{"meta":{"query_hash":"615d878141df","filters":{"venue":"Oxford Bulletin of Economics and Statistics"},"cohort_total":48,"direct_labels_cover":0,"predictions_cover":48,"exported":48,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/615d878141df","api":"https://metacan.xera.ac/api/v1/cohort?venue=Oxford+Bulletin+of+Economics+and+Statistics"},"results":[{"id":"W1506485548","doi":"10.1111/j.1468-0084.2012.00726.x","title":"Multinational Exposure and the Quality of New Chinese Exports","year":2012,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"PricewaterhouseCoopers (Canada)","funders":"","keywords":"Multinational corporation; Exploit; Business; China; Competition (biology); Quality (philosophy); International trade; Product (mathematics); Industry of China; Industrial organization; International economics; Economics","score_opus":0.04489256879484641,"score_gpt":0.24107671947600703,"score_spread":0.19618415068116063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1506485548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9992908,0.00005343591,0.00002782997,0.000024165312,0.0000014365446,0.0000017140013,0.00009132775,0.0000010838282,0.00050818],"genre_scores_gemma":[0.99959713,0.0000385164,0.000016460202,0.0000047083367,0.0000050180674,8.9900897e-7,0.00011069954,6.023321e-7,0.00022600652],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996238,0.00005817267,0.000050936134,0.00010148503,0.00010057521,0.00006507826],"domain_scores_gemma":[0.9929299,0.0009978616,0.0044442723,0.00042883743,0.00048436847,0.00071478053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076242647,0.00014021421,0.0002353581,0.0011672387,0.0003233927,0.00091755163,0.00024484668,0.00027581688,0.004152831],"category_scores_gemma":[0.0035071878,0.00011231,0.00021406179,0.0016100178,0.00041400935,0.00064037164,0.0007409687,0.00035722528,0.0002014441],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020277725,0.000017741957,0.9977355,0.000008857009,0.000031826792,0.00007168429,0.00023944426,0.00013666158,0.00024276029,0.00008572036,0.000042969717,0.0013666281],"study_design_scores_gemma":[8.739168e-7,0.000010539284,0.99929225,0.0000026664613,0.0000075236644,0.000025884303,0.00021779178,0.00023439835,0.000051538726,0.00002554064,0.0001288631,0.000002153302],"about_ca_topic_score_codex":0.011435307,"about_ca_topic_score_gemma":0.014891707,"teacher_disagreement_score":0.011435307,"about_ca_system_score_codex":0.00051646103,"about_ca_system_score_gemma":0.00023370248,"threshold_uncertainty_score":0.022737503},"labels":[],"label_agreement":null},{"id":"W1592242128","doi":"10.1111/obes.12256","title":"Local Labour Markets and Theft: New Evidence from Canada","year":2018,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"St. Francis Xavier University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Microdata (statistics); Unemployment; Economics; Exploit; Labour economics; Affect (linguistics); Demographic economics; Unemployment rate; Panel data; Econometrics; Macroeconomics; Demography; Census","score_opus":0.02756455732426215,"score_gpt":0.275669151880202,"score_spread":0.24810459455593986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1592242128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9440232,0.007839261,0.00045309644,0.00399824,0.000061774714,0.000064164946,0.014402651,0.00001890042,0.029138807],"genre_scores_gemma":[0.9896678,0.0044021066,0.0001720018,0.00030835596,0.00002459156,0.000012601749,0.002593687,0.000011587761,0.002807411],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99849534,0.00017144508,0.00007202062,0.00016107711,0.0005113999,0.00058879907],"domain_scores_gemma":[0.990388,0.0018194932,0.0016180238,0.00048498515,0.0044501876,0.0012393261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012391525,0.0002872761,0.00068649,0.0030424225,0.0038078716,0.0022762