{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":66,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":66,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"2b41569042b6","filters":{"venue":"Econometric Reviews"}},"results":[{"id":"W2053752134","doi":"10.1080/07474930600972467","title":"MIDAS Regressions: Further Results and New Directions","year":2007,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1000,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Mitacs; University of Hong Kong; Academia Sinica; City University of Hong Kong","keywords":"Econometrics; Statistics; Economics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.1275056041634428,"gpt":0.2961227114710549,"spread":0.1686171073076121,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003192996,0.0002010821,0.0006787769,0.0009173195,0.0001624306,0.00007371909,0.0001809607,0.0001312611,0.0003819914],"category_scores_gemma":[0.002060103,0.0002021397,0.0001782065,0.001345391,0.00004104772,0.0003062901,0.0000667256,0.0002042517,0.00100451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009806611,"about_ca_system_score_gemma":0.00002352566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004567436,"about_ca_topic_score_gemma":0.0001283269,"domain_scores_codex":[0.9974504,0.00001955722,0.001538805,0.0005956115,0.00002662072,0.0003690131],"domain_scores_gemma":[0.9984458,0.0001990623,0.0005904633,0.0005012228,0.00001994994,0.000243484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006379838,0.0001285056,0.06664444,0.00008743789,0.00004233953,0.000003994526,0.001221677,0.00001388893,0.00000367447,0.04316274,0.02794874,0.8606787],"study_design_scores_gemma":[0.0004321685,0.00003980975,0.05347082,0.0000501064,0.000005947877,0.000004092402,0.00002346833,0.000377517,0.00000761703,0.01228273,0.9330623,0.0002433831],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0763075,0.6963355,0.03029231,0.002309775,0.001673083,0.001121177,0.000118309,0.0001229413,0.1917194],"genre_scores_gemma":[0.6719255,0.2712635,0.02471893,0.0009564289,0.001452724,0.00005452786,0.00004529867,0.00009567658,0.02948736],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9051136,"threshold_uncertainty_score":0.9997733,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2074235260","doi":"10.1081/etc-120008724","title":"LONG-RUN STRUCTURAL MODELLING","year":2002,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":293,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Trinity College","funders":"","keywords":"Econometrics; Computer science; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.05990883588062824,"gpt":0.2382804255243944,"spread":0.1783715896437661,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001909966,0.0001236311,0.0002654268,0.00007304095,0.0001229151,0.0000270903,0.0001852309,0.00002448022,0.0209313],"category_scores_gemma":[0.00003851777,0.00009237662,0.000111181,0.0006624282,0.00004970529,0.0002100008,0.00009972871,0.00007422605,0.01091791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007021432,"about_ca_system_score_gemma":4.549449e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002072961,"about_ca_topic_score_gemma":0.000004847798,"domain_scores_codex":[0.9991236,0.00002546757,0.0002984471,0.0002544129,0.00007715767,0.0002209698],"domain_scores_gemma":[0.9995953,0.00002744718,0.00009159093,0.0002121278,0.000001642249,0.00007189011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[9.771486e-7,0.0000400384,0.1387862,0.00004379803,0.00001851962,0.000005648505,0.0003642972,0.01151718,0.00000513248,0.00007987672,0.06667802,0.7824603],"study_design_scores_gemma":[0.0001570144,0.00003165115,0.02419434,0.00001660215,0.00001378696,0.000006954003,0.000009366158,0.0467875,0.00001149591,0.0002571388,0.9282241,0.0002900104],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5570409,0.122169,0.002938604,0.0006971955,0.0007070521,0.0008101197,0.000006588606,0.00008056427,0.31555],"genre_scores_gemma":[0.9635347,0.02238133,0.002784563,0.0004158206,0.0001941316,0.00002783861,0.000002051294,0.00001399693,0.0106456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8615461,"threshold_uncertainty_score":0.9898522,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1554411802","doi":"","title":"What Caused the Great Moderation? Some Cross-Country Evidence","year":2005,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":191,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Great Moderation; Economics; Luck; Moderation; Volatility (finance); Developed country; Developing country; International economics; Development economics; Monetary economics; Economic growth; Financial economics","retraction":null,"screen_n_in":null,"score":{"opus":0.08705397083980522,"gpt":0.3052215569624886,"spread":0.2181675861226834,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.004307311,0.0002950147,0.0008101018,0.0004278641,0.0003281263,0.001175002,0.0006705085,0.0001311012,0.003495901],"category_scores_gemma":[0.001145884,0.0002426511,0.0003121041,0.001097056,0.0001070767,0.003888401,0.0001239241,0.0002808738,0.002264721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003237767,"about_ca_system_score_gemma":0.00003097226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008118853,"about_ca_topic_score_gemma":0.00009260256,"domain_scores_codex":[0.9970199,0.00007163567,0.001679218,0.0007333729,0.00005989035,0.0004359241],"domain_scores_gemma":[0.9974441,0.0003674618,0.0008132321,0.001196584,0.00004668994,0.0001319557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004682955,0.0003020341,0.580462,0.0004928157,0.0002013056,0.000003663355,0.0007909874,0.001086267,0.000003150903,0.2197948,0.02090774,0.1759084],"study_design_scores_gemma":[0.00029664,0.0000331734,0.05747008,0.00007461925,0.00001221063,0.000004335616,0.00001075528,0.1039208,0.000003188368,0.01928335,0.8184773,0.0004135986],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2555126,0.7069236,0.002318352,0.005811621,0.002927758,0.002167587,0.000125775,0.00008534097,0.02412733],"genre_scores_gemma":[0.7647182,0.2190492,0.0005101583,0.003606876,0.0009726382,0.0002636878,0.00003139597,0.00004567088,0.01080218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7975695,"threshold_uncertainty_score":0.9998619,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2007895608","doi":"10.1080/07474930600713234","title":"Continuous Time Wishart Process for Stochastic Risk","year":2006,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":149,"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":"Wishart distribution; Stochastic volatility; Inverse-Wishart distribution; Econometrics; Multivariate statistics; Autoregressive model; Mathematics; Volatility (finance); Applied mathematics; Economics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.04344459436934799,"gpt":0.2543041387572285,"spread":0.2108595443878805,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002006653,0.0002784343,0.001202956,0.0006490211,0.0002008813,0.0001021276,0.0003404791,0.0001330615,0.0006279602],"category_scores_gemma":[0.00146835,0.0003041501,0.0004109759,0.0008811437,0.00004292994,0.0003470133,0.00003399311,0.0001714463,0.003803448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001172016,"about_ca_system_score_gemma":0.00002508074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002094871,"about_ca_topic_score_gemma":0.00001470512,"domain_scores_codex":[0.9970685,0.0000229031,0.001677165,0.0007102391,0.00003173927,0.0004894321],"domain_scores_gemma":[0.9980739,0.0001949757,0.001105793,0.0004700925,0.00006255985,0.00009265826],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002747264,0.002226354,0.3365256,0.002431872,0.0003537499,0.000005582033,0.001030728,0.02632515,0.00001807966,0.2255398,0.1210553,0.2842131],"study_design_scores_gemma":[0.00130821,0.0002069819,0.01409009,0.0000724742,0.00004695734,0.000003618474,0.00001112813,0.106638,0.00001158482,0.1557213,0.7209752,0.0009143768],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3479995,0.2302731,0.3607912,0.0003377221,0.001416047,0.005920152,0.001829681,0.0002372381,0.05119539],"genre_scores_gemma":[0.9866109,0.002403361,0.002906453,0.0001698316,0.0008543676,0.0006690707,0.000149924,0.00008084538,0.006155213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6386114,"threshold_uncertainty_score":0.9999411,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1979325061","doi":"10.1080/07474930701624462","title":"Asymptotic and Bootstrap Inference for AR(∞) Processes with Conditional Heteroskedasticity","year":2007,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":112,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal; Center for Interuniversity Research and Analysis on Organizations","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Heteroscedasticity; Estimator; Mathematics; Econometrics; Autoregressive model; Asymptotic distribution; Inference; Autoregressive conditional heteroskedasticity; Statistics; Applied mathematics; Computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.1178193859168615,"gpt":0.3059485720548072,"spread":0.1881291861379458,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001476779,0.0002094754,0.0006784452,0.0005062082,0.0001531435,0.00008869912,0.0001536316,0.00008525031,0.00009558987],"category_scores_gemma":[0.001960287,0.0002005447,0.00009045709,0.0007354119,0.00008746106,0.0003805637,0.00002984316,0.0001180538,0.000107898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006941233,"about_ca_system_score_gemma":0.00004864131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003181526,"about_ca_topic_score_gemma":0.00009262019,"domain_scores_codex":[0.9980966,0.000007613359,0.0009781348,0.0005206367,0.00003006536,0.0003669522],"domain_scores_gemma":[0.9985072,0.0005643661,0.0005033878,0.0002195484,0.00007232456,0.0001331445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001349209,0.0003146741,0.6899375,0.002801581,0.00009774333,0.000002924998,0.0004392449,0.0003286477,0.000004452634,0.2634979,0.0005385326,0.04190191],"study_design_scores_gemma":[0.002281366,0.0009805486,0.4389931,0.0003090858,0.00005187802,0.00002108203,0.00005155009,0.007209806,0.00008650673,0.1646919,0.3839562,0.001366933],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2308671,0.0360404,0.7280252,0.0001081634,0.0001544466,0.001078291,0.0002109895,0.00003313331,0.003482246],"genre_scores_gemma":[0.9866374,0.005500592,0.007190822,0.0002003963,0.0001314597,0.00009788088,0.0000428025,0.00002017393,0.0001784425],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7557703,"threshold_uncertainty_score":0.8177976,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2014974066","doi":"10.1081/etc-200040777","title":"Efficient Estimation of the Seemingly Unrelated Regression Cointegration Model and Testing for Purchasing Power Parity","year":2005,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Université de Montréal; Center for Interuniversity Research and Analysis on Organizations","funders":"Mitacs","keywords":"Purchasing power parity; Econometrics; Estimator; Cointegration; Seemingly unrelated regressions; Mathematics; Proportionality (law); Economics; Statistics; Exchange rate; Law","retraction":null,"screen_n_in":null,"score":{"opus":0.1307230827588108,"gpt":0.2801799038552967,"spread":0.1494568210964859,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001740986,0.000172589,0.0005643993,0.0004495159,0.0001691375,0.00004711756,0.0001596382,0.00009446441,0.00005966092],"category_scores_gemma":[0.001700299,0.0001371445,0.0001634898,0.0005897486,0.00005154517,0.0001924461,0.00004872219,0.0001234359,0.00004500164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001487453,"about_ca_system_score_gemma":0.0000147493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004786048,"about_ca_topic_score_gemma":0.000004304894,"domain_scores_codex":[0.9982143,0.00002507325,0.001174213,0.0003357961,0.00002029219,0.0002303411],"domain_scores_gemma":[0.9982672,0.0002047928,0.001106204,0.0003400492,0.0000151213,0.0000666743],"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":[0.00002160615,0.00009521801,0.01133607,0.0002164483,0.00003965735,5.591663e-8,0.001003823,0.8127622,0.00004404303,0.01477717,0.001154058,0.1585496],"study_design_scores_gemma":[0.0003416362,0.0000451731,0.0054616,0.00009514787,0.00001203837,0.000003616713,0.000008426421,0.9826424,0.00008038103,0.002780569,0.008373762,0.0001552346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.956116,0.01516044,0.02073584,0.000686658,0.0001884647,0.001029841,0.00009737411,0.00001752874,0.005967833],"genre_scores_gemma":[0.9827136,0.0003587529,0.01636778,0.0001315338,0.00005511315,0.00003467291,0.00001038198,0.00001603625,0.0003121569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1698802,"threshold_uncertainty_score":0.5592591,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2162460645","doi":"10.1080/07474930701220576","title":"Bayesian Clustering of Many Garch Models","year":2007,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":50,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal; Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Autoregressive conditional heteroskedasticity; Econometrics; Cluster analysis; Bayesian probability; Volatility clustering; Computer science; Mathematics; Statistics; Volatility (finance)","retraction":null,"screen_n_in":null,"score":{"opus":0.1119143214866346,"gpt":0.2809918914155973,"spread":0.1690775699289626,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004416413,0.0002076397,0.00103169,0.001235129,0.00007798408,0.00003170642,0.0003743104,0.0001253846,0.0004743054],"category_scores_gemma":[0.0003554211,0.0002341175,0.0003378659,0.001337401,0.00004498989,0.0003881472,0.0001050366,0.000189626,0.0004347809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001296773,"about_ca_system_score_gemma":0.00001485714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002282844,"about_ca_topic_score_gemma":0.00004784865,"domain_scores_codex":[0.9968278,0.00001789829,0.002162979,0.0004990122,0.00003934656,0.0004529829],"domain_scores_gemma":[0.9983315,0.0001129469,0.0007968333,0.000592915,0.00003393103,0.0001319156],"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":[0.00007565595,0.000387249,0.105647,0.001228408,0.000100195,0.000007693756,0.00177483,0.007222941,0.0000185867,0.4016142,0.001642731,0.4802805],"study_design_scores_gemma":[0.0008314111,0.0001692828,0.02265238,0.0001582725,0.00001747198,0.000007494466,0.00007660723,0.5418016,0.0000744928,0.1038235,0.3295263,0.0008610722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02457104,0.06994645,0.8025656,0.00005140494,0.0004253584,0.0004856817,0.00003266083,0.00002447482,0.1018974],"genre_scores_gemma":[0.9701719,0.01310309,0.01557834,0.0001124198,0.0001582213,0.00001867041,0.000008305414,0.00003197044,0.000817098],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9456009,"threshold_uncertainty_score":0.9547035,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2003628090","doi":"10.1081/etc-120015384","title":"FAST DOUBLE BOOTSTRAP TESTS OF NONNESTED LINEAR REGRESSION MODELS","year":2002,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":49,"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":"Linear regression; Econometrics; Statistics; Regression; Linear model; Regression analysis; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.4638274899201927,"gpt":0.4630849162894863,"spread":0.0007425736307064001,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007772266,0.0002151499,0.0009067262,0.0003098622,0.00005134262,0.00001183999,0.0002244514,0.00008773739,0.0007850197],"category_scores_gemma":[0.00114084,0.0001553877,0.0001870881,0.0008790198,0.00004928353,0.0002323584,0.00005662936,0.0001543927,0.0001165469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003642195,"about_ca_system_score_gemma":0.000007139846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003597699,"about_ca_topic_score_gemma":0.000001809594,"domain_scores_codex":[0.9981404,0.0001090867,0.001026276,0.0003327807,0.000130929,0.0002605035],"domain_scores_gemma":[0.9978966,0.0007776403,0.0005435784,0.0005666901,0.00007294402,0.0001426141],"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":[0.00002869272,0.00063218,0.0001299856,0.001522975,0.00004584439,0.000008628852,0.0004221846,0.0006122653,0.0001331714,0.1680597,0.008088664,0.8203157],"study_design_scores_gemma":[0.002859266,0.0004634939,0.000163826,0.001260414,0.0002009132,0.00003296203,0.00006595705,0.170227,0.0008614966,0.7276626,0.09513517,0.00106695],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005246174,0.02292746,0.9247698,0.00008957036,0.0002010619,0.001147361,0.00003831744,0.00005894357,0.0455213],"genre_scores_gemma":[0.04837161,0.01427773,0.9330101,0.00006465599,0.0001149425,0.00009034495,0.00000569837,0.0000468106,0.004018134],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8192487,"threshold_uncertainty_score":0.8595415,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1594311740","doi":"","title":"Implications of Structural Changes in the U.S. Economy for Pricing Behavior and Inflation Dynamics","year":2003,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":43,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Economics; Inflation (cosmology); Monetary policy; Quarter (Canadian coin); Monetary economics; Real interest rate; Macroeconomics; Inflation targeting","retraction":null,"screen_n_in":null,"score":{"opus":0.1176412105865101,"gpt":0.2879555238525582,"spread":0.1703143132660481,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001552826,0.0001464993,0.0005567297,0.0006282692,0.0000812493,0.00005064392,0.00019172,0.00006739826,0.0001715676],"category_scores_gemma":[0.0003064444,0.0001335,0.0001062672,0.000450301,0.00004171636,0.0002660556,0.0000156422,0.00008514962,0.00002228519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001222881,"about_ca_system_score_gemma":0.000008443235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009523058,"about_ca_topic_score_gemma":0.0001468791,"domain_scores_codex":[0.9984889,0.00003414586,0.0009359079,0.000295905,0.000007522526,0.0002376396],"domain_scores_gemma":[0.9987021,0.0002055401,0.0006858939,0.0003534156,0.00000786638,0.00004518604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003351567,0.00003402296,0.5842534,0.0001550377,0.00002060579,8.498129e-8,0.0005175881,0.0001785485,0.000001352204,0.3899486,0.0002553091,0.02463207],"study_design_scores_gemma":[0.0008747702,0.0001461212,0.7316678,0.00002036338,0.00003175626,0.00001963784,0.0001389198,0.008448113,0.00002161635,0.07586706,0.1823402,0.0004237261],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9416244,0.02493207,0.00183499,0.001258583,0.0001973578,0.002644194,0.0002714804,0.000009017393,0.02722791],"genre_scores_gemma":[0.995567,0.002377153,0.001165461,0.0003321967,0.00004541257,0.0003701536,0.00004110163,0.00001294913,0.00008859801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3140816,"threshold_uncertainty_score":0.5443971,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1601839985","doi":"","title":"Do Only Big Cities Innovate? Technological Maturity and the Location of Innovation","year":2005,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":42,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Institute on Governance","funders":"","keywords":"Productivity; Maturity (psychological); Disadvantage; Economic geography; Technological change; Section (typography); Technical change; Business; Economics; Industrial organization; Economic growth; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.06352569059663055,"gpt":0.2428921013556653,"spread":0.1793664107590347,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00323839,0.000161671,0.0008673239,0.001308965,0.00009333313,0.00008604014,0.0002907249,0.0001163416,0.0002038801],"category_scores_gemma":[0.001173143,0.0001222587,0.0001125433,0.004437161,0.0003262514,0.0002056718,0.00009097489,0.000164045,0.0002296403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008328375,"about_ca_system_score_gemma":0.00002519379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001268913,"about_ca_topic_score_gemma":0.00003124625,"domain_scores_codex":[0.997555,0.00003514712,0.001857553,0.0003584364,0.00002801161,0.0001658258],"domain_scores_gemma":[0.9979292,0.0001298967,0.001378536,0.000413336,0.0001218916,0.00002713964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009753731,0.00003127567,0.01155727,0.00004889576,0.00003902792,6.117354e-8,0.00004395585,0.00003721987,7.727911e-7,0.8547607,0.0004132977,0.1330578],"study_design_scores_gemma":[0.001076391,0.00004910835,0.03234065,0.00004188973,0.00002276548,0.000008912865,0.00005833946,0.003544909,0.00003018871,0.1448583,0.8176219,0.0003466262],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7331222,0.2002479,0.008927255,0.0172061,0.0003011679,0.001193329,0.00006020293,0.00004450411,0.03889735],"genre_scores_gemma":[0.967524,0.03034496,0.0009301853,0.0004981559,0.0001307442,0.00005455498,0.00001673186,0.00001006915,0.0004906171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8172086,"threshold_uncertainty_score":0.4985564,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2007833551","doi":"10.1081/etc-120014348","title":"IS ADAPTIVE ESTIMATION USEFUL FOR PANEL MODELS WITH HETEROSKEDASTICITY IN THE INDIVIDUAL SPECIFIC ERROR COMPONENT? SOME MONTE CARLO EVIDENCE","year":2002,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":41,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"University of British Columbia","keywords":"Estimator; Heteroscedasticity; Monte Carlo method; Component (thermodynamics); Econometrics; Computer science; Statistics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.547061538129529,"gpt":0.2933434904736456,"spread":0.2537180476558833,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00170677,0.0003055614,0.001017629,0.0009046672,0.0001514473,0.0002153657,0.0007315802,0.00009026664,0.0005005375],"category_scores_gemma":[0.000240879,0.0002372683,0.0002949677,0.001607845,0.00007137049,0.001399795,0.00006266353,0.0002065758,0.0006919873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001391433,"about_ca_system_score_gemma":0.000007022575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004452908,"about_ca_topic_score_gemma":0.00007617996,"domain_scores_codex":[0.9973994,0.00008545069,0.00130221,0.0007248212,0.00008914169,0.000398925],"domain_scores_gemma":[0.9978275,0.0004849761,0.0008489146,0.0007156569,0.00003408912,0.00008882495],"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":[0.0006142648,0.003587854,0.3042887,0.002087292,0.001936347,0.0000515072,0.03284199,0.2070762,0.000005438847,0.1127442,0.09217672,0.2425895],"study_design_scores_gemma":[0.001209708,0.0005066569,0.0732195,0.0002472661,0.0001212304,0.00001106492,0.0001774113,0.8646655,0.000003820283,0.008658162,0.05031465,0.0008650316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4661591,0.3505334,0.1666519,0.00328789,0.0006401125,0.006718866,0.003555043,0.00007153392,0.002382197],"genre_scores_gemma":[0.9737491,0.01948343,0.005078982,0.0008547421,0.0001345587,0.0004493165,0.00005691341,0.00002605314,0.0001669138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6575893,"threshold_uncertainty_score":0.9675519,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2127045881","doi":"10.1080/07474930802388066","title":"A Robust Entropy-Based Test of Asymmetry for Discrete and Continuous Processes","year":2008,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":35,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Resampling; Nonparametric statistics; Categorical variable; Statistics; Econometrics; Algorithm","retraction":null,"screen_n_in":null,"score":{"opus":0.07717391613269806,"gpt":0.230446603549896,"spread":0.1532726874171979,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007424725,0.0002225145,0.001481313,0.0008349361,0.0001348769,0.00004431412,0.0002241141,0.00006817061,0.0004128008],"category_scores_gemma":[0.001925544,0.0002142708,0.0003319888,0.001633051,0.00009737893,0.000189052,0.00004393281,0.00006625448,0.00006156545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004704503,"about_ca_system_score_gemma":0.00002984647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001548486,"about_ca_topic_score_gemma":0.0000208377,"domain_scores_codex":[0.9976833,0.0000158712,0.001485039,0.0005059198,0.00002977666,0.0002800897],"domain_scores_gemma":[0.9977778,0.0004099531,0.001205853,0.0004152527,0.00008044664,0.0001106973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004449838,0.0006041481,0.9217325,0.006154822,0.0004347584,0.000006113378,0.0003851122,0.0002982448,0.00001774954,0.03261073,0.01379096,0.02392029],"study_design_scores_gemma":[0.001323295,0.0004505166,0.01979265,0.0001086383,0.00006087151,0.00001551015,0.00004683629,0.005534463,0.00006734197,0.001005493,0.9710284,0.0005660133],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1328932,0.7332947,0.09338585,0.000957857,0.0006029592,0.004943082,0.002163267,0.0001014746,0.03165761],"genre_scores_gemma":[0.9748889,0.01533526,0.006880784,0.0001285621,0.000148354,0.0002380047,0.00005152772,0.00003873646,0.002289893],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9572374,"threshold_uncertainty_score":0.873771,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2061286507","doi":"10.1080/07474930903327856","title":"Local GMM Estimation of Semiparametric Panel Data with Smooth Coefficient Models","year":2009,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Lethbridge","funders":"","keywords":"Estimator; Panel data; Generalized method of moments; Monte Carlo method; Semiparametric regression; Semiparametric model; Econometrics; Estimation; Mathematics; Simple (philosophy); Applied mathematics; Statistics; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.2008198985909954,"gpt":0.2692362689091357,"spread":0.06841637031814035,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00163005,0.0003147945,0.001321169,0.001252821,0.00007222173,0.00008982855,0.001041184,0.0001298446,0.0002700579],"category_scores_gemma":[0.0002754519,0.0003074381,0.0001675484,0.002651218,0.00008897534,0.0009292988,0.0001107426,0.0001829183,0.0009142474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002052534,"about_ca_system_score_gemma":0.00003713676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008790001,"about_ca_topic_score_gemma":0.000006050551,"domain_scores_codex":[0.9967447,0.00002691768,0.001842165,0.0008840944,0.00005400837,0.0004481515],"domain_scores_gemma":[0.9967862,0.0001018409,0.001268008,0.001632645,0.00002991043,0.0001814128],"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":[0.00006958195,0.001017238,0.005402093,0.0003623512,0.0001453127,0.000006603757,0.0002566788,0.3832677,9.922104e-7,0.2089333,0.01706842,0.3834698],"study_design_scores_gemma":[0.001198183,0.0005556529,0.0102111,0.0001001508,0.00005357951,0.0000207028,0.00005601346,0.7623382,0.00002247151,0.02166772,0.2029554,0.0008208626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09529133,0.1524518,0.6222463,0.0009508923,0.0006413999,0.002323532,0.001033589,0.0001179174,0.1249433],"genre_scores_gemma":[0.9764028,0.01239994,0.01029053,0.0004269589,0.00004757259,0.000018464,0.0002066606,0.00002494564,0.0001821119],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8811115,"threshold_uncertainty_score":0.9999378,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2578201297","doi":"","title":"Social