728367144,"spread":0.1041384689689484,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002181267,0.0003355718,0.0005218143,0.000960983,0.0003068864,0.002087868,0.0005453234,0.0006361667,0.001919556],"category_scores_gemma":[0.01427467,0.0001956637,0.0003680657,0.001900879,0.0007913003,0.001211046,0.001401408,0.001138765,0.0004706449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005094963,"about_ca_system_score_gemma":0.0002469198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005260104,"about_ca_topic_score_gemma":0.001930822,"domain_scores_codex":[0.9991893,0.0002908545,0.00007625063,0.0001888339,0.0001800262,0.00007473268],"domain_scores_gemma":[0.9873713,0.004890508,0.004647689,0.00129221,0.001305743,0.0004926077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001641833,0.0001482553,0.9535403,0.0001066302,0.0004560149,0.0005948009,0.0004716984,0.01408003,0.001428008,0.005721948,0.002075032,0.01973535],"study_design_scores_gemma":[0.00006940656,0.0002374346,0.9454862,0.00007457785,0.0002278196,0.0001761026,0.0007010616,0.04032737,0.001539966,0.007297498,0.003805745,0.00005675186],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964629,0.0003745978,0.0006416438,0.0004037999,0.00002313272,0.00000437816,0.0004991864,0.00002195078,0.001568487],"genre_scores_gemma":[0.9991695,0.0001231526,0.00008605512,0.00002199825,0.00003535304,0.000001962594,0.0003768498,0.000004262026,0.000180873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005260104,"threshold_uncertainty_score":0.01153576,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2026408188","doi":"10.1515/1558-3708.1876","title":"Estimation of a Nonlinear Taylor Rule Using Real-Time U.S. Data","year":2012,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Brock University","funders":"","keywords":"Taylor rule; Econometrics; Taylor series; Nonlinear system; Monetary policy; Economics; Nonlinear regression; Function (biology); Estimation; Work (physics); Regression; Statistics; Mathematics; Regression analysis; Keynesian economics; Central bank; Physics","authors":[{"name":"Jean-François Lamarche","is_ca":true},{"name":"Zisimos Koustasy","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2309335505868654,"gpt":0.3206357357525252,"spread":0.08970218516565978,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002509941,0.0004455048,0.0007008741,0.001376671,0.000379731,0.001061711,0.0005345099,0.0007179005,0.001838322],"category_scores_gemma":[0.01571564,0.0002628238,0.0005489973,0.001527956,0.0003453457,0.001204204,0.0005393984,0.001128462,0.0007371918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001043733,"about_ca_system_score_gemma":0.0009282969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03027058,"about_ca_topic_score_gemma":0.02625388,"domain_scores_codex":[0.9992995,0.0003305167,0.00005750129,0.0001575865,0.0001033258,0.00005159596],"domain_scores_gemma":[0.9929699,0.004350226,0.00152462,0.0004843977,0.000566372,0.0001044653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004056162,0.000270281,0.270951,0.0003588341,0.0004693854,0.0009022557,0.0007526147,0.5495213,0.001277424,0.04514946,0.01843592,0.1115058],"study_design_scores_gemma":[0.00004568422,0.0001053339,0.05843013,0.00008891077,0.00008270751,0.0001356749,0.0004080934,0.9088463,0.001794826,0.02200589,0.007996923,0.00005944044],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8819306,0.001889824,0.1028816,0.001799083,0.0001547156,0.00009019954,0.005507171,0.0002673498,0.005479457],"genre_scores_gemma":[0.9669927,0.0009964439,0.02318851,0.000142316,0.00006541507,0.00004924664,0.006280767,0.0000266966,0.002258015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03027058,"threshold_uncertainty_score":0.06018877,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2138918414","doi":"10.2202/1558-3708.1322","title":"A Threshold Model of Real U.S. GDP and the Problem of Constructing Confidence Intervals in TAR Models","year":2007,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Wilfrid Laurier University; Balsillie School of International Affairs","funders":"","keywords":"Confidence interval; Autoregressive model; Robust confidence intervals; Econometrics; Statistics; Series (stratigraphy); Confidence distribution; Mathematics; Monte Carlo method; Construct (python library); CDF-based nonparametric confidence interval; Computer science","authors":[{"name":"Walter Enders","is_ca":false},{"name":"Barry Falk","is_ca":false},{"name":"Pierre L. Siklos","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1685060233500239,"gpt":0.2872058439751276,"spread":0.1186998206251036,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04047006,0.0008481333,0.001860707,0.002719769,0.000823631,0.004479364,0.003781546,0.003032867,0.002571049],"category_scores_gemma":[0.2867796,0.0008452886,0.001480739,0.003088685,0.003361176,0.006817307,0.002511681,0.005095301,0.0003607552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001842409,"about_ca_system_score_gemma":0.001568324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007659537,"about_ca_topic_score_gemma":0.00291925,"domain_scores_codex":[0.9830436,0.01206575,0.0007621584,0.001643725,0.001793209,0.0006915417],"domain_scores_gemma":[0.6878793,0.2828253,0.01021906,0.01222942,0.005790457,0.001056457],"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":[0.0003228345,0.0001052896,0.01049837,0.0002239517,0.000248538,0.000258749,0.0008147839,0.4472933,0.0005913901,0.4973832,0.001858721,0.04040085],"study_design_scores_gemma":[0.00003695274,0.00004779176,0.001230435,0.00008040129,0.00003887133,0.00006250048,0.0001253256,0.6872794,0.0004939483,0.309955,0.0006115555,0.00003786197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08840731,0.0008253386,0.9050609,0.001974629,0.00008361157,0.00004092677,0.0002716095,0.0003803198,0.002955351],"genre_scores_gemma":[0.9097894,0.0005239401,0.08789607,0.0002590174,0.00008418332,0.0001561213,0.0004622279,0.00009512294,0.0007338946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04047006,"threshold_uncertainty_score":0.2140287,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2884786062","doi":"10.1515/snde-2017-0064","title":"A nonlinear model of asset returns with multiple shocks","year":2018,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Mount Allison University","funders":"","keywords":"Econometrics; Nonlinear system; Economics; Asset (computer security); Sign (mathematics); Contrast (vision); Class (philosophy); Financial economics; Mathematics; Computer science","authors":[{"name":"Hannu Kahra","is_ca":false},{"name":"Vance L. Martin","is_ca":false},{"name":"Saikat Sarkar","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06495979009861712,"gpt":0.2610800336480407,"spread":0.1961202435494235,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001969053,0.000934898,0.001135993,0.0009765881,0.0003932596,0.002377862,0.00169272,0.002019251,0.005317547],"category_scores_gemma":[0.005972852,0.0007471563,0.00124626,0.001039806,0.001469017,0.002638147,0.001322034,0.002150252,0.000798408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001615699,"about_ca_system_score_gemma":0.001054434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01413094,"about_ca_topic_score_gemma":0.006468807,"domain_scores_codex":[0.9991397,0.0002944922,0.0000349869,0.0001536206,0.0001874321,0.0001896969],"domain_scores_gemma":[0.9977995,0.001265244,0.0004043223,0.0001262578,0.0002487323,0.0001559552],"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":[0.0000642997,0.00005006424,0.002359746,0.0000295932,0.00004809124,0.0003718832,0.0001126316,0.8935632,0.000893253,0.09840309,0.0007516175,0.003352601],"study_design_scores_gemma":[0.00001044316,0.00001612784,0.00044049,0.000004231552,0.00000721577,0.00004198264,0.00001386565,0.9843775,0.00006641981,0.01474949,0.0002610815,0.00001113099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3316292,0.0004710293,0.6358236,0.002806826,0.0001260066,0.0001514197,0.001080905,0.0004948904,0.02741607],"genre_scores_gemma":[0.9672157,0.0003773906,0.007125624,0.00013579,0.00005689286,0.0001075938,0.0002106153,0.00007175024,0.02469877],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01413094,"threshold_uncertainty_score":0.02809739,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389724734","doi":"10.1515/snde-2022-0108","title":"Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis","year":2023,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Bank