972,0.001285808,0.00043464356,0.009027922],"category_scores_gemma":[0.0063294256,0.00025991097,0.0006467088,0.010462207,0.0016529881,0.00051974464,0.0016103068,0.001285292,0.00038427926],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002946382,0.00012788306,0.9356956,0.00041259077,0.00027965146,0.0006301544,0.00596257,0.0010320703,0.00010303473,0.0057095187,0.015257885,0.03449443],"study_design_scores_gemma":[0.000034348213,0.000025277173,0.9732464,0.0005013341,0.00016875032,0.00008619869,0.011063366,0.00069806655,0.000118814394,0.0006474283,0.0133732,0.00003692818],"about_ca_topic_score_codex":0.9973092,"about_ca_topic_score_gemma":0.9986014,"teacher_disagreement_score":0.0265282,"about_ca_system_score_codex":0.0265282,"about_ca_system_score_gemma":0.035579134,"threshold_uncertainty_score":0.19247645},"labels":[],"label_agreement":null},{"id":"W1650048122","doi":"10.1111/obes.12111","title":"Envy and Habits: Panel Data Estimates of Interdependent Preferences","year":2015,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Ministerio de Ciencia y Tecnología","keywords":"Consumption (sociology); Interdependence; Preference; Economics; Panel data; Econometrics; Revealed preference; Fraction (chemistry); Set (abstract data type); Microeconomics; Computer science","score_opus":0.10690260924830504,"score_gpt":0.2441959172350624,"score_spread":0.13729330798675737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1650048122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95769525,0.00046452144,0.023940414,0.00066722697,0.000038739574,0.000055510933,0.0134620415,0.000122474,0.0035539044],"genre_scores_gemma":[0.9775023,0.00027114147,0.007294805,0.00012029857,0.000052209412,0.00009084796,0.012640514,0.000025511972,0.0020023815],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99793833,0.0012488231,0.00008896217,0.0003903942,0.00018676664,0.00014665356],"domain_scores_gemma":[0.9780245,0.011604733,0.0064224014,0.0027830712,0.0005498851,0.0006154038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003907213,0.00054804207,0.0007798133,0.0017444537,0.0005491153,0.0016550748,0.0009787505,0.001161505,0.007079998],"category_scores_gemma":[0.015907481,0.0004323598,0.0010911609,0.0033451065,0.0005538347,0.0010283402,0.0012530283,0.0021296637,0.0012575609],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042500254,0.0004691593,0.89047503,0.000107935884,0.0023745927,0.0002714323,0.00059474277,0.05790539,0.0005227446,0.013263039,0.008875944,0.024714908],"study_design_scores_gemma":[0.0001737395,0.0003621997,0.7780405,0.00009326455,0.00073490525,0.00034353542,0.0007183205,0.17775281,0.0010378503,0.03041591,0.010170231,0.00015669197],"about_ca_topic_score_codex":0.0141112385,"about_ca_topic_score_gemma":0.012651928,"teacher_disagreement_score":0.0141112385,"about_ca_system_score_codex":0.0004917725,"about_ca_system_score_gemma":0.00030947075,"threshold_uncertainty_score":0.02805823},"labels":[],"label_agreement":null},{"id":"W2008509138","doi":"10.1111/j.1468-0084.2005.00128.x","title":"The Cost Effectiveness of the UK's Sovereign Debt Portfolio*","year":2005,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Predictability; Economics; Debt; Portfolio; Interest rate; Project portfolio management; Financial economics; Monetary