Movements and Counterhegemony : Canadian Contexts and Social Theories","year":2000,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Sociology; Positive economics; Political science; Social psychology; Psychology; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.02257020969710963,"gpt":0.2651488633515859,"spread":0.2425786536544763,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000754932,0.00008186882,0.0002683778,0.0005556467,0.001859205,0.0004453838,0.0001152695,0.00007545404,0.006516344],"category_scores_gemma":[0.00008483706,0.0001012493,0.00005632221,0.000407985,0.0005276978,0.0002517146,0.00001015277,0.00007784412,0.0002370544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005160059,"about_ca_system_score_gemma":0.000358455,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6675883,"about_ca_topic_score_gemma":0.9736537,"domain_scores_codex":[0.9991111,0.0001196345,0.0002240348,0.0001893887,0.00007978965,0.0002760147],"domain_scores_gemma":[0.999568,0.00003236151,0.00007160869,0.00005737804,0.00001773276,0.0002528676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002647215,0.000008197499,0.00160547,0.00003346394,0.00001651834,0.00000284892,0.01693414,1.240991e-8,1.087729e-7,0.04759122,0.04796839,0.885837],"study_design_scores_gemma":[0.00011946,0.00000714969,0.01340287,0.000005291218,0.000009611204,4.46674e-7,0.0003392546,4.090901e-7,2.392327e-8,0.002337337,0.9836664,0.0001117772],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.138032,0.07073391,0.000001202932,0.006189014,0.0003947315,0.0008204224,0.0001232728,0.0000294307,0.783676],"genre_scores_gemma":[0.829611,0.06799398,0.00001796479,0.004913099,0.0008223424,0.00005131795,0.00001431763,0.00001866768,0.0965573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.935698,"threshold_uncertainty_score":0.9994403,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2091513515","doi":"10.1080/07474930802458638","title":"A Note on Unit Root Tests with Infinite Variance Noise","year":2009,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Unit root; Estimator; Variance (accounting); Mathematics; Exploit; Delta method; Unit root test; Root (linguistics); Applied mathematics; Asymptotic analysis; Statistical hypothesis testing; Unit (ring theory); Statistics; Process (computing); Econometrics; Computer science; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.07021251798825065,"gpt":0.2743069846870708,"spread":0.2040944666988201,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001367204,0.0003486412,0.001085346,0.001036604,0.0001592239,0.0001228977,0.0004129818,0.0001365331,0.0004568718],"category_scores_gemma":[0.0008812835,0.0003309886,0.0002177138,0.002353158,0.00003690732,0.0004180587,0.00003074218,0.0003470263,0.004864864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001377487,"about_ca_system_score_gemma":0.00003838557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007088991,"about_ca_topic_score_gemma":0.00004026006,"domain_scores_codex":[0.9973544,0.00003354557,0.001308657,0.0007629871,0.00005039275,0.0004900534],"domain_scores_gemma":[0.9980142,0.0001527176,0.00074744,0.0008659493,0.00004183834,0.000177838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000216396,0.0009575986,0.2161454,0.0002396848,0.00006662769,0.00002153286,0.0008599133,0.003369072,0.000008726134,0.3374392,0.003455715,0.4372202],"study_design_scores_gemma":[0.0006893524,0.0005954513,0.2189735,0.0001497195,0.00001104545,0.000004776006,0.000003116658,0.003749042,0.000006813831,0.01547526,0.7597757,0.0005662545],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4346933,0.09718493,0.07423513,0.003069413,0.001126742,0.003155936,0.0002602806,0.0002736258,0.3860007],"genre_scores_gemma":[0.9847754,0.006257872,0.005594757,0.001510734,0.0002637478,0.00005801142,0.00002190618,0.0000363354,0.001481233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.75632,"threshold_uncertainty_score":0.9999142,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1525579751","doi":"","title":"Perspectives on a Potential North American Monetary Union","year":2000,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Global Financial Crisis and Policies","field":"Economics, Econometrics and Finance","cited_by":23,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Liberian dollar; Currency; Currency union; Context (archaeology); Economics; Monetary hegemony; International economics; Single currency; International trade; Monetary policy; Political science; Monetary economics; Geography; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.0243237616377837,"gpt":0.2312952690468519,"spread":0.2069715074090682,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006009769,0.000269822,0.0009777457,0.0006803055,0.0001413034,0.0000906049,0.0003473158,0.00004690771,0.00363978],"category_scores_gemma":[0.0001482837,0.0002738446,0.0003805951,0.00213608,0.0001001721,0.0002190962,0.00002934116,0.000183429,0.01459331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001509346,"about_ca_system_score_gemma":0.000009530127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009728981,"about_ca_topic_score_gemma":0.00006468262,"domain_scores_codex":[0.997947,0.00005679062,0.0009305538,0.0006035441,0.00004069897,0.0004214299],"domain_scores_gemma":[0.9987928,0.0000338042,0.0004523771,0.0005548316,0.00001770193,0.0001485014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006197529,0.0006673433,0.09817535,0.00008742346,0.000130498,0.00001373893,0.001990038,0.001076436,5.340187e-7,0.09168994,0.06041123,0.7456955],"study_design_scores_gemma":[0.0001598478,0.0002057377,0.2769674,0.000009160837,0.000006384445,0.000003048427,0.00006811514,0.0001011645,6.847904e-7,0.0007304015,0.7214678,0.0002803024],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7856436,0.07198335,0.00009051758,0.0008438081,0.0002806929,0.0004594413,0.0002026501,0.00004760094,0.1404484],"genre_scores_gemma":[0.8781872,0.1172292,0.0003589711,0.0008659516,0.0003818523,0.00004379866,0.0000294769,0.00002584392,0.002877633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7454152,"threshold_uncertainty_score":0.9999714,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1520276044","doi":"","title":"Characteristics of High-Foreclosure Neighborhoods in the Tenth District","year":2009,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Foreclosure; Quarter (Canadian coin); Financial crisis; Demographic economics; Economics; Business; Geography; Finance","retraction":null,"screen_n_in":null,"score":{"opus":0.03897548901475804,"gpt":0.232000980627959,"spread":0.193025491613201,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002722712,0.0002451695,0.00121079,0.0008063711,0.00006312315,0.0000919794,0.0006709262,0.0001182931,0.000528351],"category_scores_gemma":[0.000607398,0.0002093746,0.0002886819,0.001680452,0.00004806362,0.0002723096,0.0000356151,0.0002335614,0.0005278775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001330882,"about_ca_system_score_gemma":0.00001843492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008545665,"about_ca_topic_score_gemma":0.00001237468,"domain_scores_codex":[0.9971415,0.00006219029,0.001955774,0.0004274369,0.00003257639,0.0003804849],"domain_scores_gemma":[0.9978774,0.000155701,0.001148312,0.0007306027,0.00001642497,0.00007162456],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000256484,0.0004730999,0.4167759,0.0001495142,0.00003169632,0.000006003282,0.0004350324,0.00002068455,9.061818e-7,0.1588431,0.004844688,0.4183937],"study_design_scores_gemma":[0.0004148252,0.0001511141,0.7441477,0.00003260508,0.00001132483,0.000005062213,0.00001941091,0.0002827033,0.000002921707,0.01333031,0.2412982,0.0003038463],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7298219,0.02136827,0.0008943821,0.001692828,0.001045311,0.001265086,0.0002295841,0.00003276091,0.2436499],"genre_scores_gemma":[0.9675147,0.03110353,0.0004146652,0.0005527034,0.0001878579,0.00002679321,0.0000487082,0.00001687136,0.000134185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4180899,"threshold_uncertainty_score":0.8538048,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2086285495","doi":"10.1081/etc-120015787","title":"A CONSISTENT MODEL SPECIFICATION TEST BASED ON THE KERNEL SUM OF SQUARES OF RESIDUALS","year":2002,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Windsor","funders":"","keywords":"Mathematics; Test statistic; Null (SQL); Nonparametric statistics; Null distribution; Parametric statistics; Statistics; Asymptotic distribution; Statistic; Null hypothesis; Specification; Applied mathematics; Parametric model; Kernel (algebra); One- and two-tailed tests; Kernel density estimation; Explained sum of squares; Goldfeld–Quandt test; Statistical hypothesis testing; Z-test; Computer science; Discrete mathematics; Data mining","retraction":null,"screen_n_in":null,"score":{"opus":0.3826535017111033,"gpt":0.3762101953576314,"spread":0.0064433063534719,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001630415,0.0001115067,0.0005250382,0.000201245,0.00002668421,0.00001098609,0.0002082674,0.0000364579,0.001424412],"category_scores_gemma":[0.02083756,0.00006766497,0.0001335427,0.0006105918,0.0000818881,0.00002349056,0.00001844989,0.00007873636,0.00007197314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000280853,"about_ca_system_score_gemma":0.00001354383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004100391,"about_ca_topic_score_gemma":6.61435e-7,"domain_scores_codex":[0.9984711,0.0001973603,0.0009195227,0.0001719219,0.000128812,0.0001112721],"domain_scores_gemma":[0.9911149,0.007530187,0.0006260274,0.0006067738,0.00008119773,0.00004093326],"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":[0.0000104716,0.00101554,0.002409526,0.001231796,0.00002798959,4.751395e-7,0.0002338025,0.0001380256,0.000182008,0.8292939,0.04908173,0.1163747],"study_design_scores_gemma":[0.0008884948,0.0008609038,0.0103481,0.00118232,0.0002229606,0.000002031591,0.0001083501,0.5154784,0.004110416,0.4390232,0.02718424,0.0005906652],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03353037,0.027388,0.4165879,0.004240396,0.0002869365,0.005666775,0.0007051941,0.00006753287,0.5115269],"genre_scores_gemma":[0.7370401,0.00456235,0.2571163,0.0002730875,0.00003550802,0.0001146372,0.00000273109,0.00002091176,0.0008343146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7035097,"threshold_uncertainty_score":0.9994884,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2103221909","doi":"10.1080/07474938.2014.945385","title":"Imposing Theoretical Regularity on Flexible Functional Forms","year":2014,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":19,"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":"Pointwise; Curvature; Computer science; Mathematical economics; Bayesian probability; Flexibility (engineering); Applied mathematics; Econometrics; Mathematical optimization; Mathematics; Statistics; Artificial intelligence; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.05719663688226228,"gpt":0.2344063096654991,"spread":0.1772096727832368,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003311625,0.0002892133,0.000984494,0.0006459259,0.0001989254,0.0001502612,0.0003503147,0.000150537,0.005058379],"category_scores_gemma":[0.0006684001,0.0002770185,0.0004179177,0.0005476761,0.0001482993,0.0003533893,0.00009344369,0.0002536742,0.007043372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002155726,"about_ca_system_score_gemma":0.00001385827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001261379,"about_ca_topic_score_gemma":0.000001461387,"domain_scores_codex":[0.9973639,0.00004852377,0.00133963,0.0007347728,0.00003222359,0.0004809013],"domain_scores_gemma":[0.9981417,0.0002310236,0.0005935114,0.0008142248,0.00001886175,0.0002007018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001658487,0.00006168913,0.001791049,0.00003360105,0.00002402175,1.93782e-7,0.00002649176,0.0001037311,0.000001094585,0.979242,0.002865236,0.0158343],"study_design_scores_gemma":[0.0003549879,0.0001156265,0.002159904,0.00001835517,0.000005384878,0.000004526401,0.000005019124,0.001794952,0.00003167802,0.4623439,0.532888,0.0002776033],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05879058,0.01360826,0.06562676,0.001476551,0.001893195,0.0008521423,0.0000878932,0.0001292478,0.8575354],"genre_scores_gemma":[0.9893432,0.002943993,0.001457897,0.001813524,0.0005647857,0.00009637505,0.00004354811,0.00005119789,0.003685436],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9305527,"threshold_uncertainty_score":0.9999682,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2044921758","doi":"10.1080/07474930903562221","title":"Cointegrating