of Canada","funders":"","keywords":"Prior probability; Bayesian probability; Shrinkage; Flexibility (engineering); Function (biology); Computer science; Probability density function; Contrast (vision); Mathematics; Bayesian inference; Algorithm; Econometrics; Statistics; Artificial intelligence","authors":[{"name":"Tony Chernis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08593460766345094,"gpt":0.259872711908942,"spread":0.173938104245491,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01776379,0.001829227,0.002472172,0.00297925,0.001034313,0.003178941,0.002142242,0.001717048,0.0124559],"category_scores_gemma":[0.07722754,0.001558794,0.001969349,0.002435295,0.00232522,0.005006359,0.003653483,0.003263294,0.001206159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001987466,"about_ca_system_score_gemma":0.001932832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006592226,"about_ca_topic_score_gemma":0.005563125,"domain_scores_codex":[0.9933723,0.003959861,0.0003087419,0.0008330406,0.00127411,0.0002519864],"domain_scores_gemma":[0.9464948,0.04635001,0.001785874,0.002816912,0.002162633,0.0003897687],"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":[0.0001856312,0.00006539176,0.001630085,0.0001924759,0.0002172246,0.0001217416,0.0002199593,0.7732661,0.0004819323,0.1319715,0.002225788,0.08942221],"study_design_scores_gemma":[0.00002394306,0.00002223163,0.00020883,0.00005802004,0.00003385199,0.000009936855,0.00002282378,0.8259078,0.0004610358,0.1722707,0.0009578015,0.00002297762],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01406995,0.0002743085,0.9792833,0.0005745979,0.0000624829,0.0001045083,0.0002252034,0.0005113368,0.004894345],"genre_scores_gemma":[0.6010364,0.0005537949,0.3893022,0.0004958867,0.0002448009,0.0005908424,0.00122044,0.0003914191,0.006164187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01776379,"threshold_uncertainty_score":0.09394503,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979460031","doi":"10.1515/snde-2012-0002","title":"Real vs. nominal cycles: a multistate Markov-switching bi-factor approach","year":2013,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Bank of Canada","funders":"","keywords":"Business cycle; Recession; Deflation; Economics; Shock (circulatory); Demand shock; Inflation (cosmology); Supply shock; Monetary economics; Econometrics; Markov chain; Keynesian economics; Monetary policy; Macroeconomics; Statistics; Mathematics","authors":[{"name":"Danilo Leiva‐León","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1151987673556419,"gpt":0.2713897513322946,"spread":0.1561909839766527,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002463838,0.0008798531,0.001786544,0.001159646,0.0006942922,0.001797378,0.001779443,0.002027974,0.006572068],"category_scores_gemma":[0.006959319,0.001147704,0.001841878,0.001064379,0.001342983,0.001716986,0.001352189,0.00186674,0.0006588045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001439535,"about_ca_system_score_gemma":0.00122856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03134135,"about_ca_topic_score_gemma":0.01711386,"domain_scores_codex":[0.9992583,0.0003195723,0.00003237638,0.0001959027,0.00007833653,0.0001153641],"domain_scores_gemma":[0.9955158,0.003440699,0.0004474396,0.0001527898,0.0002815705,0.0001616854],"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":[0.00007159459,0.00002565932,0.001783887,0.00002853953,0.00006520638,0.00009809674,0.00004674177,0.9640769,0.000191477,0.02982909,0.0003754967,0.003407287],"study_design_scores_gemma":[0.000004884047,0.000006854285,0.0001859736,0.000003491477,0.000009142982,0.000006031788,0.000006264302,0.9936553,0.00001649453,0.006000202,0.00009901551,0.00000633682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1346815,0.0007559951,0.8548284,0.001538758,0.0001430668,0.0001027178,0.0009622524,0.0003303353,0.006656838],"genre_scores_gemma":[0.964589,0.000797817,0.02410043,0.0001613408,0.0001359417,0.0001771817,0.0006159915,0.00007013364,0.009352214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03134135,"threshold_uncertainty_score":0.06231785,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3092049788","doi":"10.1515/snde-2019-0091","title":"Modeling time-varying parameters using artificial neural networks: a GARCH illustration","year":2020,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Heteroscedasticity; Autoregressive conditional heteroskedasticity; Autoregressive model; Econometrics; Artificial neural network; Volatility (finance); Computer science; Stochastic volatility; Markov chain; Mathematics; Artificial intelligence; Machine learning","authors":[{"name":"Morvan Nongni Donfack","is_ca":true},{"name":"Arnaud Dufays","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1906406467301315,"gpt":0.2931324891227887,"spread":0.1024918423926571,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001167115,0.0003546128,0.0003738049,0.0003308856,0.0002504218,0.0006420212,0.0008135876,0.001146211,0.001226317],"category_scores_gemma":[0.002569453,0.0002158831,0.0004997384,0.0005153025,0.0006497861,0.001046046,0.0005593635,0.001065393,0.0001267527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004664219,"about_ca_system_score_gemma":0.0003690184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004114046,"about_ca_topic_score_gemma":0.002851086,"domain_scores_codex":[0.9997088,0.0001277781,0.00001575668,0.00005726512,0.00006165826,0.0000286969],"domain_scores_gemma":[0.999408,0.0003448876,0.0000858643,0.00007166162,0.0000679545,0.00002169936],"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":[0.00002516561,0.00002180405,0.001856788,0.00001870749,0.00004280762,0.0001033377,0.00005143253,0.9355558,0.001454187,0.04717312,0.000294828,0.013402],"study_design_scores_gemma":[0.000001616713,0.000004220001,0.0001414366,0.000001592953,0.000003163156,0.000008008675,0.000002331811,0.9935722,0.0001415172,0.005988011,0.0001330178,0.000002892837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1151469,0.0002730536,0.8789654,0.0006730531,0.00008349484,0.00002215964,0.00008658813,0.0002458062,0.004503511],"genre_scores_gemma":[0.9568095,0.0002115503,0.04086911,0.00006134983,0.00003457925,0.00002770974,0.00004170291,0.00002474928,0.00191973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004114046,"threshold_uncertainty_score":0.008180141,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389740075","doi":"10.1515/snde-2022-0084","title":"Power of Unit Root Tests Against Nonlinear and Noncausal Alternatives with an Application to the Brent Crude Oil Price","year":2023,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Unit root; Nonlinear system; Unit root test; Brent Crude; Econometrics; Sample (material); Mathematics; Power (physics); Augmented Dickey–Fuller test; Series (stratigraphy); Applied mathematics; Mathematical optimization; Cointegration","authors":[{"name":"Frédérique Bec","is_ca":false},{"name":"Alain Guay","is_ca":true},{"name":"Heino Bohn Nielsen","is_ca":false},{"name":"Sarra Saïdi","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03935043239263327,"gpt":0.290572656410064,"spread":0.2512222240174308,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02898405,0.0004814865,0.001380731,0.00193472,0.0005228003,0.001247241,0.001461488,0.00121889,0.002460354],"category_scores_gemma":[0.1642689,0.0002242636,0.0009479897,0.001521545,0.002481015,0.001874062,0.001199315,0.001160427,0.0001751143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007022497,"about_ca_system_score_gemma":0.0008029014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001750432,"about_ca_topic_score_gemma":0.0009595544,"domain_scores_codex":[0.9872503,0.0101706,0.0003495162,0.0008161298,0.001190202,0.000223213],"domain_scores_gemma":[0.5961259,0.3901503,0.003888617,0.006403229,0.00264564,0.0007862717],"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":[0.00364986,0.0005420648,0.08624602,0.0005511866,0.001400782,0.001435884,0.0006857472,0.5875459,0.006452568,0.1069857,0.002094597,0.2024096],"study_design_scores_gemma":[0.000226553,0.0007021639,0.0106278,0.00004577332,0.0001184363,0.0002106035,0.0001777957,0.951309,0.003279803,0.03267195,0.0005723223,0.0000579011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6479707,0.001017859,0.3456771,0.0007098504,0.0001109349,0.0001158825,0.000229531,0.0003973156,0.00377094],"genre_scores_gemma":[0.9802566,0.00007838364,0.01925946,0.00002828879,0.00002646391,0.00003507948,0.00009419772,0.00003073192,0.0001908378],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02898405,"threshold_uncertainty_score":0.1532842,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3172812884","doi":"10.1515/snde-2023-0052","title":"Quasi-Maximum