economics; Econometrics; Finance","score_opus":0.029961851694119,"score_gpt":0.21627056328081065,"score_spread":0.18630871158669166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008509138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961415,0.00013962084,0.0006497708,0.00022501759,0.0000063597304,0.0000059248123,0.00020738156,0.000020968895,0.0026035015],"genre_scores_gemma":[0.9995189,0.000022517917,0.00008947511,0.00000704826,0.0000014772082,0.000001714108,0.00008500038,0.0000029684627,0.0002711204],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99909735,0.00038880474,0.000063249114,0.00012992353,0.00014496062,0.00017577043],"domain_scores_gemma":[0.9932221,0.0041394155,0.0013604577,0.0004832436,0.00055704924,0.00023771639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019479452,0.0003007686,0.00045934314,0.00058418425,0.00031911442,0.0019476949,0.0004901135,0.0009614877,0.0026885928],"category_scores_gemma":[0.017060569,0.00029353454,0.00039884544,0.00067715964,0.00050895195,0.0016470961,0.0007711584,0.0008011055,0.0002073409],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012272609,0.00014186428,0.085948616,0.00008792993,0.00017211576,0.00041495115,0.0002055819,0.8655104,0.0018812272,0.015288547,0.001776641,0.027344797],"study_design_scores_gemma":[0.00016623193,0.0008985436,0.16868077,0.000057620564,0.00019330673,0.00039141238,0.00038690356,0.8131067,0.0032374281,0.010292756,0.0025004097,0.00008785911],"about_ca_topic_score_codex":0.023406452,"about_ca_topic_score_gemma":0.013457313,"teacher_disagreement_score":0.023406452,"about_ca_system_score_codex":0.0032308104,"about_ca_system_score_gemma":0.00057026785,"threshold_uncertainty_score":0.04654044},"labels":[],"label_agreement":null},{"id":"W2032683857","doi":"10.1111/j.1468-0084.2006.00151.x","title":"Occupational Labour Demand and the Sources of Non‐neutral Technical Change*","year":2006,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Technical change; Dispose pattern; Neutrality; Context (archaeology); Economics; Econometrics; Computer science; Macroeconomics; Law","score_opus":0.021046713398011924,"score_gpt":0.2173217031332377,"score_spread":0.19627498973522578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032683857","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97835404,0.00021409724,0.006330411,0.00077714224,0.0000123101445,0.000022073686,0.0005257876,0.000017484634,0.013746667],"genre_scores_gemma":[0.99860805,0.000035648896,0.00023308357,0.000013973468,0.000008703465,0.0000045493234,0.00015021475,0.0000027658248,0.00094300817],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99891984,0.00029697552,0.000087043525,0.00014529412,0.0004118334,0.00013903945],"domain_scores_gemma":[0.9887228,0.006762917,0.0020118388,0.0011378548,0.0010492932,0.00031527795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021104668,0.00016587011,0.00032153216,0.0012783599,0.0003280578,0.0017086156,0.0004619767,0.0005224038,0.0048257746],"category_scores_gemma":[0.011853394,0.00020537511,0.00033883227,0.0011883004,0.0011122137,0.0010065209,0.0011557825,0.00061716593,0.00062418974],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050421647,0.00026861147,0.8187955,0.00014823981,0.00021232365,0.0007175012,0.00300934,0.022566328,0.006815075,0.08493988,0.0009726259,0.061050314],"study_design_scores_gemma":[0.000022882834,0.00012604418,0.8904793,0.00004617921,0.000037844275,0.00032212242,0.0035363652,0.029086173,0.0018432119,0.06892142,0.00552012,0.000058374993],"about_ca_topic_score_codex":0.0024213456,"about_ca_topic_score_gemma":0.0015660037,"teacher_disagreement_score":0.0048257746,"about_ca_system_score_codex":0.0012607829,"about_ca_system_score_gemma":0.0003919153,"threshold_uncertainty_score":0.016143799},"labels":[],"label_agreement":null},{"id":"W2039708668","doi":"10.1111/j.1468-0084.2007.00491.x","title":"Measurement Error in Access to Markets*","year":2008,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Econometrics; Observational error; Standard deviation; Observable; Economics; Statistics; Standard error; Errors-in-variables