Regressions with Time Heterogeneity","year":2010,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Heteroscedasticity; Econometrics; Cointegration; Economics; Error correction model; Mathematics; Statistics; Function (biology); Regression","retraction":null,"screen_n_in":null,"score":{"opus":0.09542220254182514,"gpt":0.2571975192475972,"spread":0.161775316705772,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001562455,0.0003153161,0.001025908,0.0006940243,0.0002019455,0.0001361333,0.0004324624,0.0001353844,0.008517129],"category_scores_gemma":[0.0005239299,0.0002671527,0.0002725791,0.000694577,0.00009224671,0.0005043488,0.00006436525,0.0004546177,0.01881361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006694317,"about_ca_system_score_gemma":0.00001645598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001755852,"about_ca_topic_score_gemma":0.0000771327,"domain_scores_codex":[0.9975828,0.00003048135,0.001209808,0.0006449943,0.0000229875,0.0005089433],"domain_scores_gemma":[0.997808,0.0001172828,0.0008764419,0.0009059015,0.00001016553,0.0002822284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001239557,0.001043584,0.5698206,0.0004993219,0.0008093994,0.00005501199,0.001183413,0.0007559246,0.0004074003,0.1078897,0.1483022,0.1691095],"study_design_scores_gemma":[0.0005223367,0.0001213012,0.01620761,0.00003705722,0.00001268345,0.00008180583,0.000006775179,0.004661323,0.00009516585,0.002057964,0.975615,0.0005809503],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8546588,0.01015629,0.0006847387,0.0006222462,0.0006310684,0.0007423512,0.0001849534,0.00008150961,0.132238],"genre_scores_gemma":[0.9795204,0.002124728,0.01009252,0.001016112,0.0005196201,0.000116148,0.00006174321,0.00006799602,0.006480691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8273129,"threshold_uncertainty_score":0.9999781,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2774057695","doi":"10.1080/07474938.2020.1808371","title":"Model selection in factor-augmented regressions with estimated factors","year":2020,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Generalization; Econometrics; Selection (genetic algorithm); Model selection; Factor analysis; Statistics; Regression; Sample (material); Equity (law); Panel data; Computer science; Cross-validation; Mathematics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.3770945068673583,"gpt":0.2927428878644437,"spread":0.0843516190029146,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000375075,0.0003344883,0.001095033,0.0008740379,0.00009393792,0.00008070951,0.0002917155,0.0001223726,0.001996523],"category_scores_gemma":[0.00038744,0.0003022814,0.0001747044,0.001662147,0.00003451931,0.0006291019,0.0000465312,0.0002977999,0.001499196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002449123,"about_ca_system_score_gemma":0.00002412513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002597774,"about_ca_topic_score_gemma":0.00004219951,"domain_scores_codex":[0.9974793,0.00003397099,0.001293391,0.0006845302,0.00002626273,0.0004826095],"domain_scores_gemma":[0.9986646,0.00006479858,0.0007003515,0.0002558182,0.000007279109,0.0003071411],"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":[0.00006144891,0.0001670786,0.9205452,0.0001756608,0.000104239,0.000003478221,0.001345488,0.06444317,0.00001929304,0.00300253,0.006018062,0.004114353],"study_design_scores_gemma":[0.001343365,0.0002716579,0.174282,0.00008784015,0.00001391028,0.00000499775,0.000038039,0.7664373,0.00005588359,0.001067198,0.05557923,0.000818529],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9706852,0.01122776,0.005231596,0.000980219,0.0001069772,0.0009437313,0.0002408302,0.00009131285,0.01049239],"genre_scores_gemma":[0.9928328,0.003733953,0.002036143,0.0007684971,0.00006492684,0.00005306205,0.00004702109,0.00004110968,0.0004225232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7462631,"threshold_uncertainty_score":0.999943,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2159861303","doi":"10.1080/07474938.2013.825177","title":"Bootstrap Confidence Sets with Weak Instruments","year":2013,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":14,"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":"Confidence interval; Statistics; Mathematics; CDF-based nonparametric confidence interval; Confidence distribution; Empirical likelihood; Confidence region","retraction":null,"screen_n_in":null,"score":{"opus":0.2213272789380408,"gpt":0.3945013055759235,"spread":0.1731740266378827,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006702142,0.0001805058,0.0005551098,0.0001831533,0.00005035607,0.00008970351,0.0002448197,0.00004679594,0.007631935],"category_scores_gemma":[0.002210228,0.0001188553,0.00006570067,0.0006502379,0.00006520261,0.000194047,0.00004153525,0.0001357544,0.002184217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003813234,"about_ca_system_score_gemma":0.00002581356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003766982,"about_ca_topic_score_gemma":0.000002488642,"domain_scores_codex":[0.9985992,0.0001339926,0.0006008709,0.0002850779,0.0001152068,0.0002656584],"domain_scores_gemma":[0.9983639,0.0006923931,0.0002909999,0.0004310301,0.00005796471,0.0001636933],"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":[0.000002584802,0.00007524453,0.005256334,0.0002877098,0.00003086125,0.000001156933,0.00005139671,1.156296e-7,0.000009087054,0.1854573,0.01622294,0.7926053],"study_design_scores_gemma":[0.000873604,0.0005502885,0.04461876,0.0005469227,0.0000913461,0.00004362146,0.0001014125,0.0006435899,0.0001735264,0.6857098,0.2658124,0.0008347413],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.2444649,0.01098674,0.2230868,0.0009145983,0.0007979598,0.00633613,0.00005287745,0.0002087085,0.5131513],"genre_scores_gemma":[0.2122853,0.004606699,0.7787465,0.0005762526,0.00008654151,0.0005579172,0.000004806129,0.00004256778,0.003093402],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7917706,"threshold_uncertainty_score":0.9985927,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2040313060","doi":"10.1081/etc-100106997","title":"DYNAMIC FACTOR MODELS","year":2001,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","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":"York University","funders":"","keywords":"Stochastic volatility; Dynamic factor; Skewness; Computer science; Econometrics; Factor analysis; Kurtosis; Volatility (finance); Mathematics; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.1297693207525027,"gpt":0.2741416645998117,"spread":0.144372343847309,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009425354,0.0002560639,0.0009565289,0.0008598095,0.0001269888,0.00009033102,0.0003980881,0.0001297852,0.001961294],"category_scores_gemma":[0.0003621704,0.0002776591,0.000363429,0.001423493,0.00003222968,0.0006788554,0.00007168602,0.0002077184,0.006043616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002076735,"about_ca_system_score_gemma":0.00001615594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001210928,"about_ca_topic_score_gemma":0.00002667972,"domain_scores_codex":[0.9973984,0.00002281232,0.001447407,0.000645846,0.00003149211,0.0004540952],"domain_scores_gemma":[0.998571,0.00005984899,0.0005361469,0.0006585813,0.00002412514,0.0001503031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003857182,0.0004747328,0.1334542,0.0002946493,0.0001109858,0.0000148071,0.001166204,0.002936616,0.000006202655,0.306208,0.005132189,0.5501628],"study_design_scores_gemma":[0.0003044067,0.00004584155,0.0118119,0.0000234995,0.000004811371,0.000005986288,0.00001052747,0.1562367,9.774768e-7,0.087773,0.7433428,0.0004395997],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2855867,0.3255762,0.1938317,0.0005659576,0.001446693,0.001309718,0.0001985843,0.0001572939,0.1913271],"genre_scores_gemma":[0.9006923,0.09109639,0.003693328,0.0003315492,0.0001017673,0.00007385615,0.00002102266,0.00004012458,0.003949638],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7382106,"threshold_uncertainty_score":0.9999676,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2155246368","doi":"10.1080/07474938.2015.1114285","title":"Invariant tests based on<i>M</i>-estimators, estimating functions, and the generalized method of moments","year":2016,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"Banco Santander; McGill University","keywords":"Mathematics; Wald test; Estimator; Invariant (physics); Applied mathematics; Score test; Context (archaeology); Type (biology); Nonlinear system; Generalized method of moments; Statistical hypothesis testing; Maximum likelihood; Statistics; Moment (physics)","retraction":null,"screen_n_in":null,"score":{"opus":0.1584239924684867,"gpt":0.4277161447266811,"spread":0.2692921522581945,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004150849,0.0001865967,0.0008190649,0.0002188336,0.00008988625,0.00001896487,0.0001522931,0.00004306016,0.0002401588],"category_scores_gemma":[0.0228105,0.00008644554,0.0001252231,0.0004684663,0.0001071953,0.0000909873,0.00005438115,0.00008050362,0.0000217053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000414581,"about_ca_system_score_gemma":0.00002417583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005057531,"about_ca_topic_score_gemma":6.573088e-7,"domain_scores_codex":[0.9978365,0.0006775288,0.0008687272,0.0003024695,0.0001218745,0.0001928737],"domain_scores_gemma":[0.9888123,0.009975105,0.0005628224,0.0004976905,0.00005533931,0.00009671829],"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":[0.00005843497,0.00009238117,0.0001509694,0.0003156243,0.00003911978,9.826169e-7,0.00003192591,0.000145469,0.00004562128,0.2694655,0.002500567,0.7271534],"study_design_scores_gemma":[0.005343748,0.0001938849,0.0002407819,0.000554371,0.0002350358,0.00001064526,0.00001088821,0.1501831,0.0001324946,0.813807,0.02888574,0.000402301],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002151183,0.001580986,0.9946595,0.000412062,0.0001497773,0.000752162,0.00003797332,0.00001820483,0.002174211],"genre_scores_gemma":[0.002256372,0.0006411703,0.9961128,0.0002420183,0.00005100324,0.0001875515,0.000001616517,0.00002134417,0.0004861263],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7267511,"threshold_uncertainty_score":0.9854208,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2001310465","doi":"10.1080/07474930008800470","title":"Alternative approaches to testing by variable addition","year":2000,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"McMaster University","funders":"Social Sciences and Humanities Research Council of Canada; University of New South Wales; Australian National University","keywords":"Variable (mathematics); Econometrics; Computer science; Statistics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.5961734657645038,"gpt":0.4171872828989383,"spread":0.1789861828655655,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009757277,0.0001477387,0.0004579702,0.0001265081,0.00006689087,0.00003165858,0.0001494986,0.00003474234,0.00324414],"category_scores_gemma":[0.00451633,0.0001227512,0.00005133443,0.0009406894,0.00001529435,0.0001472412,0.00002342516,0.00009966258,0.0004880549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007597067,"about_ca_system_score_gemma":0.000008980931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001082698,"about_ca_topic_score_gemma":3.829213e-7,"domain_scores_codex":[0.9987265,0.0001331717,0.0005112702,0.0003262384,0.00007319974,0.000229628],"domain_scores_gemma":[0.9979536,0.001483327,0.0001439651,0.0002589087,0.00001950304,0.000140726],"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":[0.000002768419,0.00006065149,0.000005983596,0.00007601402,0.000009142645,4.675954e-7,0.00004341359,0.0001202047,0.000004960356,0.07373951,0.01498464,0.9109522],"study_design_scores_gemma":[0.0001067915,0.00006956139,0.00000766032,0.00006477306,0.00001832654,0.000002690513,0.00000426121,0.004028026,0.00003238201,0.516995,0.4784966,0.0001739015],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003094331,0.001740717,0.8643256,0.00005236187,0.00005005896,0.0006268975,0.0001103425,0.00003193825,0.1327526],"genre_scores_gemma":[0.0007133511,0.0006308169,0.9938021,0.0002552875,0.000110782,0.0002431364,0.00001691124,0.00002161236,0.004206038],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9107783,"threshold_uncertainty_score":0.997667,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1997577129","doi":"10.1081/etc-100104079","title":"A CONSISTENT MODEL SPECIFICATION TEST FOR A REGRESSION FUNCTION BASED ON NONPARAMETRIC WAVELET ESTIMATION","year":2001,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto; University of Guelph","funders":"","keywords":"Nonparametric regression; Nonparametric statistics; Test statistic; Mathematics; Statistics; Kernel (algebra); Parametric statistics; Monte Carlo method; Statistic; Semiparametric regression; Kernel density estimation; Econometrics; Statistical hypothesis testing; Applied mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.1098881263387143,"gpt":0.3276402181372694,"spread":0.2177520917985551,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002265358,0.0002039217,0.0004110758,0.001376276,0.0001690048,0.0002170626,0.0003992598,0.00007670386,0.0000322083],"category_scores_gemma":[0.002664646,0.000162754,0.0002193525,0.003209469,0.00001812255,0.0004749256,0.00003251641,0.0001109389,0.0002342645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001960671,"about_ca_system_score_gemma":0.00006460219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002278495,"about_ca_topic_score_gemma":2.796546e-7,"domain_scores_codex":[0.9981951,0.0001519683,0.0006630686,0.0005610101,0.0001800476,0.0002487781],"domain_scores_gemma":[0.9974309,0.001085929,0.0004622704,0.0007996894,0.0001210076,0.0001002374],"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":[0.00003264544,0.00017614,0.00008771796,0.0000626774,0.000003898921,0.000001159157,0.00001855043,0.009279495,0.00008291014,0.001757086,0.005104927,0.9833928],"study_design_scores_gemma":[0.0006327878,0.0002875442,0.0009186096,0.00008251164,0.00001872806,0.000005596735,9.300867e-7,0.9417708,0.0001648392,0.002354397,0.0535792,0.000184078],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003159362,0.002158301,0.9908004,0.000555272,0.0002954693,0.001035592,0.000003484559,0.00007203039,0.004763479],"genre_scores_gemma":[0.0988465,0.001424221,0.8962038,0.001487569,0.0001290897,0.0003650815,0.00004143178,0.00002209065,0.001480212],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9832087,"threshold_uncertainty_score":0.6636915,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1564103086","doi":"","title":"Why Have the Dynamics of Labor Productivity Changed","year":2010,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Productivity; Business cycle; Economics; Nonfarm payrolls; Recession; Quarter (Canadian coin); Labour economics; Macroeconomics; Agriculture","retraction":null,"screen_n_in":null,"score":{"opus":0.04732986711505884,"gpt":0.2374236492740006,"spread":0.1900937821589418,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004353642,0.0002654569,0.001062141,0.000606596,0.0001452597,0.0000667052,0.0007008415,0.0001333546,0.00155146],"category_scores_gemma":[0.002115154,0.0002262758,0.0003176791,0.001141367,0.0002054652,0.0004388148,0.0001306506,0.0005101713,0.0007744504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008507209,"about_ca_system_score_gemma":0.00002628211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003355564,"about_ca_topic_score_gemma":0.0009456548,"domain_scores_codex":[0.9975029,0.0000671735,0.001279594,0.0007236018,0.00003100017,0.0003957756],"domain_scores_gemma":[0.9969066,0.0001606845,0.001329536,0.00143333,0.00005260916,0.0001172604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002328798,0.0003978788,0.5037616,0.0004135296,0.0001379022,9.353294e-7,0.0005465178,0.000007195978,0.00006057296,0.4004702,0.0270183,0.06716211],"study_design_scores_gemma":[0.0002668692,0.00005863477,0.06195056,0.000008998685,0.00001338678,0.000007921537,0.00002283023,0.000803599,0.0001855366,0.02026237,0.9160796,0.0003397116],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7909406,0.06332554,0.001843494,0.03290574,0.0074684,0.00348035,0.0009488626,0.00008494702,0.099002],"genre_scores_gemma":[0.9896665,0.004197491,0.001008356,0.001012749,0.0008160992,0.0001980753,0.00003890475,0.00004723206,0.003014609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8890613,"threshold_uncertainty_score":0.9993613,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2128828816","doi":"10.1080/07474930903451565","title":"Information-Theoretic Distribution Test with Application to Normality","year":2009,"lang":"en","type":"article","venue":"Econometric Reviews","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":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada; Pennsylvania State University","keywords":"Mathematics; Score test; Lagrange multiplier; Normality; Principle of maximum entropy; Applied mathematics; Exponential family; Fisher information; Maximum entropy probability distribution; Asymptotic distribution; Wald test; Empirical likelihood; Monte Carlo method; Statistics; Statistical hypothesis testing; Likelihood principle; Entropy (arrow of time); Likelihood function; Mathematical optimization; Estimation theory; Estimator; Quasi-maximum likelihood","retraction":null,"screen_n_in":null,"score":{"opus":0.03232107141213998,"gpt":0.2292298418503698,"spread":0.1969087704382299,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001237051,0.0002276101,0.0006386819,0.0005024587,0.0001230895,0.0001403472,0.0003120457,0.00007657918,0.0006100002],"category_scores_gemma":[0.0005360564,0.0002201952,0.0001307512,0.001154183,0.00003048208,0.001107421,0.00002390018,0.0001251693,0.01417939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002563813,"about_ca_system_score_gemma":0.00001109202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001105357,"about_ca_topic_score_gemma":0.000005014245,"domain_scores_codex":[0.9980187,0.00001613602,0.001251346,0.0003023189,0.00002587345,0.0003856633],"domain_scores_gemma":[0.9983714,0.00007310412,0.0006666802,0.0006328891,0.00001666527,0.0002392426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009582219,0.0005120064,0.1746885,0.0002870163,0.00008292322,0.000001138993,0.001220943,0.00488506,0.000003248256,0.4362489,0.05487505,0.3270994],"study_design_scores_gemma":[0.000339859,0.0002931765,0.1537553,0.00001539992,0.000008270507,0.000008758768,0.00001116969,0.002647633,0.00001320411,0.007871524,0.8346592,0.0003764969],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.307368,0.01353482,0.4319878,0.01182748,0.0005800157,0.006531259,0.002763123,0.0002946877,0.2251129],"genre_scores_gemma":[0.9940562,0.001343608,0.0009484365,0.002804174,0.0001291423,0.0001137162,0.0003406217,0.000009314705,0.000254843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7797841,"threshold_uncertainty_score":0.9865882,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1596084174","doi":"","title":"The Beige Book: Timely Information on the Regional Economy","year":2001,"lang":"en","type":"article","venue":"Econometric Reviews","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":"Atlanta; Quarter (Canadian coin); Variety (cybernetics); State (computer science); Economic indicator; Product (mathematics); Value (mathematics); Economics; Business; Political science; Geography; Macroeconomics; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.1475693480482196,"gpt":0.239640534058409,"spread":0.09207118601018943,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002956523,0.00029114,0.0006035845,0.0005177115,0.000608416,0.0004037815,0.0007746342,0.00009895951,0.004435833],"category_scores_gemma":[0.0004803417,0.0001959329,0.0003905578,0.0006431416,0.0001129633,0.001303525,0.00006813629,0.0002957537,0.04365613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002342461,"about_ca_system_score_gemma":0.00001857059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001381026,"about_ca_topic_score_gemma":0.000009755948,"domain_scores_codex":[0.997365,0.00006295802,0.001646026,0.0003476102,0.0000290295,0.0005493744],"domain_scores_gemma":[0.9971972,0.000547799,0.001108075,0.0009874813,0.00001256738,0.0001468954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002775011,0.00003975285,0.004747312,0.00001993722,0.00009460413,6.628556e-7,0.0002047633,0.0002260518,4.025316e-8,0.3670972,0.5930858,0.03445605],"study_design_scores_gemma":[0.0002338077,0.0000657593,0.00674463,0.0000108662,0.000005145053,0.0000132066,0.00002373846,0.00244276,0.000001203043,0.0154427,0.9747661,0.0002500177],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02614032,0.08672997,0.0004384965,0.03397921,0.0008851818,0.001771048,0.00008660374,0.00006120143,0.849908],"genre_scores_gemma":[0.5349267,0.299717,0.0002835782,0.1151863,0.002245268,0.00110612,0.0001871672,0.0001105379,0.04623731],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8036706,"threshold_uncertainty_score":0.9964743,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1433192250","doi":"10.1080/07474938.2018.1514023","title":"Generalized information matrix tests for copulas","year":2019,"lang":"en","type":"article","venue":"Econometric Reviews","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":"Concordia University","funders":"Russian Science Foundation","keywords":"Mathematics; Hessian matrix; Vine copula; Copula (linguistics); Nonparametric statistics; Goodness of fit; Parametric statistics; Applied mathematics; Fisher information; Statistical hypothesis testing; Monte Carlo method; Statistics; Econometrics","retraction":null,"screen_n_in":null,"score":{"opus":0.07249545447367114,"gpt":0.2925692431295293,"spread":0.2200737886558581,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001600787,0.0001946747,0.0008664376,0.0007793545,0.00008169701,0.000129402,0.000270147,0.0001191635,0.0009744066],"category_scores_gemma":[0.0006469336,0.0002093249,0.0003411637,0.0008302061,0.00001409586,0.00108712,0.00004442142,0.000104063,0.01111209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001423215,"about_ca_system_score_gemma":0.0000210916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008410904,"about_ca_topic_score_gemma":0.00000482382,"domain_scores_codex":[0.9977226,0.00001486554,0.001563404,0.0003423118,0.00002626159,0.0003305497],"domain_scores_gemma":[0.9984851,0.00009579416,0.000784558,0.0005000633,0.0000505446,0.00008397646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004556367,0.00008724787,0.1692923,0.0008474445,0.00004635298,1.537163e-7,0.0003296259,0.0005832471,0.000005213036,0.7348686,0.02254208,0.07135223],"study_design_scores_gemma":[0.0007132016,0.00007053376,0.006871948,0.00001970228,0.000005307154,8.428477e-7,0.000005645668,0.01553235,0.000005275135,0.01502436,0.9614858,0.0002650141],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6856416,0.1511928,0.0908745,0.000669613,0.004064022,0.007111792,0.000648514,0.0001513216,0.05964586],"genre_scores_gemma":[0.8974297,0.03280786,0.05597111,0.001720126,0.0006392816,0.0008723891,0.0005154238,0.00008715018,0.009956948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9389437,"threshold_uncertainty_score":0.9999388,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1513104179","doi":"","title":"Results of the Bank’s survey of wage-setting in Belgian firms","year":2008,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Economic Theory and Policy","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":"Wage; Economics; Labour economics; Efficiency wage; Indexation; Wage share; Survey data collection; Quarter (Canadian coin); Business; Monetary economics; Monetary policy","retraction":null,"screen_n_in":null,"score":{"opus":0.1028948614907427,"gpt":0.2622449728635152,"spread":0.1593501113727725,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005688435,0.00018686,0.001149471,0.0007626717,0.000066856,0.000009252706,0.0006579769,0.0001079532,0.0005195251],"category_scores_gemma":[0.003593255,0.0001656167,0.0002958325,0.001842602,0.0001485301,0.0001986103,0.0001234321,0.0002040071,0.00047867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001001728,"about_ca_system_score_gemma":0.00004279712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003303369,"about_ca_topic_score_gemma":0.0004695047,"domain_scores_codex":[0.9963519,0.0001934295,0.002738958,0.0004030149,0.00001665005,0.0002960218],"domain_scores_gemma":[0.9964564,0.0005538727,0.00201888,0.0008837246,0.00002467026,0.00006240317],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003586624,0.0001489417,0.944514,0.0001495361,0.00003784288,0.000001029084,0.0009856238,0.0001309098,0.000002222262,0.03866873,0.004537048,0.0107882],"study_design_scores_gemma":[0.0007104366,0.00004276653,0.8847064,0.00006071115,0.000002808949,0.000004546082,0.000009176018,0.00009899777,0.00008595415,0.003443803,0.1106321,0.0002022925],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9129262,0.02646744,0.00001735673,0.0002143627,0.0004387213,0.0005284831,0.0006091988,0.000006624947,0.05879159],"genre_scores_gemma":[0.9888952,0.009134566,0.0001801224,0.0001383318,0.00005403592,0.00001845972,0.00001922132,0.00001891056,0.001541141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.106095,"threshold_uncertainty_score":0.6753654,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1546200662","doi":"","title":"The Shadow Labor Supply and Its Implications for the Unemployment Rate","year":2013,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Unemployment; Economics; Shadow (psychology); Recession; Quarter (Canadian coin); Labour economics; Unemployment rate; Work (physics); Discouraged worker; Demographic economics; Government (linguistics); Economic shortage; Economic growth; Geography; Keynesian