Likelihood for Estimating Structural Models","year":2025,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"Canadian Statistical Sciences Institute; Natural Sciences and Engineering Research Council of Canada","keywords":"Econometrics; Seniority; Bankruptcy; Structural estimation; Asset (computer security); Likelihood function; Economics; Maximum likelihood; Value (mathematics); Markov chain; Equity (law); Debt; Bellman equation; Payment; Actuarial science; Mathematics; Computer science; Statistics; Mathematical economics; Finance; Engineering","authors":[{"name":"Malek Ben-Abdellatif","is_ca":false},{"name":"Hatem Ben‐Ameur","is_ca":true},{"name":"Rim Chérif","is_ca":false},{"name":"Tarek Fakhfakh","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05534261128810941,"gpt":0.3011990330403963,"spread":0.2458564217522869,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01003438,0.001610764,0.00234546,0.002348545,0.0008818015,0.002220672,0.003522948,0.002406774,0.007489387],"category_scores_gemma":[0.04651648,0.002371794,0.001945411,0.003200423,0.002116971,0.003180379,0.002445172,0.004232335,0.001628626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002144506,"about_ca_system_score_gemma":0.003372309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009338666,"about_ca_topic_score_gemma":0.01031,"domain_scores_codex":[0.9939193,0.004929485,0.0001597528,0.0004503221,0.0003811644,0.0001601004],"domain_scores_gemma":[0.9512083,0.04469648,0.001303996,0.001733522,0.0008439003,0.0002138298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008215175,0.00009294145,0.001711909,0.0003637611,0.0001964619,0.000158749,0.0001682236,0.7467544,0.0004936801,0.2030191,0.002710527,0.04424818],"study_design_scores_gemma":[0.00001530774,0.00001308611,0.0001455228,0.00002101944,0.000007888892,0.0000151695,0.00001287564,0.9080758,0.0001109834,0.09083918,0.0007314557,0.00001162523],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001955653,0.000270214,0.9965472,0.0002269449,0.00001642808,0.000042194,0.000155397,0.0002092931,0.0005766909],"genre_scores_gemma":[0.1877286,0.001083738,0.803958,0.0002472537,0.0001989636,0.0008435101,0.001907757,0.0004831632,0.003549032],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01003438,"threshold_uncertainty_score":0.05306751,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3207902490","doi":"10.1515/snde-2018-0120","title":"Recovering cointegration via wavelets in the presence of non-linear patterns","year":2021,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"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":"Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España","keywords":"Cointegration; Bivariate analysis; Econometrics; Wavelet; Economics; Consumption (sociology); Series (stratigraphy); Monte Carlo method; Mathematics; Statistics; Computer science; Geology; Artificial intelligence","authors":[{"name":"Jorge Martínez Compains","is_ca":true},{"name":"Ignacio Rodríguez","is_ca":false},{"name":"Ramazan Gençay","is_ca":true},{"name":"Tommaso Trani","is_ca":false},{"name":"Daniel Ramos Vilardell","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05127134568834545,"gpt":0.2787771913865835,"spread":0.2275058456982381,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003833237,0.0003480162,0.0004945431,0.001117347,0.000249778,0.001014151,0.0003632338,0.0005888366,0.001250834],"category_scores_gemma":[0.02560888,0.0002271863,0.0003809491,0.001493738,0.0005222911,0.001181935,0.0006639337,0.000929315,0.0002061282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002321592,"about_ca_system_score_gemma":0.0004398968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002155689,"about_ca_topic_score_gemma":0.000982789,"domain_scores_codex":[0.9990452,0.0004703209,0.00006573991,0.0001506964,0.0001788039,0.00008926169],"domain_scores_gemma":[0.9864976,0.01058702,0.001155982,0.001096466,0.0005121275,0.0001507687],"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":[0.000831353,0.0003326799,0.2208714,0.0002687135,0.0004592853,0.001640748,0.0008620786,0.4181516,0.02251103,0.07571544,0.002596571,0.2557591],"study_design_scores_gemma":[0.00002470011,0.00006440139,0.02101837,0.00001816776,0.00003140472,0.00006505863,0.0001372799,0.9571514,0.001689849,0.01934539,0.0004391797,0.00001481203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8508204,0.0001819117,0.1475849,0.0002571164,0.0000349082,0.00001741352,0.0001674701,0.0000882591,0.0008477347],"genre_scores_gemma":[0.9883353,0.00009008768,0.01120147,0.00001208227,0.0000150812,0.000008222825,0.0001456833,0.0000107658,0.00018142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003833237,"threshold_uncertainty_score":0.02027231,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3124418441","doi":"10.1515/snde-2014-0034","title":"Fourier inversion formulas for multiple-asset option pricing","year":2015,"lang":"en","type":"preprint","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Bank of Canada; Bank of Canada","funders":"","keywords":"Stochastic game; Inversion (geology); Fourier transform; Asset (computer security); Valuation of options; Affine transformation; Mathematical economics; Mathematics; Mathematical optimization; Econometrics; Applied mathematics; Computer science; Pure mathematics; Mathematical analysis; Geology","authors":[{"name":"Bruno Feunou","is_ca":true},{"name":"Ernest Tafolong","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1185689941422555,"gpt":0.3070193021715698,"spread":0.1884503080293143,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001658654,0.0005940625,0.0005411743,0.001017836,0.000261514,0.001217918,0.0009705913,0.001153034,0.006131321],"category_scores_gemma":[0.007421211,0.0002621113,0.0008787384,0.0007211104,0.0009704558,0.002723056,0.0008730856,0.002042969,0.0005897021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006699929,"about_ca_system_score_gemma":0.0007947311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001788187,"about_ca_topic_score_gemma":0.001209812,"domain_scores_codex":[0.9996418,0.0001170582,0.00001789191,0.00003388735,0.0001501092,0.00003927486],"domain_scores_gemma":[0.9986052,0.0008342177,0.0001389619,0.00009570485,0.000254298,0.00007165993],"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":[0.00002274553,0.00005270398,0.0003797974,0.00005288513,0.00001367708,0.0001934509,0.00009932886,0.100696,0.002427011,0.8702904,0.001330293,0.02444174],"study_design_scores_gemma":[0.0000060617,0.000007768375,0.00008556732,0.000007660859,0.000003375186,0.00006207323,0.00001526336,0.863937,0.000308453,0.1348771,0.0006801507,0.000009518157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03302822,0.0005311182,0.9545539,0.000511047,0.00009144927,0.00003558847,0.00006276304,0.0001180161,0.01106794],"genre_scores_gemma":[0.7993694,0.00111323,0.1822976,0.0002387796,0.0002393879,0.0001057143,0.0001687478,0.0001929927,0.01627412],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006131321,"threshold_uncertainty_score":0.02051133,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2809413141","doi":"10.1515/snde-2017-0043","title":"Regime switching with structural breaks in output convergence","year":2018,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"","keywords":"Autoregressive fractionally integrated moving average; Convergence (economics); Context (archaeology); Divergence (linguistics); Markov chain; Econometrics; Applied mathematics; Path (computing); Mathematics; Computer science; Statistical physics; Long memory; Economics; Statistics; Physics","authors":[{"name":"Fuat Can Beylunioğlu","is_ca":false},{"name":"Thanasis Stengos","is_ca":true},{"name":"M. Ege