models; Mathematics","score_opus":0.1387924511343704,"score_gpt":0.2319030391662739,"score_spread":0.0931105880319035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039708668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8230553,0.004408763,0.13528466,0.0065846117,0.0008950216,0.0003838644,0.0062305764,0.0002360607,0.02292111],"genre_scores_gemma":[0.99367565,0.00024175357,0.0038277046,0.00022488185,0.00009405364,0.000106386644,0.0009333724,0.000022487166,0.00087371626],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9061382,0.057740673,0.01013909,0.008106782,0.016336458,0.0015388692],"domain_scores_gemma":[0.5288664,0.31178358,0.08476185,0.047927283,0.025169056,0.0014917986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.060124744,0.00040698916,0.0007605278,0.0018475368,0.00080956763,0.0024966495,0.0013891105,0.0008464403,0.0030376099],"category_scores_gemma":[0.29901436,0.00031293847,0.00073769706,0.0049099536,0.002399295,0.0017820285,0.0024924763,0.0016271074,0.00047679394],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019378818,0.00010621724,0.9392826,0.00048025744,0.0009499326,0.00010998827,0.002616527,0.0033098783,0.00030765712,0.022111505,0.002847376,0.027684228],"study_design_scores_gemma":[0.00005649158,0.0003150691,0.9086445,0.00087418064,0.000552383,0.0006737522,0.0024450538,0.015935011,0.0048470553,0.04865567,0.01688866,0.00011220516],"about_ca_topic_score_codex":0.0074087414,"about_ca_topic_score_gemma":0.0030246023,"teacher_disagreement_score":0.060124744,"about_ca_system_score_codex":0.0011170215,"about_ca_system_score_gemma":0.000988588,"threshold_uncertainty_score":0.3179738},"labels":[],"label_agreement":null},{"id":"W2041103157","doi":"10.1111/j.1468-0084.2004.00086.x","title":"Calculating a Standard Error for the Gini Coefficient: Some Further Results*","year":2004,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":93,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Jackknife resampling; Standard error; Gini coefficient; Statistics; Mathematics; Regression; Econometrics; Ordinary least squares; Coefficient of determination; Inequality; Economic inequality; Mathematical analysis","score_opus":0.052846847448516254,"score_gpt":0.24046928872519602,"score_spread":0.18762244127667976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041103157","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016647177,0.004111861,0.96395606,0.0031611314,0.0005495135,0.0000752104,0.00025298225,0.00022734047,0.011018747],"genre_scores_gemma":[0.4839271,0.0058414624,0.4956321,0.0012869375,0.0019030772,0.00047544544,0.0010398459,0.0009065139,0.008987519],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9888764,0.0060253222,0.0005193654,0.0018232398,0.0023376492,0.00041806014],"domain_scores_gemma":[0.9318153,0.05148384,0.0027617,0.007484596,0.005961064,0.0004934751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024091428,0.0010859594,0.0017828565,0.004691204,0.0013251576,0.002679962,0.0026870088,0.0015823352,0.0046175034],"category_scores_gemma":[0.1309185,0.0005237105,0.0020251367,0.005933446,0.0032896476,0.0048455843,0.0030365111,0.0044210074,0.0011898222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039624974,0.00006899951,0.009266367,0.00020622858,0.0002242588,0.00017818855,0.00078703073,0.0593944,0.00087305903,0.81983984,0.007975955,0.10114598],"study_design_scores_gemma":[0.000009296801,0.00003676139,0.0048209974,0.00017659088,0.00004591385,0.00014505592,0.00015485982,0.14702392,0.0011197594,0.83348525,0.012912003,0.00006959885],"about_ca_topic_score_codex":0.005652075,"about_ca_topic_score_gemma":0.0030071249,"teacher_disagreement_score":0.024091428,"about_ca_system_score_codex":0.0028118426,"about_ca_system_score_gemma":0.0012015662,"threshold_uncertainty_score":0.12740916},"labels":[],"label_agreement":null},{"id":"W2041493247","doi":"10.1111/1468-0084.00163","title":"A Method to Calculate the Jackknife Variance Estimator For the Gini Coefficient","year":2000,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":86,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Statistics Canada; Employment and Social Development Canada","funders":"","keywords":"Jackknife