economics; Psychology","retraction":null,"screen_n_in":null,"score":{"opus":0.0625071621130385,"gpt":0.2729876891288406,"spread":0.2104805270158021,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00327739,0.0001816056,0.0004526383,0.0001504111,0.0005016968,0.0003836013,0.0004901775,0.00005527228,0.0003131134],"category_scores_gemma":[0.001220006,0.0001121221,0.00017217,0.0007911613,0.00005271369,0.0002382273,0.0001031807,0.0001112671,0.0005642836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000777398,"about_ca_system_score_gemma":0.0000154849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001279377,"about_ca_topic_score_gemma":0.00004087808,"domain_scores_codex":[0.998147,0.00005257929,0.001032017,0.0004065797,0.00001532819,0.0003465032],"domain_scores_gemma":[0.9973301,0.001247807,0.0005822364,0.0006630894,0.00007679105,0.00009994332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002607276,0.00002769627,0.04725704,0.00004773254,0.00005494834,2.830441e-8,0.0000391405,0.000005846211,0.000002004169,0.8923657,0.008054914,0.05214234],"study_design_scores_gemma":[0.0001775706,0.00002402942,0.2205703,0.000005192095,0.000008836164,6.792709e-7,0.000009503173,0.00165681,0.000001182132,0.1276432,0.6497633,0.0001393149],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1604859,0.6759841,0.002914009,0.1383614,0.001451504,0.009568985,0.001634889,0.000061412,0.009537783],"genre_scores_gemma":[0.77421,0.2145654,0.0004151421,0.002222071,0.000208594,0.00347935,0.00002972813,0.0000370035,0.004832713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7647225,"threshold_uncertainty_score":0.7252913,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2602810000","doi":"10.1080/07474938.2017.1307598","title":"On the relevance of weaker instruments","year":2017,"lang":"en","type":"article","venue":"Econometric Reviews","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":"Simon Fraser University","funders":"","keywords":"Spurious relationship; Estimator; Econometrics; Intuition; Generalized method of moments; Compatibility (geochemistry); Identification (biology); Computer science; Mathematics; Statistics; Psychology; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1851618425388522,"gpt":0.2780956850570744,"spread":0.09293384251822229,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001909884,0.0002020508,0.0008082741,0.0003312191,0.0003209932,0.0001272307,0.0009908811,0.0000727389,0.003032331],"category_scores_gemma":[0.002489644,0.0001594586,0.0003047132,0.0001743139,0.0001358918,0.0004217218,0.0001053075,0.0001748833,0.007679545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007995003,"about_ca_system_score_gemma":0.000007434342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002076349,"about_ca_topic_score_gemma":0.00000650492,"domain_scores_codex":[0.9980491,0.00002949903,0.001184284,0.0003958388,0.00002348101,0.0003177313],"domain_scores_gemma":[0.9959627,0.0001905174,0.001962479,0.001789153,0.000006122312,0.00008897068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002782773,0.0001652981,0.1006615,0.0001313541,0.0001711336,0.000001043105,0.0002283025,0.0001128631,0.00000252122,0.7859045,0.04576391,0.0668297],"study_design_scores_gemma":[0.0004655036,0.0001131026,0.09632739,0.00006049789,0.000007413611,0.00000253298,0.000006508182,0.001159908,0.0000575691,0.05636787,0.845138,0.0002937411],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6513628,0.01161821,0.00009538718,0.002466574,0.0009163408,0.0006710943,0.0001394402,0.00001140626,0.3327187],"genre_scores_gemma":[0.9828848,0.01187743,0.0001961819,0.0008705577,0.0001275726,0.00004834248,0.000003952769,0.00001963857,0.003971532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.799374,"threshold_uncertainty_score":0.997879,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1975137172","doi":"10.1080/07474938.2011.553538","title":"Bootstrap Unit Root Tests in Models with GARCH(1,1) Errors","year":2011,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","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":"National Circus School; Concordia University","funders":"","keywords":"Heteroscedasticity; Unit root; Autoregressive conditional heteroskedasticity; Mathematics; Monte Carlo method; Econometrics; Sample size determination; Statistics; Unit root test; Asymptotic analysis; Asymptotic distribution; Cointegration; Estimator","retraction":null,"screen_n_in":null,"score":{"opus":0.3153720633229867,"gpt":0.2847558251072748,"spread":0.03061623821571197,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001787637,0.0003170604,0.001107868,0.001570127,0.0000802742,0.00004491008,0.0004684333,0.0001386107,0.0008268182],"category_scores_gemma":[0.0002532621,0.0003115481,0.0001943187,0.00222446,0.00006940529,0.0007166936,0.00007016467,0.00033374,0.001167808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001295726,"about_ca_system_score_gemma":0.00004160798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001177706,"about_ca_topic_score_gemma":0.0008838744,"domain_scores_codex":[0.9970371,0.00004044449,0.00158248,0.0007410665,0.00004037016,0.0005585006],"domain_scores_gemma":[0.998436,0.00006248731,0.0005978758,0.0007087874,0.00003050792,0.0001643107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005642531,0.0003737137,0.8098889,0.0001969406,0.00003485453,0.00001449184,0.001631109,0.0009645542,4.318684e-7,0.1516545,0.000354617,0.0348295],"study_design_scores_gemma":[0.001567429,0.0004493344,0.6439979,0.0002450954,0.00002010683,0.00001281392,0.00008335598,0.03473273,0.0000134172,0.1546693,0.162862,0.001346546],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6887124,0.07634141,0.01594197,0.00009126466,0.0003072289,0.001289083,0.00005360793,0.00006590882,0.2171972],"genre_scores_gemma":[0.9868695,0.007157618,0.004873076,0.000110528,0.00005697943,0.0001271687,0.00001199832,0.00004457866,0.0007485343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2981572,"threshold_uncertainty_score":0.9999337,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406627774","doi":"10.1080/07474938.2024.2444229","title":"Heavy tail robust estimation and inference for average treatment effects","year":2025,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Inference; Estimation; Statistics; Econometrics; Mathematics; Computer science; Economics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.1512173140209095,"gpt":0.4156300426979224,"spread":0.2644127286770129,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0006448646,0.0001521906,0.00055664,0.0002354313,0.00007403112,0.00005830556,0.00007599192,0.00004880247,0.00009438258],"category_scores_gemma":[0.01016962,0.0001117462,0.00007757747,0.000457968,0.00002640632,0.00006535873,0.00002698141,0.00004485852,0.00002563228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009266318,"about_ca_system_score_gemma":0.00002960751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009198067,"about_ca_topic_score_gemma":0.000003223231,"domain_scores_codex":[0.9990087,0.0001103661,0.0004449624,0.0002476182,0.00003298032,0.0001554024],"domain_scores_gemma":[0.9940117,0.005507738,0.0001474145,0.0002416241,0.00003060078,0.00006091747],"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":[0.00000470687,0.0000531853,0.0002867013,0.0008738521,0.00001753033,2.720433e-7,0.00002883052,0.000007760003,0.000001730589,0.171865,0.001064441,0.825796],"study_design_scores_gemma":[0.001422116,0.0007394747,0.004260038,0.0006717074,0.000241524,0.000002130335,0.000008082299,0.07019375,0.000414311,0.7927658,0.1288904,0.0003906519],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004008671,0.008301421,0.98132,0.00012735,0.0001776346,0.001547479,0.00001890186,0.00002234962,0.004476172],"genre_scores_gemma":[0.02998761,0.007571498,0.9597235,0.0001955132,0.00003879895,0.0008431332,0.00001085355,0.00001217903,0.001616853],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8254054,"threshold_uncertainty_score":0.9981682,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1541482505","doi":"","title":"On Business Cycles and Countercyclical Policies","year":2001,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Economic Theory and Policy","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Business cycle; Surprise; Economics; Animal spirits; Productivity; Keynesian economics; Government (linguistics); Quarter (Canadian coin); Monetary economics; Macroeconomics; Market economy","retraction":null,"screen_n_in":null,"score":{"opus":0.06769369524346795,"gpt":0.2753914508333915,"spread":0.2076977555899235,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001080131,0.000254001,0.0008686357,0.0009031414,0.0001270654,0.000134006,0.0002832952,0.0001085204,0.002158139],"category_scores_gemma":[0.0006104767,0.0002587666,0.000146902,0.0009252576,0.0001080486,0.0003154394,0.00007180474,0.0001537617,0.007152137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009974921,"about_ca_system_score_gemma":0.000009138143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001887503,"about_ca_topic_score_gemma":0.00002265161,"domain_scores_codex":[0.9980502,0.00003677167,0.001012528,0.0005172041,0.00001079706,0.0003725665],"domain_scores_gemma":[0.9986379,0.0002389564,0.0004468035,0.0004993911,0.00001248715,0.0001645278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001694321,0.00007566167,0.03842264,0.00005167805,0.00002658875,0.000002464376,0.0001502994,0.00001360065,6.158087e-7,0.9313849,0.0051317,0.02472286],"study_design_scores_gemma":[0.0003463518,0.00005116141,0.06592892,0.00002825887,0.000004754938,0.00002910998,0.00001339205,0.00005416989,0.000002198817,0.1269858,0.8062463,0.0003095742],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7405281,0.03552663,0.0002309604,0.001464114,0.000436765,0.0003624186,0.00007695508,0.00004345494,0.2213306],"genre_scores_gemma":[0.9231403,0.06801011,0.0001479553,0.003377205,0.0004371222,0.00006683481,0.00001464476,0.00003805138,0.004767727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8043992,"threshold_uncertainty_score":0.9999865,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4319785721","doi":"10.1080/07474938.2022.2157965","title":"Yet another look at the omitted variable bias","year":2023,"lang":"en","type":"article","venue":"Econometric Reviews","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":"Université de Montréal","funders":"Japan Society for the Promotion of Science; Russian Science Foundation","keywords":"Imputation (statistics); Missing data; Estimator; Econometrics; Nonparametric statistics; Parametric statistics; Monte Carlo method; Instrumental variable; Mathematics; Data set; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.2574139572292435,"gpt":0.2660087955264099,"spread":0.008594838297166396,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003939049,0.0003208768,0.001020809,0.001012648,0.0002983483,0.000151197,0.0006363735,0.0001379827,0.02258535],"category_scores_gemma":[0.0009054503,0.0002628374,0.000383154,0.002560958,0.00009085432,0.0003629666,0.000212948,0.0002095736,0.1421176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002739118,"about_ca_system_score_gemma":0.00001666714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004268917,"about_ca_topic_score_gemma":0.00002609951,"domain_scores_codex":[0.9969452,0.00007920984,0.001525096,0.0006883334,0.00003083756,0.0007312961],"domain_scores_gemma":[0.9974304,0.0004148172,0.0008310765,0.001173997,0.000007211641,0.0001424611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000147427,0.00005861148,0.06030815,0.0001136074,0.0001846298,0.000003715756,0.0003651062,0.001327318,0.000004828821,0.02225762,0.9051713,0.01019043],"study_design_scores_gemma":[0.0003628757,0.00003537766,0.01719418,0.00001480481,0.00001075338,0.000008322304,0.00001327834,0.00385071,0.00001260131,0.007638834,0.9705187,0.0003395637],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.4016395,0.1087767,0.0005883063,0.006174345,0.003495241,0.002536404,0.0009215841,0.0003419578,0.475526],"genre_scores_gemma":[0.3953481,0.09945419,0.001177538,0.01747849,0.001642241,0.0008087552,0.0004916827,0.0003099503,0.4832891],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1195323,"threshold_uncertainty_score":0.9999824,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1528960478","doi":"10.1080/07474938.2013.808478","title":"Time-Deformation Modeling of Stock Returns Directed by Duration Processes","year":2014,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","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":"University of Waterloo; Canadian Imperial Bank of Commerce (Canada)","funders":"","keywords":"Econometrics; Volatility (finance); Duration (music); Autoregressive model; Stochastic volatility; Computer science; Stock (firearms); Mathematics; Economics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04523155177407061,"gpt":0.2356606529729679,"spread":0.1904291011988973,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001938622,0.0001847888,0.0008210296,0.0005674316,0.00009255537,0.00004641515,0.000222525,0.0001140903,0.0003023303],"category_scores_gemma":[0.002576845,0.0001935928,0.0001457858,0.001339196,0.0000241788,0.0006648254,0.0000336474,0.0001216847,0.0006396576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009257103,"about_ca_system_score_gemma":0.00002134782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001002757,"about_ca_topic_score_gemma":0.00001170564,"domain_scores_codex":[0.9974327,0.00004112993,0.001881985,0.0003734762,0.00004048927,0.000230212],"domain_scores_gemma":[0.998291,0.00008566031,0.001091912,0.0003672489,0.00009662469,0.00006762693],"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":[0.0003488183,0.002736381,0.1299618,0.01788079,0.0005460536,0.000001074023,0.01276179,0.08057631,0.0006210335,0.06963973,0.07162187,0.6133043],"study_design_scores_gemma":[0.0002356544,0.00006866543,0.0002944576,0.00006515221,0.000008500767,7.034695e-7,0.000008118218,0.9073751,0.00005595996,0.004564033,0.08707672,0.000246947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6098096,0.09439658,0.2577467,0.0002795576,0.0004895474,0.001655936,0.0002758065,0.0001746444,0.03517166],"genre_scores_gemma":[0.9873561,0.009621887,0.002124007,0.00006839279,0.00009975088,0.00005964265,0.0001566141,0.00002470293,0.0004889138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8267988,"threshold_uncertainty_score":0.8221717,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2252571361","doi":"10.1080/07474938.2019.1701809","title":"Efficiency