Yazgan","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0519071585293314,"gpt":0.2653287136340263,"spread":0.2134215551046949,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003919946,0.0002028896,0.0006503769,0.001106489,0.0005005255,0.001702242,0.0006964891,0.00116224,0.005130162],"category_scores_gemma":[0.02874609,0.0002459595,0.0008055581,0.0008583381,0.00167271,0.001603094,0.001323928,0.00187103,0.0002680976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001102674,"about_ca_system_score_gemma":0.0003923762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003083632,"about_ca_topic_score_gemma":0.001549758,"domain_scores_codex":[0.9989284,0.0004464857,0.0000661098,0.0002148734,0.0001337234,0.0002104109],"domain_scores_gemma":[0.9864047,0.008286119,0.002785552,0.001423145,0.0006731517,0.0004273228],"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":[0.0006834358,0.0003387076,0.2356947,0.0002354748,0.0004562087,0.00175224,0.00213948,0.3351577,0.006488087,0.3551397,0.002991978,0.05892227],"study_design_scores_gemma":[0.00004969829,0.0001421407,0.1069749,0.00007188422,0.00006338632,0.0003875768,0.0007018123,0.6490682,0.001709078,0.2388189,0.00194729,0.00006515787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9619264,0.0001813451,0.02926377,0.0007213494,0.00001845509,0.00002187303,0.0001106022,0.0001168838,0.007639377],"genre_scores_gemma":[0.9989567,0.00002868819,0.0006090502,0.00002222887,0.000006879389,0.000005318293,0.0000224495,0.000006697367,0.0003420377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005130162,"threshold_uncertainty_score":0.02073091,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2624915418","doi":"10.1515/snde-2016-0062","title":"Detecting capital market convergence clubs","year":2017,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Economic Growth and Development","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Unobservable; Convergence (economics); Economics; Pairwise comparison; Econometrics; Stock market; Capital market; Arbitrage; Financial economics; Mathematics; Macroeconomics; Finance; Statistics; Geography","authors":[{"name":"Fuat Can Beylunioğlu","is_ca":false},{"name":"Thanasis Stengos","is_ca":true},{"name":"M. Ege Yazgan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04385248383049429,"gpt":0.2799666214877153,"spread":0.236114137657221,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004436077,0.0007741377,0.001783622,0.007703673,0.001954864,0.002181714,0.002171023,0.001524227,0.002938102],"category_scores_gemma":[0.02076258,0.0004920569,0.001260662,0.002543259,0.00139322,0.002051409,0.003299336,0.001276689,0.0006058112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008814117,"about_ca_system_score_gemma":0.001138875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003598397,"about_ca_topic_score_gemma":0.002576484,"domain_scores_codex":[0.9961116,0.001334793,0.0002023398,0.0008243509,0.001010816,0.0005161795],"domain_scores_gemma":[0.9862872,0.006078236,0.001804314,0.001466035,0.002950757,0.001413471],"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":[0.001777021,0.001227582,0.2163429,0.0005795884,0.000678147,0.002502569,0.001523727,0.2898265,0.02518115,0.08253267,0.01149745,0.3663306],"study_design_scores_gemma":[0.00002698626,0.00008932332,0.007123048,0.00002756734,0.00003089152,0.00020161,0.0002221444,0.9699137,0.003191921,0.01805902,0.001086621,0.00002728966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3170084,0.0003869389,0.674783,0.000248354,0.00006192274,0.0002899094,0.0003847982,0.001131196,0.005705425],"genre_scores_gemma":[0.8936366,0.00007626027,0.1040276,0.00005192976,0.00004918637,0.0001231735,0.0005493605,0.00009734741,0.001388555],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007703673,"threshold_uncertainty_score":0.02346051,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4393315982","doi":"10.1515/snde-2023-0028","title":"A Simulation and Empirical Study of the Maximum Likelihood Estimator for Stochastic Volatility Jump-Diffusion Models","year":2024,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Simon Fraser University","keywords":"Estimator; Jump; Econometrics; Stochastic volatility; Maximum likelihood; Jump diffusion; Mathematics; Volatility (finance); Statistical physics; Economics; Statistics; Applied mathematics; Physics","authors":[{"name":"Jean‐François Bégin","is_ca":true},{"name":"Mathieu Boudreault","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08826308223351437,"gpt":0.3319779333839397,"spread":0.2437148511504253,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008611081,0.0004918632,0.001037291,0.001302499,0.0006275349,0.001016672,0.001182928,0.001536265,0.0021133],"category_scores_gemma":[0.04344067,0.0004627524,0.000711129,0.001043312,0.001085033,0.001830144,0.001050418,0.001749648,0.0001769573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009427421,"about_ca_system_score_gemma":0.0007266336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00796589,"about_ca_topic_score_gemma":0.004696123,"domain_scores_codex":[0.9981222,0.001383888,0.00007081593,0.0001381812,0.0001913043,0.00009359513],"domain_scores_gemma":[0.9112471,0.08214853,0.002063925,0.0020713,0.002000515,0.0004686215],"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":[0.0001154777,0.0001015044,0.01025401,0.00005281458,0.00006159024,0.0001451085,0.0001043703,0.9677714,0.0003967021,0.01580577,0.000394925,0.004796447],"study_design_scores_gemma":[0.00002129662,0.00003072995,0.0005493612,0.000009619095,0.000006406782,0.0000192669,0.0000170059,0.9968155,0.0001801496,0.002251919,0.00008994807,0.000008848378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8377025,0.0006054434,0.155251,0.001185816,0.00004128334,0.000110895,0.000287427,0.0002433311,0.004572352],"genre_scores_gemma":[0.9749138,0.00008951508,0.02429958,0.00004211695,0.00001037402,0.00006356572,0.0001659624,0.00002278349,0.0003922234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008611081,"threshold_uncertainty_score":0.04554033,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399024944","doi":"10.1515/snde-2023-0106","title":"Divisia Monetary Aggregates for India","year":2024,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lakehead University; University of Calgary","funders":"","keywords":"Divisia index; Divisia monetary aggregates index; Economics; Econometrics; Keynesian economics; Monetary economics; Monetary policy; Mathematics; Statistics; Central bank; Quantitative easing","authors":[{"name":"Anirban Sengupta","is_ca":false},{"name":"Apostolos Serletis","is_ca":true},{"name":"Libo Xu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1424694205419128,"gpt":0.2883487150579674,"spread":0.1458792945160546,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006935459,0.0003176172,0.0002759182,0.004598296,0.0003454084,0.001738,0.000410435,0.0002253072,0.002458854],"category_scores_gemma":[0.003624515,0.0001684074,0.0004058952,0.006752459,0.0003225555,0.0005296706,0.001036135,0.0006632813,0.0005755874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001095202,"about_ca_system_score_gemma":0.0007654261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03490909,"about_ca_topic_score_gemma":0.02227246,"domain_scores_codex":[0.9994758,0.0001237069,0.00004896069,0.00009158313,0.0001519566,0.0001080151],"domain_scores_gemma":[0.9960715,0.000862552,0.001691738,0.0004066584,0.0007572325,0.0002103806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003186463,0.00007667155,0.9061919,0.000185914,0.0002938162,0.000617441,0.00101072,0.03326511,0.0009871639,0.0100336,0.01379017,0.03322889],"study_design_scores_gemma":[0.0000107702,0.00005322645,0.9678936,0.00004083552,0.00005291256,0.0001919498,0.0008584544,0.01545235,0.0008052287,0.002211932,0.01238933,0.00003939744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684022,0.0004230528,0.001321472,0.0005390234,0.00003500216,0.00002618597,0.01670236,0.0003419774,0.01220873],"genre_scores_gemma":[0.9917341,0.0001550687,0.0005717238,0.00001771852,0.00002201789,0.00001219627,0.006739628,0.00001771504,0.0007298107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03490909,"threshold_uncertainty_score":0.06941181,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3217300031","doi":"10.1515/snde-2024-0108","title":"Conventional and Unconventional Monetary Policy Rate Uncertainty and Stock Market Volatility: A Forecasting Perspective","year":2025,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Economics; Monetary policy; Autoregressive conditional heteroskedasticity; Volatility (finance); Bivariate analysis; Econometrics; Stock market; Stock market index; Heteroscedasticity; Financial economics; Univariate; Stock (firearms); Monetary economics; Multivariate statistics; Statistics","authors":[{"name":"Ruipeng Liu","is_ca":false},{"name":"Rangan Gupta","is_ca":false},{"name":"Elie