resampling; Statistics; Variance (accounting); Estimator; Citation; Econometrics; Gini coefficient; Sociology; Library science; Mathematics; Computer science; Economics; Inequality; Economic inequality; Accounting","score_opus":0.04345570900117523,"score_gpt":0.2516128963748438,"score_spread":0.20815718737366856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041493247","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013503529,0.00011740089,0.9969303,0.000062327534,0.00010865524,0.0000511813,0.00009358327,0.00060886133,0.00067745615],"genre_scores_gemma":[0.031339955,0.00016905024,0.9644051,0.0001159146,0.0001245284,0.0003514398,0.00051254046,0.00087268464,0.0021088158],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.990031,0.005511589,0.00044726804,0.001661582,0.001958653,0.0003898244],"domain_scores_gemma":[0.9820218,0.009881699,0.0010971318,0.0034035628,0.0033561827,0.0002396307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011376968,0.001222043,0.002012379,0.0054422864,0.0018826833,0.0021414694,0.0034188027,0.0020446496,0.007822263],"category_scores_gemma":[0.072538175,0.0011694323,0.0018769919,0.0044761226,0.0014537651,0.0025437642,0.0022490646,0.0043284656,0.004359732],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019579446,0.00022436859,0.013340476,0.0004273719,0.0010072135,0.000298921,0.0011119,0.055401675,0.004057271,0.24140367,0.0438365,0.6386948],"study_design_scores_gemma":[0.00017684673,0.0001521831,0.01170915,0.000428231,0.00028773767,0.0014699462,0.0004998858,0.4974107,0.009922389,0.41054076,0.06697855,0.00042354927],"about_ca_topic_score_codex":0.0070716226,"about_ca_topic_score_gemma":0.008765032,"teacher_disagreement_score":0.011376968,"about_ca_system_score_codex":0.0009313591,"about_ca_system_score_gemma":0.0020871747,"threshold_uncertainty_score":0.06016785},"labels":[],"label_agreement":null},{"id":"W2058523879","doi":"10.1111/j.1468-0084.2004.099_1.x","title":"Evaluating New‐Keynesian Models of a Small Open Economy*","year":2004,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; New Keynesian economics; Vector autoregression; Small open economy; Variance decomposition of forecast errors; Impulse response; Structural vector autoregression; Open economy; Monetary policy; Exchange rate; Econometrics; Variance (accounting); Keynesian economics; Taylor rule; Exchange-rate pass-through; Macroeconomics; Central bank; Mathematics","score_opus":0.16365310047014012,"score_gpt":0.2771896103074896,"score_spread":0.1135365098373495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058523879","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45293313,0.0007886799,0.5288743,0.0012436969,0.00017745045,0.00008536586,0.0003488122,0.00014867398,0.01539989],"genre_scores_gemma":[0.97574735,0.0003424863,0.02162455,0.00006518463,0.00007265743,0.000060856295,0.00018391931,0.000030235424,0.0018727307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946946,0.0002816659,0.000025526027,0.00007728391,0.00010106752,0.000045117842],"domain_scores_gemma":[0.99337786,0.004831507,0.0006742903,0.00039957787,0.0004310746,0.00028572264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030750497,0.00065185165,0.00089630793,0.00081271806,0.00035932552,0.0019514656,0.0008482852,0.0007708862,0.003847351],"category_scores_gemma":[0.010260106,0.0004003917,0.0008515542,0.00047778597,0.0010827525,0.002328859,0.0012893043,0.0011642594,0.00017598974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063172716,0.000026351161,0.0016690152,0.00003013194,0.000055156688,0.000072679664,0.000050269322,0.9258572,0.00038762728,0.06838881,0.00028656764,0.003113026],"study_design_scores_gemma":[0.00001565339,0.000036112404,0.00026221236,0.000008122869,0.000010693351,0.000011312173,0.000030761053,0.9460681,0.0001853373,0.052686602,0.0006775378,0.0000075879084],"about_ca_topic_score_codex":0.0064509073,"about_ca_topic_score_gemma":0.004416357,"teacher_disagreement_score":0.0064509073,"about_ca_system_score_codex":0.0014544846,"about_ca_system_score_gemma":0.00094017904,"threshold_uncertainty_score":0.01626259},"labels":[],"label_agreement":null},{"id":"W2060234741","doi":"10.1111/j.1468-0084.2006.00442.x","title":"Factor