bounds for semiparametric models with singular score functions","year":2019,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"","keywords":"Score; Semiparametric model; Mathematics; Semiparametric regression; Econometrics; Applied mathematics; Statistics; Computer science; Nonparametric statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.1973173200060575,"gpt":0.3646152224342311,"spread":0.1672979024281735,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001442361,0.000205843,0.0007337874,0.0005989002,0.00009551747,0.00008416968,0.0002257425,0.00006753224,0.000704752],"category_scores_gemma":[0.003806083,0.0001427659,0.0001666376,0.002447165,0.00004363607,0.0001475566,0.00003344909,0.0001298099,0.0003298322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008303914,"about_ca_system_score_gemma":0.00005651616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004845176,"about_ca_topic_score_gemma":0.000001026069,"domain_scores_codex":[0.9984177,0.00008403024,0.0006292617,0.000417158,0.0001254799,0.0003263636],"domain_scores_gemma":[0.9965339,0.002354601,0.0003107592,0.000576379,0.0001066282,0.0001177855],"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":[0.00002454219,0.0002739196,0.002140918,0.001224452,0.00005733349,7.846343e-7,0.00007930689,0.0001705672,0.00000809922,0.7424502,0.006424447,0.2471455],"study_design_scores_gemma":[0.001410449,0.001578385,0.000827849,0.0004355525,0.0002875282,0.00002185804,0.0000651166,0.05571349,0.00004057846,0.5863411,0.3523494,0.0009287351],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0196574,0.006647252,0.9368952,0.00003431118,0.0002906692,0.001824893,0.00002967562,0.00004255895,0.03457804],"genre_scores_gemma":[0.08428405,0.001106438,0.9079818,0.0002028187,0.000119982,0.000455202,0.00001520464,0.0000587142,0.005775853],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3459249,"threshold_uncertainty_score":0.771654,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1787998803","doi":"10.1080/07474938.2014.966634","title":"Large Sample Properties of the Three-Step Euclidean Likelihood Estimators under Model Misspecification","year":2014,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"University of Manchester","keywords":"Estimator; Mathematics; Applied mathematics; Statistics; Econometrics","retraction":null,"screen_n_in":null,"score":{"opus":0.2343833555617613,"gpt":0.3552505738465492,"spread":0.1208672182847879,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001967854,0.0001525458,0.000526273,0.0001218311,0.0000828018,0.00002804505,0.0003566192,0.00005403069,0.0003028597],"category_scores_gemma":[0.01101359,0.00008798746,0.0001539603,0.0005897882,0.0000582163,0.00006320801,0.00008254532,0.0001160438,0.00006836552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003951559,"about_ca_system_score_gemma":0.00003004785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001586177,"about_ca_topic_score_gemma":0.00001790184,"domain_scores_codex":[0.9984136,0.0002128483,0.0007972573,0.0002348524,0.0001256447,0.0002158055],"domain_scores_gemma":[0.9977845,0.0009031462,0.0004626197,0.0007064078,0.00007158246,0.00007177449],"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":[0.000003745385,0.0001348184,0.001923345,0.0006084042,0.00002081318,1.909576e-8,0.0001550329,0.00003372789,0.00005074788,0.8211896,0.002689021,0.1731908],"study_design_scores_gemma":[0.0002365156,0.00004537349,0.003772769,0.000191657,0.00006853278,9.366701e-7,0.00002796216,0.174827,0.0003692739,0.7898871,0.03034259,0.0002302343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009151113,0.002682371,0.9825101,0.0002031982,0.0001169783,0.0005804228,0.00002345371,0.00001958166,0.004712703],"genre_scores_gemma":[0.4445657,0.0008053965,0.5539997,0.0002806633,0.00006967122,0.00008405415,0.000002083445,0.00003076895,0.0001620445],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4354146,"threshold_uncertainty_score":0.9973171,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2047308938","doi":"10.1080/07474930903039246","title":"Length-bias Correction in Transformation Models with Supplementary Data","year":2009,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Monetary Policy and Economic Impact","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":"Western University","funders":"","keywords":"Estimator; Microdata (statistics); Robustness (evolution); Econometrics; Statistics; Mathematics; Observable; Truncation (statistics); Computer science; Census; Population; Demography","retraction":null,"screen_n_in":null,"score":{"opus":0.3302682273843924,"gpt":0.2856564408571911,"spread":0.04461178652720132,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002000701,0.000251887,0.0008332104,0.001190818,0.00007257031,0.00009192141,0.0005198639,0.00008244601,0.001714331],"category_scores_gemma":[0.00007816178,0.0002527382,0.0001009433,0.0009008126,0.00002141188,0.002045414,0.00003024637,0.0002118847,0.0008345597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002373981,"about_ca_system_score_gemma":0.00001400259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001176044,"about_ca_topic_score_gemma":0.0003231479,"domain_scores_codex":[0.9973513,0.00003936912,0.001543201,0.0006141589,0.00002654622,0.0004253525],"domain_scores_gemma":[0.9983381,0.00005791211,0.0005635254,0.000920591,0.000004608887,0.0001152527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002858901,0.001102555,0.1018776,0.0003237659,0.0002404718,0.00001354476,0.004045863,0.05865497,0.00000179216,0.08023587,0.1112883,0.6419294],"study_design_scores_gemma":[0.001609811,0.0003689011,0.03024874,0.00006412056,0.00001822378,0.00002321679,0.00008179937,0.3102177,0.000007797923,0.01342087,0.6432636,0.0006751996],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5592877,0.08285247,0.04047163,0.009075441,0.002561908,0.005831403,0.002795456,0.0001495964,0.2969744],"genre_scores_gemma":[0.9778477,0.01804741,0.001547606,0.001187139,0.0001444357,0.00003461779,0.0007208377,0.00001916091,0.0004511191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6412542,"threshold_uncertainty_score":0.9999925,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4384071184","doi":"10.1080/07474938.2023.2225947","title":"Automatic variable selection for semiparametric spatial autoregressive model","year":2023,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"Natural Science Foundation of Hunan Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Autoregressive model; Estimator; Parametric statistics; Semiparametric model; Applied mathematics; Model selection; Semiparametric regression; Mathematics; Monte Carlo method; Moment (physics); Selection (genetic algorithm); Parametric model; Mathematical optimization; Computer science; Statistics; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.106206180436186,"gpt":0.2822936655441785,"spread":0.1760874851079924,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002127893,0.0002904197,0.001209051,0.003067631,0.0002240171,0.0001598808,0.0004360373,0.000162604,0.002031385],"category_scores_gemma":[0.002224695,0.000299496,0.0004360144,0.006387152,0.00002864369,0.0004152929,0.00008254875,0.00014855,0.006353045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002170158,"about_ca_system_score_gemma":0.00004563783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005124536,"about_ca_topic_score_gemma":0.00003560537,"domain_scores_codex":[0.9971041,0.00003551225,0.001497898,0.000765073,0.0000513577,0.0005460474],"domain_scores_gemma":[0.9979504,0.0003227836,0.0009859261,0.0005281334,0.00005486638,0.0001578947],"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":[0.00004413916,0.0005046547,0.086541,0.002127094,0.001042761,0.000003499876,0.0006563526,0.04158605,0.00003737333,0.1960846,0.2708512,0.4005213],"study_design_scores_gemma":[0.0003245237,0.00005757437,0.002140475,0.00002150799,0.00004287406,0.000001652601,0.000004938806,0.7826931,0.000006697596,0.02406879,0.1903268,0.0003110245],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02472975,0.02938326,0.9164152,0.000575395,0.001961227,0.003658362,0.001996529,0.0006646833,0.02061567],"genre_scores_gemma":[0.7412068,0.03756845,0.1549755,0.002106779,0.002807621,0.006551948,0.004472455,0.0004285334,0.04988192],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7614397,"threshold_uncertainty_score":0.9999457,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2915237405","doi":"10.1080/07474938.2022.2140982","title":"Hamiltonian sequential Monte Carlo with application to consumer choice behavior","year":2023,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Canada Foundation for Innovation","keywords":"Markov chain Monte Carlo; Particle filter; Monte Carlo method; Computer science; Hybrid Monte Carlo; Bayesian inference; Random walk; Nonparametric statistics; Scalability; Bayesian probability; Algorithm; Statistical physics; Mathematical optimization; Econometrics; Artificial intelligence; Mathematics; Statistics; Physics; Kalman filter","retraction":null,"screen_n_in":null,"score":{"opus":0.05111570066422108,"gpt":0.3235668275476152,"spread":0.2724511268833941,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00102563,0.0001825628,0.0004111793,0.000651884,0.00009396982,0.0001447673,0.0007377014,0.0000546086,0.0000236314],"category_scores_gemma":[0.00009147774,0.0001433411,0.0001033889,0.00400757,0.00002079908,0.0003120734,0.0001628722,0.0001156648,0.001377102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006792051,"about_ca_system_score_gemma":0.00004350066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009317515,"about_ca_topic_score_gemma":0.00004659794,"domain_scores_codex":[0.9984071,0.0001228441,0.0004161342,0.0006063671,0.0001259037,0.0003216442],"domain_scores_gemma":[0.9985285,0.00008772829,0.0001688892,0.0009511805,0.00004897756,0.0002147615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001157516,0.00002369962,0.002000312,0.00003091685,0.00001047792,0.000005126498,0.0001186884,0.00002869322,0.00005998196,0.002963484,0.00491311,0.9898444],"study_design_scores_gemma":[0.0002370541,0.00008494574,0.02403904,0.00003166778,0.00003394543,0.00001518806,0.000001958016,0.005468468,0.00009350004,0.0002212927,0.9694221,0.0003508539],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007338152,0.003530384,0.9849117,0.000498216,0.0002602833,0.001372042,0.000006260371,0.0001595703,0.001923352],"genre_scores_gemma":[0.1186946,0.004473154,0.8655763,0.002267401,0.0003631581,0.003168435,0.00001429258,0.00006285055,0.005379866],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9894935,"threshold_uncertainty_score":0.9994004,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2186679808","doi":"10.1080/07474938.2017.1307918","title":"Diagnostics for the bootstrap and fast double bootstrap","year":2017,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Financial Risk and Volatility Modeling","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":"McGill University","funders":"","keywords":"Bootstrapping (finance); Computer science; Series (stratigraphy); Context (archaeology); Bootstrap model; Autocorrelation; Bootstrap aggregating; Econometrics; Statistics; Artificial intelligence; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.2612953706786453,"gpt":0.3362924053905873,"spread":0.07499703471194202,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00208847,0.0002187262,0.0007255186,0.0002361881,0.0009257565,0.0004838664,0.0006366051,0.0001072271,0.0001435884],"category_scores_gemma":[0.001697991,0.0001847587,0.0002658715,0.0001738177,0.000137866,0.0004248169,0.0001250364,0.0001707774,0.000288428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005139698,"about_ca_system_score_gemma":0.00001865534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002597266,"about_ca_topic_score_gemma":0.00006957039,"domain_scores_codex":[0.9980735,0.000008611268,0.0009731163,0.0005152781,0.00002429256,0.0004051992],"domain_scores_gemma":[0.9975734,0.0003574445,0.0008788813,0.001044905,0.00003037629,0.0001149949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004971146,0.000127533,0.2912823,0.0004058309,0.0001118586,0.000001485346,0.0004082339,0.00006698899,9.650286e-7,0.3397771,0.0151803,0.3525878],"study_design_scores_gemma":[0.0007342841,0.00006038835,0.1038503,0.00002943426,0.00002184059,0.00000186163,0.00001551358,0.006273196,0.000005818883,0.01528228,0.8734559,0.0002691918],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1139028,0.7540278,0.06937738,0.005068346,0.003351073,0.005046861,0.0005703912,0.00006688481,0.04858849],"genre_scores_gemma":[0.811731,0.1839132,0.001430516,0.0002646591,0.0004973751,0.0003433534,0.00001120937,0.00003516525,0.001773479],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.8582756,"threshold_uncertainty_score":0.7534243,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2032626449","doi":"10.1080/07474938.2014.944794","title":"Shrinkage