Bouri","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04989595371890827,"gpt":0.290575375801136,"spread":0.2406794220822277,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001828422,0.0003428207,0.0003427547,0.0009960628,0.0002094898,0.001728289,0.0003965047,0.0006786485,0.001110613],"category_scores_gemma":[0.00736579,0.0002008813,0.0003153765,0.001197543,0.0005405657,0.001954584,0.0006151883,0.000772511,0.00008531558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005817538,"about_ca_system_score_gemma":0.0005119687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006998531,"about_ca_topic_score_gemma":0.006174496,"domain_scores_codex":[0.9997352,0.0001023009,0.00001932849,0.00004569191,0.00006400366,0.00003354833],"domain_scores_gemma":[0.9970552,0.001872204,0.0006650124,0.0001223712,0.0001695572,0.000115597],"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":[0.0001992256,0.00009256485,0.269304,0.00007891726,0.0002405533,0.0002498979,0.0005158232,0.5579244,0.001840237,0.1087057,0.001007482,0.05984128],"study_design_scores_gemma":[0.000007690426,0.00005471825,0.06474398,0.00004252863,0.00004235062,0.00004057557,0.0002443976,0.8933759,0.0005952888,0.04008988,0.000725488,0.00003708776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9611421,0.001240317,0.03017412,0.00174012,0.0000535399,0.000008201329,0.0001903368,0.0000335543,0.005417737],"genre_scores_gemma":[0.998154,0.0003579382,0.001234752,0.00001805647,0.00004191008,0.000001347919,0.00004477356,0.000001879446,0.0001453741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006998531,"threshold_uncertainty_score":0.0139156,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W7116316565","doi":"10.1515/snde-2025-0067","title":"Decomposed Oil-Driven Inflation Persistence and Asymmetric Shocks","year":2025,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Oil price; Inflation (cosmology); Persistence (discontinuity); Monetary policy; Geopolitics; Exchange rate; Price setting; Inflation targeting","authors":[{"name":"Joseph Agyapong","is_ca":false},{"name":"Eric Atanga Ayamga","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04579067828775224,"gpt":0.2716678993306321,"spread":0.2258772210428799,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008943446,0.0002568678,0.0003539427,0.0009589759,0.0001117177,0.0008585717,0.0002902928,0.0002538104,0.001079263],"category_scores_gemma":[0.004807122,0.0001323089,0.0003498718,0.0008291834,0.0004341138,0.0007915504,0.0006470516,0.0005417384,0.000108238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003496857,"about_ca_system_score_gemma":0.0003591514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001631493,"about_ca_topic_score_gemma":0.001128558,"domain_scores_codex":[0.9996432,0.00009247621,0.00003607019,0.00007176111,0.0000979638,0.00005848252],"domain_scores_gemma":[0.9975771,0.0007187158,0.001026785,0.0002384854,0.0003414735,0.00009754806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000602482,0.0001960949,0.6753963,0.0001492747,0.0005633865,0.0004031507,0.000433737,0.1703177,0.01678854,0.06027201,0.0005509992,0.07432636],"study_design_scores_gemma":[0.00002376407,0.0001399746,0.3672859,0.00003540063,0.00009550645,0.0001387283,0.0002545018,0.5871998,0.006212525,0.03789471,0.0006626667,0.00005644352],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9550508,0.0000801512,0.04275101,0.00009173068,0.000007656061,0.00001172344,0.0002248308,0.00004941543,0.001732609],"genre_scores_gemma":[0.9985651,0.00002275759,0.001142654,0.000005055259,0.000004319652,0.000002755593,0.0001005763,0.000004319401,0.0001525413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001631493,"threshold_uncertainty_score":0.004729748,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404690918","doi":"10.1515/snde-2023-0108","title":"Monetary Policy Uncertainty in the United States and Investment Sentiment in Advanced Economies","year":2024,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Calgary","funders":"","keywords":"Economics; Investment (military); Monetary policy; Macroeconomics; Political science","authors":[{"name":"Nahiyan Faisal Azad","is_ca":false},{"name":"Apostolos Serletis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03224298465134405,"gpt":0.2781346554793898,"spread":0.2458916708280457,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001225751,0.0002131994,0.0003835292,0.000762497,0.0002287556,0.001777721,0.0001429414,0.0005860072,0.001050769],"category_scores_gemma":[0.007450749,0.0001350968,0.0002345557,0.001232405,0.0004521029,0.0008180006,0.0005332354,0.0007410152,0.0001415329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006258371,"about_ca_system_score_gemma":0.0002449768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007407174,"about_ca_topic_score_gemma":0.00484349,"domain_scores_codex":[0.9996717,0.000106738,0.00004108524,0.00005430229,0.00008078689,0.00004530774],"domain_scores_gemma":[0.9914519,0.003291286,0.003844508,0.0001654129,0.0008068559,0.0004400251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002756674,0.00009870272,0.9565248,0.00005567756,0.0002467906,0.000311644,0.0004439984,0.02005398,0.0009249668,0.009418501,0.001730141,0.009915054],"study_design_scores_gemma":[0.00001983977,0.00009778149,0.9514076,0.00009041973,0.0001089339,0.0001046077,0.0007780928,0.0342764,0.0007731661,0.009876527,0.002420486,0.00004620148],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952059,0.0006612297,0.0004914643,0.0008970439,0.00002446469,0.000002748912,0.0002330924,0.000006949998,0.002477126],"genre_scores_gemma":[0.9995044,0.0001842022,0.00003921767,0.0000254655,0.00001721919,0.000001077621,0.0001160593,8.759825e-7,0.0001114123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007407174,"threshold_uncertainty_score":0.01472813,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2265736684","doi":"10.1515/snde-2016-0063","title":"Interest rate pass-through: a nonlinear vector error-correction approach","year":2017,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Queen's University","funders":"","keywords":"Econometrics; Economics; Interest rate; Error correction model; Endogeneity; Recession; Indirect Inference; Nonlinear system; Short rate; Inference; Estimation; Yield curve; Mathematics; Statistics; Monetary economics; Macroeconomics; Computer science; Cointegration","authors":[{"name":"Michał Ksawery Popiel","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.12570506507326,"gpt":0.3011683415915268,"spread":0.1754632765182668,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01192685,0.0007892644,0.001090143,0.001691502,0.0007654455,0.00279131,0.002221976,0.001020108,0.005243289],"category_scores_gemma":[0.0352603,0.0005606301,0.001715017,0.001705901,0.001538745,0.001625338,0.001313908,0.002204045,0.001000035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003357026,"about_ca_system_score_gemma":0.004146648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2145741,"about_ca_topic_score_gemma":0.0901369,"domain_scores_codex":[0.9945279,0.002010445,0.0004206164,0.001447759,0.001035379,0.0005578725],"domain_scores_gemma":[0.9765888,0.01117644,0.005266116,0.003444176,0.003226935,0.0002976219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007910416,0.0002275235,0.4776458,0.0001876246,0.00130671,0.000766237,0.001192594,0.3329414,0.0009572612,0.0593319,0.00636819,0.1182838],"study_design_scores_gemma":[0.00005644316,0.0002168298,0.1380916,0.00007990756,0.00032123,0.000177747,0.0003478581,0.8342883,0.002746117,0.01508963,0.008460491,0.0001237462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6181954,0.0008757553,0.3615227,0.001977317,0.000277645,0.0002722779,0.004559932,0.001509609,0.01080941],"genre_scores_gemma":[0.9716175,0.0002111675,0.01376543,0.00008274517,0.00004217638,0.00006663787,0.002145066,0.0001258741,0.01194336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2145741,"threshold_uncertainty_score":0.4266502,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389203081","doi":"10.1515/snde-2022-0083","title":"Interfuel Substitution and Inflation Dynamics in India","year":2023,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Lakehead University; University of Calgary","funders":"","keywords":"Substitution (logic); Economics; Inflation (cosmology); Econometrics; Consumption (sociology); Macroeconomics","authors":[{"name":"Anirban Sengupta","is_ca":false},{"name":"Apostolos Serletis","is_ca":true},{"name":"Libo