Utilization and Adjusted Productivity Estimates for the UK*","year":2006,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Bank of Canada","funders":"","keywords":"Solow residual; Total factor productivity; Economics; Productivity; Residual; Econometrics; Capital (architecture); Variable (mathematics); Series (stratigraphy); Growth accounting; Labour economics; Macroeconomics; Mathematics","score_opus":0.08055077211038153,"score_gpt":0.232996251089557,"score_spread":0.15244547897917546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060234741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9030242,0.0023158712,0.033630725,0.00043182712,0.00015002057,0.00005324779,0.050054695,0.00047948523,0.009859997],"genre_scores_gemma":[0.9618259,0.00091819285,0.0050244466,0.00003455648,0.00003862377,0.000054872886,0.02617675,0.000079031575,0.005847543],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989524,0.00021923055,0.00014918536,0.00018761228,0.0003824492,0.00010907308],"domain_scores_gemma":[0.996585,0.0010476606,0.0008001971,0.0002774685,0.0012189453,0.00007065456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096629106,0.00038991187,0.00034478237,0.0028931526,0.00008738284,0.0009692352,0.0003382194,0.0002509972,0.0044964734],"category_scores_gemma":[0.009411722,0.00020923432,0.00060045056,0.0039690374,0.00015704554,0.00077884935,0.00062648434,0.00045911263,0.0014959915],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068056694,0.00009462384,0.49012935,0.00096958363,0.0010251881,0.0009510546,0.0014567511,0.22171909,0.003768979,0.023257272,0.028668772,0.22727872],"study_design_scores_gemma":[0.000060629973,0.00024357362,0.87396073,0.00021087301,0.00015969653,0.0004342111,0.0006773685,0.06260925,0.0032836483,0.006091801,0.05212282,0.00014542059],"about_ca_topic_score_codex":0.08264065,"about_ca_topic_score_gemma":0.032238916,"teacher_disagreement_score":0.08264065,"about_ca_system_score_codex":0.0014096206,"about_ca_system_score_gemma":0.00060468086,"threshold_uncertainty_score":0.16431928},"labels":[],"label_agreement":null},{"id":"W2063695712","doi":"10.1111/j.1468-0084.2006.00169.x","title":"A Cautionary Note on Estimating the Standard Error of the Gini Index of Inequality: Comment","year":2006,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Gini coefficient; Index (typography); Standard error; Inequality; Econometrics; Statistics; Construct (python library); Mathematics; Economics; Regression; Economic inequality; Computer science; Mathematical analysis","score_opus":0.04195286957875235,"score_gpt":0.2395469632030876,"score_spread":0.19759409362433525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063695712","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009890205,0.0012324369,0.003746247,0.97854054,0.013367653,0.000022960723,0.00045181272,0.00021126757,0.0014381431],"genre_scores_gemma":[0.020613553,0.0010559437,0.0070851133,0.9471239,0.020736624,0.00014608665,0.00012745429,0.00024285684,0.0028684984],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.94980174,0.018174088,0.0074052145,0.009013082,0.014125224,0.0014807067],"domain_scores_gemma":[0.70536864,0.21424489,0.014690165,0.012263905,0.050433688,0.002998724],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.056596097,0.0020746666,0.002241977,0.0024123508,0.005053528,0.0066737467,0.010713611,0.02684286,0.0064989193],"category_scores_gemma":[0.33155343,0.0012976483,0.0036599142,0.0037152166,0.01467225,0.01072378,0.0047077336,0.056107