of Variance for Minimum Distance Based Tests","year":2014,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Estimator; Inference; Statistics; Econometrics; Mathematics; Variance (accounting); Monte Carlo method; Maximization; Context (archaeology); Covariance; Entropy (arrow of time); Computer science; Mathematical optimization; Artificial intelligence; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.1520066283518316,"gpt":0.3924813729126459,"spread":0.2404747445608143,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002097586,0.0001342172,0.0006995935,0.0001400174,0.00003090204,0.00001568104,0.0002354378,0.00004455131,0.0003642921],"category_scores_gemma":[0.0257231,0.0001059928,0.0001469514,0.0005566329,0.00004470245,0.00004331737,0.00001996061,0.00005824791,0.00004086587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002315261,"about_ca_system_score_gemma":0.00001922226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001476399,"about_ca_topic_score_gemma":0.000001362456,"domain_scores_codex":[0.9985961,0.0001456978,0.0007553253,0.0002472941,0.0000665472,0.00018908],"domain_scores_gemma":[0.9927886,0.00614288,0.0004488223,0.0004789625,0.00006374216,0.0000769802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009079348,0.0001242351,0.001103811,0.001842579,0.00001038131,1.65252e-7,0.00001961595,0.000001412201,0.0000429328,0.6627007,0.006586006,0.3275591],"study_design_scores_gemma":[0.0006192243,0.0002779716,0.004204257,0.0002898662,0.00005503693,6.075776e-7,0.000002712914,0.01158803,0.0003088696,0.4161951,0.5661709,0.000287373],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007272447,0.001913976,0.9843623,0.00007175428,0.0001603217,0.0006348938,0.00005053521,0.00001413522,0.01206482],"genre_scores_gemma":[0.06360854,0.0003057502,0.9351265,0.0001876196,0.00008838251,0.0001851115,0.000003593538,0.00001860568,0.0004759007],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5595849,"threshold_uncertainty_score":0.9824836,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4396808157","doi":"10.1080/07474938.2024.2339149","title":"Semiparametric spatial autoregressive models with nonlinear endogeneity","year":2024,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Spatial and Panel Data Analysis","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":"University of Guelph","funders":"","keywords":"Endogeneity; Autoregressive model; Econometrics; Economics; STAR model; Nonlinear system; Semiparametric model; Mathematics; Nonlinear autoregressive exogenous model; Statistics; Autoregressive integrated moving average; Time series; Nonparametric statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.09078560606405126,"gpt":0.2504465969165445,"spread":0.1596609908524932,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001179838,0.0003805514,0.001254621,0.0024261,0.0001154822,0.0003500095,0.0005138594,0.0001366727,0.003065263],"category_scores_gemma":[0.0003010943,0.0003159034,0.0004547559,0.004074014,0.00007101714,0.0007540517,0.0001015063,0.0003010909,0.007428613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001955984,"about_ca_system_score_gemma":0.00005078724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001216306,"about_ca_topic_score_gemma":0.0001064469,"domain_scores_codex":[0.9970525,0.0000468922,0.001317792,0.001043288,0.00007243549,0.0004670871],"domain_scores_gemma":[0.9982374,0.0002022451,0.0004913749,0.0008128078,0.00003610672,0.0002200935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008572197,0.000630356,0.06150229,0.001855335,0.00218494,0.0002703619,0.001089251,0.006308284,0.000006782581,0.169477,0.03236894,0.7242208],"study_design_scores_gemma":[0.0003052907,0.0001439883,0.001707186,0.0001086751,0.00009513719,0.00002848356,0.0000108017,0.15677,0.00002734546,0.006277554,0.8338847,0.0006408145],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02112804,0.6523796,0.2004915,0.0006501231,0.001887922,0.001653835,0.002138469,0.0003332157,0.1193373],"genre_scores_gemma":[0.9041151,0.07277943,0.01371599,0.0005816684,0.001438028,0.0003849847,0.0006712657,0.0001440327,0.006169511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.882987,"threshold_uncertainty_score":0.9999293,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1498456452","doi":"","title":"Methodology or pricing: how can the greater volatility of consumer gas and electricity prices in Belgium be explained?","year":2009,"lang":"en","type":"article","venue":"Econometric Reviews","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":"Electricity; Liberalization; Economics; Volatility (finance); Consumption (sociology); Electricity price; Electricity market; Quarter (Canadian coin); Monetary economics; Financial economics; Market economy","retraction":null,"screen_n_in":null,"score":{"opus":0.146972348967975,"gpt":0.2937100663706184,"spread":0.1467377174026434,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006761958,0.0002834265,0.001442173,0.0008638786,0.00008993132,0.00006810013,0.0003841124,0.0001462729,0.0003479048],"category_scores_gemma":[0.00294075,0.0002044276,0.0001806725,0.001981792,0.0001150407,0.0002127961,0.000077917,0.0002925584,0.000005081446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001325326,"about_ca_system_score_gemma":0.00003244451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003354978,"about_ca_topic_score_gemma":0.0003788328,"domain_scores_codex":[0.9972011,0.0002438067,0.001425509,0.0006617135,0.000040648,0.0004271939],"domain_scores_gemma":[0.9972534,0.0008492201,0.001067606,0.0006878976,0.00004084356,0.0001010022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009614539,0.0001607089,0.925594,0.0002547909,0.00006038093,0.000002931885,0.0008391788,0.000001656654,0.00000819935,0.01070955,0.0009495286,0.06132291],"study_design_scores_gemma":[0.0008171382,0.0003327156,0.8549983,0.00003301661,0.00002923741,0.00001345499,0.00006610831,0.01678499,0.0000299483,0.01974842,0.1066852,0.0004614528],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9344159,0.05045872,0.002576188,0.003640584,0.0001992892,0.001469848,0.0001030014,0.00001783033,0.00711867],"genre_scores_gemma":[0.9765931,0.01934957,0.00299383,0.0005749736,0.00004499319,0.00004670408,0.000009579876,0.0000133426,0.000373934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1057357,"threshold_uncertainty_score":0.8336318,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4395075943","doi":"10.1080/07474938.2024.2334166","title":"Powerful t-tests in the presence of nonclassical measurement error","year":2024,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Simon Fraser University","funders":"Economic and Social Research Council; European Research Council; Social Sciences and Humanities Research Council of Canada","keywords":"Statistics; Null hypothesis; Statistic; Regression; Mathematics; Linear regression; Test statistic; Observational error; Zero (linguistics); Test (biology); Statistical hypothesis testing; Econometrics","retraction":null,"screen_n_in":null,"score":{"opus":0.4066661522746499,"gpt":0.4822527804047219,"spread":0.075586628130072,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00445793,0.0001186278,0.0004537439,0.0002179117,0.000014984,0.00002550357,0.000261757,0.00003471538,0.0001706275],"category_scores_gemma":[0.008236443,0.00006781863,0.0001213091,0.001038013,0.0000478922,0.00009357396,0.00003923583,0.0001774441,0.00007637442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006847754,"about_ca_system_score_gemma":0.00003547622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002951563,"about_ca_topic_score_gemma":0.000009106193,"domain_scores_codex":[0.9983437,0.0003164402,0.0006995305,0.0002437959,0.0002197018,0.0001768037],"domain_scores_gemma":[0.9969957,0.002447636,0.0001130129,0.000365573,0.00003376904,0.00004424657],"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":[0.00000550603,0.0002076674,0.00009099202,0.001499706,0.00002167192,0.00001610546,0.0006177361,0.00001352612,0.00003988279,0.4661115,0.01357386,0.5178018],"study_design_scores_gemma":[0.0001608148,0.0001352987,0.0007451699,0.0007123257,0.00005377498,0.00001019819,0.00005854258,0.004240014,0.00005941067,0.5461468,0.447476,0.0002016557],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003005706,0.07733037,0.8864798,0.001153682,0.000511451,0.001829121,0.00002607545,0.00003279107,0.02963103],"genre_scores_gemma":[0.4956767,0.007102262,0.4957252,0.0002348059,0.0001799,0.0002663952,0.0000020423,0.00004170176,0.0007709803],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5176002,"threshold_uncertainty_score":0.9860386,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2153013713","doi":"10.1081/etc-200028211","title":"Semiparametric Efficient Estimation of the Mean of a Time Series in the Presence of Conditional Heterogeneity of Unknown Form","year":2005,"lang":"en","type":"article","venue":"Econometric Reviews","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":"Université du Québec à Montréal","funders":"National Science Foundation","keywords":"Estimator; Mathematics; Kernel density estimation; Series (stratigraphy); Nonparametric statistics; Ergodic theory; Applied mathematics; Conditional expectation; Upper and lower bounds; Kernel (algebra); Conditional probability distribution; Statistics; Econometrics; Combinatorics; Mathematical analysis","retraction":null,"screen_n_in":null,"score":{"opus":0.06729178080974686,"gpt":0.2597942150857737,"spread":0.1925024342760268,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002586314,0.000150793,0.0009223624,0.0008311279,0.00003270369,0.000009080391,0.0005609693,0.00006840994,0.0004143023],"category_scores_gemma":[0.0008742437,0.0001109767,0.0003411097,0.001649565,0.0001855135,0.0002515749,0.00006852167,0.0001039797,0.00007469282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007886806,"about_ca_system_score_gemma":0.00002294208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001952557,"about_ca_topic_score_gemma":0.00003011054,"domain_scores_codex":[0.9973593,0.00008396283,0.002074672,0.0002295048,0.00005634968,0.0001961705],"domain_scores_gemma":[0.9968156,0.0003721507,0.002145918,0.0006124513,0.00002076969,0.00003307282],"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":[0.0001088864,0.001669914,0.1830785,0.002150161,0.0003200326,3.474415e-7,0.005360404,0.6837322,0.00007951567,0.08702308,0.002983515,0.0334935],"study_design_scores_gemma":[0.002045393,0.0006207066,0.610615,0.0003733404,0.00009175158,0.00002905714,0.0001103214,0.3188134,0.008181246,0.015901,0.04250536,0.0007133835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982038,0.01226803,0.000350502,0.0002022991,0.00007383504,0.0007186112,0.0003454552,0.000002252883,0.004001022],"genre_scores_gemma":[0.9971823,0.00177992,0.0007991898,0.00005437919,0.00002636228,0.0000275639,0.00001644498,0.000007708485,0.0001061477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4275365,"threshold_uncertainty_score":0.453632,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2105499585","doi":"10.1081/etc-200049135","title":"ROBUST ASYMPTOTIC INFERENCE IN AUTOREGRESSIVE MODELS WITH MARTINGALE DIFFERENCE ERRORS","year":2005,"lang":"en","type":"article","venue":"Econometric Reviews","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Concordia University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Autoregressive model; Estimator; Mathematics; Inference; Confidence interval; Martingale difference sequence; Econometrics; Statistics; Heteroscedasticity; Coverage probability; Likelihood function; Martingale (probability theory); Maximum likelihood; Computer science; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.2482348519432467,"gpt":0.3707023005753363,"spread":0.1224674486320896,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00119742,0.0003016233,0.0009163856,0.0004618763,0.00005891346,0.00006328084,0.0003747019,0.00008636178,0.0008026142],"category_scores_gemma":[0.006794699,0.0002098167,0.00008573149,0.001051656,0.00009147018,0.0002405107,0.00008436758,0.0003177802,0.0001769269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001577346,"about_ca_system_score_gemma":0.00006649641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002328056,"about_ca_topic_score_gemma":0.00008243039,"domain_scores_codex":[0.9976287,0.0002657724,0.0009992027,0.0004886239,0.0001705946,0.0004470702],"domain_scores_gemma":[0.9962081,0.002509067,0.0005033511,0.0005427612,0.00006551923,0.0001712383],"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":[0.00002566177,0.0004389977,0.01918237,0.0005998776,0.00003423879,0.00001466712,0.0009137821,0.002863406,0.000008096332,0.2989957,0.0008319892,0.6760913],"study_design_scores_gemma":[0.002247025,0.0007298703,0.07419302,0.002822346,0.0001682545,0.00002504811,0.0001785363,0.4092544,0.0001101203,0.494168,0.01394496,0.002158439],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1370227,0.00897544,0.8044029,0.0004375689,0.0001822612,0.001866687,0.00002973919,0.0001202787,0.04696235],"genre_scores_gemma":[0.4322253,0.001432415,0.5649632,0.000173128,0.00007654644,0.0001946794,0.000002740994,0.00002954948,0.0009025425],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6739328,"threshold_uncertainty_score":0.8788062,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}