Xu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02760874985653929,"gpt":0.2724024502747304,"spread":0.2447937004181911,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003564395,0.0001292503,0.0002623989,0.0008445796,0.0002793539,0.001062094,0.0002505319,0.000210715,0.002002893],"category_scores_gemma":[0.001248957,0.0001693334,0.000343011,0.001182301,0.0004973879,0.000426726,0.0006304026,0.0004294344,0.0002477147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001272994,"about_ca_system_score_gemma":0.0005865076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01548653,"about_ca_topic_score_gemma":0.01405353,"domain_scores_codex":[0.9997234,0.00007916414,0.00001893892,0.00002937082,0.00006579106,0.00008330971],"domain_scores_gemma":[0.9992579,0.0003145631,0.0002092255,0.00006095526,0.0001120115,0.00004542754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005290805,0.0001327578,0.7528229,0.0001382592,0.000174689,0.001302055,0.001353382,0.1246278,0.005899413,0.0848418,0.001308153,0.02686964],"study_design_scores_gemma":[0.00001632501,0.0001040236,0.8096486,0.00003506722,0.00007218062,0.0006611256,0.002708528,0.1514416,0.003144428,0.02709754,0.00500509,0.00006541923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927555,0.0001433721,0.001301187,0.0003813047,0.000004618421,0.000004366831,0.0002336294,0.00001522181,0.005160817],"genre_scores_gemma":[0.9994012,0.00004618934,0.0001026196,0.000009415201,0.000001924563,0.000001129707,0.00006806307,0.000002021915,0.000367424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01548653,"threshold_uncertainty_score":0.03079277,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3184332670","doi":"10.1515/snde-2019-0084","title":"Time-specific average estimation of dynamic panel regressions","year":2021,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Carleton University","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Econometrics; Estimation; Panel data; Statistics; Mathematics; Economics","authors":[{"name":"Ba Chu","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08128200323966635,"gpt":0.2776482907061176,"spread":0.1963662874664513,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003576672,0.0003963461,0.0009220563,0.001110126,0.0002551064,0.001012833,0.001056112,0.0005918852,0.001986879],"category_scores_gemma":[0.01446866,0.0004171147,0.0006831878,0.001449586,0.0002624064,0.001075918,0.0007675395,0.0009219447,0.0005257169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004426877,"about_ca_system_score_gemma":0.0006713924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004065258,"about_ca_topic_score_gemma":0.004268778,"domain_scores_codex":[0.9981796,0.001087105,0.00007067238,0.0003564696,0.0002121093,0.00009399329],"domain_scores_gemma":[0.9944062,0.003597108,0.0006610683,0.0007158139,0.0005473784,0.00007229568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009905201,0.00009177717,0.02158528,0.0001615053,0.0007167863,0.0001477135,0.0001537367,0.6596464,0.00496614,0.07272773,0.003722753,0.2359811],"study_design_scores_gemma":[0.000005539521,0.00002311498,0.003258213,0.00001615378,0.00004117928,0.00002871221,0.00001763568,0.9759616,0.001529278,0.01714603,0.001955721,0.00001681851],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01919761,0.0001711351,0.9794158,0.00006008159,0.00002298323,0.00001348748,0.0001679338,0.0002746983,0.0006763361],"genre_scores_gemma":[0.6593773,0.0006393162,0.3339091,0.0001214199,0.0001184585,0.0001366573,0.001878124,0.0001894376,0.003630078],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004065258,"threshold_uncertainty_score":0.01891541,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4403771965","doi":"10.1515/snde-2023-0030","title":"To Bag is to Prune","year":2024,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Statistical physics; Econometrics; Computer science; Mathematics; Physics","authors":[{"name":"Philippe Goulet Coulombe","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1707280879698296,"gpt":0.3040571668794783,"spread":0.1333290789096487,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002867187,0.001126847,0.001323312,0.001062894,0.001269826,0.003021408,0.00182358,0.001825736,0.01008367],"category_scores_gemma":[0.01298751,0.0006579226,0.00090079,0.001029506,0.00142001,0.005307244,0.002014094,0.003806186,0.0085412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006869579,"about_ca_system_score_gemma":0.0007535065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001539285,"about_ca_topic_score_gemma":0.002417189,"domain_scores_codex":[0.9980406,0.0007754033,0.00008906876,0.0004941459,0.0004378089,0.000162894],"domain_scores_gemma":[0.9949705,0.00165901,0.0004036457,0.001887147,0.000832588,0.0002471016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003908368,0.0002607629,0.008932459,0.0003144802,0.0004176807,0.0002094913,0.0004249336,0.1442913,0.008408893,0.07393555,0.1209514,0.6414621],"study_design_scores_gemma":[0.00005414504,0.0002200853,0.002595282,0.000218212,0.000142396,0.0004196067,0.0002345075,0.6785809,0.00930899,0.2182827,0.08984218,0.000101103],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04767065,0.002489105,0.9109008,0.01088126,0.002094634,0.0001328572,0.000662284,0.006960832,0.01820757],"genre_scores_gemma":[0.5407446,0.001591274,0.4211046,0.007332101,0.001719178,0.000199226,0.002133346,0.002690878,0.02248484],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01008367,"threshold_uncertainty_score":0.03373325,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975043302","doi":"10.1515/snde-2012-0047","title":"Common large innovations across nonlinear time series","year":2013,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Econometrics; Inference; Nonlinear system; Multivariate statistics; Unemployment; Autoregressive model; Series (stratigraphy); Latent variable; Time series; Econometric model; Representation (politics); Economics; Mathematics; Statistics; Computer science; Artificial intelligence; Macroeconomics","authors":[{"name":"Philip Hans Franses","is_ca":false},{"name":"Richard Paap","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0899853358908662,"gpt":0.2862978776260205,"spread":0.1963125417351543,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004631364,0.0005460416,0.00102258,0.001516297,0.0006269361,0.001989566,0.001157986,0.001278724,0.004217895],"category_scores_gemma":[0.02875571,0.0006111405,0.001330935,0.001580793,0.002712621,0.003325647,0.00225076,0.00227718,0.0003434753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002373268,"about_ca_system_score_gemma":0.001302227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02721669,"about_ca_topic_score_gemma":0.01557959,"domain_scores_codex":[0.9977203,0.000724072,0.0001395191,0.0005233979,0.0005774149,0.0003152789],"domain_scores_gemma":[0.9836976,0.01014769,0.003406944,0.001165919,0.001257353,0.0003246085],"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":[0.0001395066,0.00009419194,0.04202649,0.0001495079,0.0003177054,0.0008468371,0.0008812307,0.3549153,0.001873626,0.5691795,0.001492632,0.02808351],"study_design_scores_gemma":[0.0000199132,0.00003360105,0.01272492,0.00003731775,0.00005396795,0.0001072824,0.000185665,0.7737324,0.0005256624,0.210952,0.001567262,0.0000600447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3640106,0.0004724128,0.6240103,0.002644479,0.00009419695,0.0001034017,0.0005947922,0.0003785295,0.007691127],"genre_scores_gemma":[0.9857467,0.0002632415,0.009244306,0.00009652913,0.00005789215,0.00004817101,0.0001798438,0.00003231607,0.004330895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02721669,"threshold_uncertainty_score":0.05411649,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3114963464","doi":"10.1515/snde-2019-0096","title":"A new bivariate Archimedean copula with application to the evaluation of VaR","year":2020,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Northern British Columbia","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Copula (linguistics); Bivariate analysis; Econometrics; Gumbel distribution; Portfolio; Tail dependence; Value at risk; Mathematics; Economics; Monte Carlo method; Statistics; Extreme value theory; Multivariate statistics; Financial economics; Risk management; Finance","authors":[{"name":"Çiğdem Topçu Gülöksüz","is_ca":true},{"name":"Pranesh