823,0.0061864695],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011005088,0.000031078715,0.0038250324,0.00030904915,0.00014065216,0.00042359947,0.0018917315,0.0005742506,0.0005923868,0.036497813,0.9445688,0.011035578],"study_design_scores_gemma":[0.00036820685,0.00025594098,0.027203199,0.0045354487,0.00040146077,0.0021856425,0.006985526,0.009540473,0.008731871,0.21323502,0.7252838,0.0012734898],"about_ca_topic_score_codex":0.065966405,"about_ca_topic_score_gemma":0.038735386,"teacher_disagreement_score":0.9434039,"about_ca_system_score_codex":0.0055866605,"about_ca_system_score_gemma":0.0052279364,"threshold_uncertainty_score":0.29931235},"labels":[],"label_agreement":null},{"id":"W2072648216","doi":"10.1111/j.1468-0084.2004.00087.x","title":"Calculating a Standard Error for the Gini Coefficient: Some Further Results: Reply","year":2004,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University; University of Northern British Columbia","funders":"","keywords":"Gini coefficient; Standard error; Statistics; Econometrics; Mathematics; Economics; Inequality; Mathematical analysis; Economic inequality","score_opus":0.049956176973980304,"score_gpt":0.2401808986229503,"score_spread":0.19022472164897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072648216","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00047493452,0.002430202,0.0031191409,0.97979754,0.012898966,0.000011824097,0.00034394485,0.000058079368,0.0008653995],"genre_scores_gemma":[0.024704663,0.0064562443,0.008258528,0.90475035,0.046962686,0.00017227071,0.00043872133,0.0004551494,0.00780138],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9934982,0.002584707,0.0009910325,0.0012796801,0.0013579644,0.0002884085],"domain_scores_gemma":[0.93161243,0.050383475,0.001626034,0.0033862805,0.012212713,0.0007791837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016663078,0.0014038667,0.001846538,0.0020223313,0.0021897284,0.0036507621,0.0037387754,0.017166609,0.00635589],"category_scores_gemma":[0.1422268,0.0009963068,0.002106565,0.0035639938,0.006475292,0.010507468,0.003482264,0.03222161,0.005788377],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000677462,0.00002970924,0.0012219376,0.0001898055,0.000063744264,0.00020693934,0.00061564794,0.0006660059,0.0002385822,0.0486702,0.93271685,0.01531281],"study_design_scores_gemma":[0.00021247038,0.00006717818,0.00820821,0.0012178194,0.00015091628,0.0010249865,0.0020178708,0.004252513,0.0018652851,0.37207803,0.6083943,0.00051031343],"about_ca_topic_score_codex":0.0207602,"about_ca_topic_score_gemma":0.00782384,"teacher_disagreement_score":0.0207602,"about_ca_system_score_codex":0.0044834786,"about_ca_system_score_gemma":0.0028533617,"threshold_uncertainty_score":0.0881238},"labels":[],"label_agreement":null},{"id":"W2075723759","doi":"10.1111/1468-0084.00164","title":"A Convenient Method of Computing the Gini Index and its Standard Error","year":2000,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":112,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Index (typography); Citation; Computer science; Standard error; Library science; Information retrieval; Econometrics; Statistics; World Wide Web; Mathematics","score_opus":0.02897922396198501,"score_gpt":0.3072517030175939,"score_spread":0.2782724790556089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075723759","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023570687,0.00066035334,0.99031067,0.00036859873,0.0005990436,0.000059208287,0.0006207677,0.0011075155,0.0039167223],"genre_scores_gemma":[0.062106997,0.0012501031,0.92404234,0.0003072826,0.00074225577,0.00032246872,0.0014572147,0.0018942556,0.007877016],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9944981,0.0020302108,0.00039233128,0.0011082081,0.0017340605,0.00023716482],"domain_scores_gemma":[0.9909189,0.003435816,0.00078170176,0.0024