Kumar","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1151404532624749,"gpt":0.3074247222458666,"spread":0.1922842689833918,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001880231,0.0007825695,0.0008331791,0.001609787,0.0003860095,0.001244504,0.0008086062,0.0007406711,0.001475947],"category_scores_gemma":[0.007143584,0.0003337544,0.001017693,0.001214749,0.0006128997,0.001331141,0.0007596362,0.000991256,0.0003180626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005926808,"about_ca_system_score_gemma":0.0008349263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00237682,"about_ca_topic_score_gemma":0.001101813,"domain_scores_codex":[0.9987411,0.0005695212,0.0000651173,0.0001722841,0.0003765113,0.00007555562],"domain_scores_gemma":[0.997925,0.0009639626,0.0001803005,0.0001723304,0.0006678441,0.00009039856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008507211,0.00007317829,0.004959022,0.0001799256,0.00015342,0.0004668238,0.0001299752,0.7703767,0.007197589,0.09775289,0.002425159,0.1162003],"study_design_scores_gemma":[0.000003095948,0.00001799489,0.0003986065,0.000007998865,0.000008416895,0.00007508675,0.000007408429,0.99287,0.0005997913,0.005337044,0.0006626557,0.00001187645],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009073318,0.0002894816,0.9895061,0.00007633479,0.00004047168,0.00002514166,0.0000329045,0.0001182,0.0008381213],"genre_scores_gemma":[0.560789,0.001189758,0.4351359,0.000111526,0.0001875866,0.0001595042,0.0002801603,0.0001968463,0.001949727],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00237682,"threshold_uncertainty_score":0.009943724,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3001323165","doi":"10.1515/snde-2019-0005","title":"What model for the target rate","year":2020,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Bank of Canada","funders":"","keywords":"Econometrics; Inflation (cosmology); Inflation rate; Volatility (finance); Sample (material); Unemployment rate; Federal funds; Statistics; Sample size determination; Economics; Mathematics; Interest rate; Unemployment; Monetary policy; Physics","authors":[{"name":"Bruno Feunou","is_ca":true},{"name":"Jean‐Sébastien Fontaine","is_ca":true},{"name":"Jianjian Jin","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2685900641639429,"gpt":0.2913656381502849,"spread":0.022775573986342,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002331811,0.0006514262,0.0008940153,0.0005983533,0.0003830542,0.003137427,0.00163648,0.002311694,0.01360557],"category_scores_gemma":[0.01279324,0.0003656864,0.0008617439,0.0006624155,0.0004999707,0.003369915,0.0005108034,0.002019396,0.002836329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001709443,"about_ca_system_score_gemma":0.001104614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0139507,"about_ca_topic_score_gemma":0.006358977,"domain_scores_codex":[0.9990689,0.0003743813,0.00002952374,0.0002697082,0.0001350741,0.0001224276],"domain_scores_gemma":[0.9970261,0.001659213,0.0004848088,0.0002817445,0.0004022036,0.0001458399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003708371,0.0001408328,0.01114382,0.0002795656,0.0001564146,0.0002765577,0.0003219877,0.5690808,0.001213938,0.3520158,0.03024514,0.03475416],"study_design_scores_gemma":[0.0001065643,0.00005571271,0.002601425,0.00009508764,0.00004522208,0.0001103613,0.0001289833,0.851707,0.0003688598,0.1340049,0.01073147,0.00004438624],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2481668,0.003336679,0.5339097,0.0451641,0.001768077,0.0002517923,0.008381325,0.00200401,0.1570176],"genre_scores_gemma":[0.9712106,0.0006165585,0.0107896,0.0008395292,0.0002297359,0.0001036266,0.001011578,0.0001701727,0.01502855],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0139507,"threshold_uncertainty_score":0.04551512,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4414298862","doi":"10.1515/snde-2024-0123","title":"Trend Breaks and the Persistence of Closed-End Fund Discounts","year":2025,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"State Capitalism and Financial Governance","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Zoo","funders":"","keywords":"Persistence (discontinuity); Identification (biology); Asset (computer security); Nonlinear system; Moment (physics); Phenomenon","authors":[{"name":"Nazif Durmaz","is_ca":false},{"name":"Hyeongwoo Kim","is_ca":false},{"name":"Hyejin Lee","is_ca":false},{"name":"Yanfei Sun","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.038950492973904,"gpt":0.2600098430712176,"spread":0.2210593500973136,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00276577,0.0001181051,0.0003623577,0.0009326031,0.0002560533,0.001630334,0.0004371614,0.0006210686,0.002261893],"category_scores_gemma":[0.0252254,0.0001524271,0.0002628403,0.0008555501,0.0006516218,0.001427968,0.0006604286,0.001228282,0.0002348925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005731113,"about_ca_system_score_gemma":0.0001387737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00216809,"about_ca_topic_score_gemma":0.002065378,"domain_scores_codex":[0.9993721,0.0001231207,0.00007673895,0.0001565094,0.0001843706,0.00008714432],"domain_scores_gemma":[0.9774435,0.008647743,0.01073479,0.001831792,0.0009142408,0.0004279051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005558451,0.0001318889,0.9075395,0.00008194166,0.0002149077,0.0007638498,0.002061632,0.01511098,0.003884143,0.02129173,0.001631851,0.04673172],"study_design_scores_gemma":[0.00002096125,0.0001548602,0.9078655,0.00004539142,0.0000605169,0.0004287775,0.0009590848,0.05934989,0.002062597,0.02658026,0.002410257,0.00006190861],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962357,0.000106959,0.002152314,0.0001181478,0.000006649856,0.000004167156,0.0001799379,0.00001871751,0.00117755],"genre_scores_gemma":[0.9996691,0.00001910092,0.0001071696,0.000004052997,0.000005621323,8.872087e-7,0.00007688747,0.000002437023,0.0001148998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00276577,"threshold_uncertainty_score":0.01462698,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410555711","doi":"10.1515/snde-2024-0012","title":"Identifying Shock Propagation Mechanisms in Global Equity Markets","year":2025,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Economics; Emerging markets; Diversification (marketing strategy); Risk premium; Financial economics; Country risk; Portfolio; Volatility (finance); Equity (law); Monetary economics; Capital asset pricing model; Econometrics; Business; Finance","authors":[{"name":"Vance L. Martin","is_ca":false},{"name":"Saikat Sarkar","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06342439104540398,"gpt":0.3106745463743426,"spread":0.2472501553289386,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001709606,0.0005179158,0.0004945931,0.000633567,0.0002452118,0.001312763,0.0003975497,0.0008076809,0.001586393],"category_scores_gemma":[0.006505838,0.0002794298,0.0005685342,0.0004764521,0.0007228677,0.002026028,0.0008921309,0.0007668779,0.00007697841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006041177,"about_ca_system_score_gemma":0.0004438419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005665568,"about_ca_topic_score_gemma":0.002023177,"domain_scores_codex":[0.9997595,0.0001306683,0.00001024423,0.00003184811,0.00002822954,0.00003947386],"domain_scores_gemma":[0.9975289,0.001727522,0.0004231154,0.0001102269,0.0001154401,0.00009486097],"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":[0.0001153671,0.00007806566,0.02353393,0.00002871694,0.00009351035,0.0002697235,0.000151929,0.9138838,0.001561572,0.05185188,0.0003541137,0.008077291],"study_design_scores_gemma":[0.00002020643,0.00002956611,0.002423748,0.00000412382,0.00001414612,0.00001815075,0.00003902615,0.9830787,0.0002425338,0.01404837,0.00007287825,0.000008621411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9505773,0.0001021066,0.04710661,0.0001975162,0.00001025672,0.00002715068,0.00005978531,0.00004901619,0.001870198],"genre_scores_gemma":[0.9980471,0.00005853109,0.001511433,0.00001070928,0.000003440654,0.000005536269,0.00001887238,0.000003624865,0.0003407394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005665568,"threshold_uncertainty_score":0.01126516,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399034880","doi":"10.1515/snde-2023-0009","title":"Asymptotic Efficiency of Joint Estimator Relative to Two-Stage Estimator Under Misspecified Likelihoods","year":2024,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Estimator; Efficiency; Econometrics; Joint (building); Mathematics; Statistics; Applied mathematics; Engineering","authors":[{"name":"Doosoo Kim","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1816046537187592,"gpt":0.424340940150551,"spread":0.2427362864317918,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03435731,0.0009207057,0.002517457,0.001772633,0.0005282406,0.002727495,0.003332797,0.002026341,0.005070195],"category_scores_gemma":[0.1842367,0.0008581533,0.001108042,0.00158851,0.003486814,0.005482305,0.003461768,0.00241078,0.0008146337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001580521,"about_ca_system_score_gemma":0.002428927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002734215,"about_ca_topic_score_gemma":0.002197097,"domain_scores_codex":[0.9837211,0.01168484,0.0006075207,0.001448397,0.001983365,0.0005547075],"domain_scores_gemma":[0.7609866,0.2168199,0.00564635,0.01084469,0.004827962,0.0008744265],"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":[0.0005470408,0.0002247772,0.01499,0.0008554413,0.0005337794,0.0004873925,0.0005581176,0.3336481,0.003276039,0.5393167,0.00295802,0.1026046],"study_design_scores_gemma":[0.00004099151,0.00009190349,0.002581317,0.00008890118,0.0000639456,0.0001988875,0.00007232462,0.8409053,0.001199229,0.1536103,0.001102843,0.00004398188],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02105045,0.0007369088,0.975291,0.0004937523,0.00004122723,0.00004019144,0.00007457488,0.000204248,0.002067712],"genre_scores_gemma":[0.6722795,0.001371042,0.3183671,0.0004059345,0.0002628768,0.0003516682,0.0006171428,0.0003522937,0.005992393],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03435731,"threshold_uncertainty_score":0.181701,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2802478853","doi":"10.1515/snde-2017-0047","title":"The Rescaled VAR Model with an Application to Mixed-Frequency Macroeconomic Forecasting","year":2018,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Dalhousie University","funders":"","keywords":"Econometrics; Bayesian vector autoregression; Representation (politics); Vector autoregression; Bayesian probability; Mathematics; Computer science; Statistics","authors":[{"name":"Andrea Giusto","is_ca":true},{"name":"Talan İşcan","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1269853095508587,"gpt":0.2790439504439393,"spread":0.1520586408930806,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003725538,0.0005786606,0.0009113997,0.0007441849,0.000216019,0.001482451,0.001426953,0.001270794,0.003314145],"category_scores_gemma":[0.01613859,0.0004634037,0.0008631019,0.0009493898,0.0005807365,0.002054989,0.001076616,0.001730407,0.0005029536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004580775,"about_ca_system_score_gemma":0.0004142806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003221624,"about_ca_topic_score_gemma":0.001570453,"domain_scores_codex":[0.9983743,0.001049942,0.00007306992,0.0002427698,0.0001921471,0.0000677619],"domain_scores_gemma":[0.9951857,0.003258726,0.0004705921,0.0005554901,0.0004311229,0.00009835658],"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":[0.00009252538,0.00003900076,0.001735642,0.00006320639,0.0001090137,0.0002012004,0.0001023329,0.7629915,0.001422167,0.188622,0.001431097,0.04319033],"study_design_scores_gemma":[0.000004600504,0.000009549862,0.0001002463,0.000004976835,0.000004802252,0.00001466626,0.000003694007,0.9797627,0.00007915012,0.01955362,0.0004547177,0.000007238354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01956707,0.0003651389,0.9775339,0.0003875141,0.0000891169,0.0000184176,0.0001297281,0.0002870491,0.001622062],"genre_scores_gemma":[0.7257729,0.0005872602,0.2681926,0.0002178082,0.0002299912,0.0001253346,0.0003405389,0.0001543415,0.004379237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003725538,"threshold_uncertainty_score":0.01970279,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2805476515","doi":"10.1515/snde-2019-0042","title":"Fiscal austerity in emerging market economies","year":2020,"lang":"en","type":"preprint","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Global Financial Crisis and Policies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"Consolidation (business); Austerity; Economics; Monetary economics; Fiscal policy; Emerging markets; Macroeconomics; International economics; Finance","authors":[{"name":"Chetan Dave","is_ca":true},{"name":"Chetan Ghate","is_ca":false},{"name":"Pawan Gopalakrishnan","is_ca":false},{"name":"Suchismita Tarafdar","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07911835714193255,"gpt":0.2981813271087032,"spread":0.2190629699667706,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008055814,0.0002029922,0.0005543393,0.000415615,0.0004038042,0.001703921,0.0005553738,0.0009226921,0.00272312],"category_scores_gemma":[0.003955913,0.00026869,0.0004028729,0.0004554461,0.001037248,0.00163752,0.0006906251,0.001417085,0.0002576401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001495604,"about_ca_system_score_gemma":0.001145809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01477892,"about_ca_topic_score_gemma":0.005970856,"domain_scores_codex":[0.9998229,0.00006480118,0.00001014282,0.00002960497,0.00002883504,0.00004370302],"domain_scores_gemma":[0.9991243,0.0002458399,0.0003474187,0.00005464931,0.0001115691,0.0001161472],"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":[0.00007295235,0.00006598267,0.00826843,0.00004362162,0.00004549312,0.000428405,0.000187987,0.5454664,0.000519062,0.4373557,0.003009131,0.004536831],"study_design_scores_gemma":[0.00004475468,0.00003764196,0.004280217,0.00002711833,0.00002115931,0.00007951487,0.0001958727,0.8396788,0.000163191,0.1517494,0.003700519,0.00002185769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8929004,0.0008040112,0.07067651,0.006226818,0.0001294421,0.0000404452,0.0006360051,0.0001201418,0.02846624],"genre_scores_gemma":[0.9950901,0.0003037547,0.0009787286,0.00008527005,0.00002480637,0.00001316206,0.00005899076,0.00001056509,0.003434672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01477892,"threshold_uncertainty_score":0.02938581,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4285491995","doi":"10.1515/snde-2020-0136","title":"Clean energy consumption and economic growth in China: a time-varying analysis","year":2022,"lang":"en","type":"article","venue":"Studies in Nonlinear Dynamics and Econometrics","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Queen's University","funders":"","keywords":"Causality (physics); Econometrics; Causation; Granger causality; Causal inference; Economics; Consumption (sociology); Inference; Energy consumption; Stability (learning theory); Computer science","authors":[{"name":"Pejman Bahramian","is_ca":true},{"name":"Andisheh Saliminezhad","is_ca":false},{"name":"Sami Fethì","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.024285511251986,"gpt":0.2300714032107311,"spread":0.2057858919587451,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001405813,0.0003870879,0.0004416767,0.00166431,0.0005417534,0.001022765,0.0005769234,0.0005861706,0.003053507],"category_scores_gemma":[0.002153541,0.0001436236,0.001111586,0.002501869,0.0005580531,0.0006273121,0.0006796573,0.0007436533,0.0002010567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001204602,"about_ca_system_score_gemma":0.001410722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06598717,"about_ca_topic_score_gemma":0.03199061,"domain_scores_codex":[0.999562,0.0001006554,0.00003291738,0.0001220544,0.00007453047,0.0001079307],"domain_scores_gemma":[0.9983963,0.0006125105,0.0004021862,0.0001342408,0.0002398235,0.0002149224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001551134,0.0001433634,0.9480193,0.00008385554,0.0004697999,0.001024065,0.0003941658,0.03114403,0.001069318,0.005361475,0.001103621,0.01103197],"study_design_scores_gemma":[0.00001886291,0.0001501608,0.8522513,0.00003280001,0.0003415383,0.0001021652,0.0006992589,0.1413576,0.0004681987,0.001864686,0.002670178,0.00004321899],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961199,0.0003675567,0.001365076,0.0003630465,0.00002246661,0.00001464249,0.0005700382,0.00001811213,0.001159376],"genre_scores_gemma":[0.9986134,0.0001696134,0.0001542675,0.00001762943,0.00001482215,0.000007731096,0.0004379469,0.000002986729,0.0005815204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06598717,"threshold_uncertainty_score":0.1312062,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}