451732,0.0022490765,0.00016930801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0057036052,0.0015411151,0.0019546389,0.0051993597,0.0012475057,0.0027370139,0.0023857697,0.0013603573,0.008182467],"category_scores_gemma":[0.058516677,0.0006666782,0.0017548408,0.0065981993,0.0012529949,0.002571664,0.0025922528,0.005041354,0.005079413],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077171986,0.00009489384,0.006667612,0.0003514652,0.00038541752,0.00018627534,0.00078863,0.025483746,0.0052063484,0.536515,0.048889343,0.37535414],"study_design_scores_gemma":[0.00005726487,0.00015345246,0.018062877,0.00035667032,0.00020981929,0.0013742999,0.0004048181,0.16304602,0.012542911,0.65466756,0.14869452,0.00042980412],"about_ca_topic_score_codex":0.0063695037,"about_ca_topic_score_gemma":0.0058893347,"teacher_disagreement_score":0.008182467,"about_ca_system_score_codex":0.00088583614,"about_ca_system_score_gemma":0.0017056445,"threshold_uncertainty_score":0.030163884},"labels":[],"label_agreement":null},{"id":"W2096849708","doi":"10.1111/j.1468-0084.2006.00158.x","title":"A Recursive Thick Frontier Approach to Estimating Production Efficiency*","year":2006,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Inefficiency; Econometrics; Estimator; Production–possibility frontier; Frontier; Production (economics); Cointegration; Complement (music); Econometric model; Component (thermodynamics); Economics; Panel data; Ordinary least squares; Computer science; Mathematics; Statistics; Microeconomics","score_opus":0.0314248807181124,"score_gpt":0.2823778870325915,"score_spread":0.2509530063144791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096849708","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011599629,0.0002510551,0.985993,0.00011471712,0.000011057587,0.000027484153,0.0001276897,0.000055101857,0.0018201519],"genre_scores_gemma":[0.524414,0.00070390257,0.46938068,0.000120096556,0.000040361305,0.00031502577,0.0006583633,0.000074212585,0.004293271],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972013,0.0019803145,0.000097226985,0.0002621341,0.00033122793,0.00012782721],"domain_scores_gemma":[0.9905434,0.007471282,0.0006712493,0.0007059761,0.00052094524,0.00008707541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005408467,0.0006842542,0.0011175371,0.001684556,0.0003443673,0.0017386707,0.0011228498,0.0010076415,0.0046915696],"category_scores_gemma":[0.01717303,0.00041833683,0.0010061916,0.0017631482,0.0007321314,0.0020842499,0.0010810811,0.0014250808,0.00051777146],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042459782,0.00006204177,0.0016593218,0.00010511424,0.00012574697,0.00007548665,0.00007914774,0.78719884,0.0011316234,0.15188211,0.0010666142,0.05657151],"study_design_scores_gemma":[0.0000073165543,0.000031575622,0.0006445732,0.0000214057,0.000013298265,0.000017054952,0.000017242188,0.94363123,0.0004949057,0.053652808,0.0014547723,0.000013765666],"about_ca_topic_score_codex":0.0044035963,"about_ca_topic_score_gemma":0.0030137012,"teacher_disagreement_score":0.005408467,"about_ca_system_score_codex":0.00095931854,"about_ca_system_score_gemma":0.0009773336,"threshold_uncertainty_score":0.028603017},"labels":[],"label_agreement":null},{"id":"W2097494622","doi":"10.1046/j.0305-9049.2003.00085.x","title":"Exact Skewness–Kurtosis Tests for Multivariate Normality and Goodness‐of‐Fit in Multivariate Regressions with Application to Asset Pricing Models*","year":2003,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Social Sciences and Humanities Research Council of Canada; Canada Council for the Arts; Université de Montréal; Mitacs; Killam Trusts; Technische Universität Dresden","keywords":"Kurtosis; Multivariate statistics; Mathematics; Multivariate normal distribution; Econometrics; Statistics; Skewness; Nuisance parameter; Normal-Wishart distribution","score_opus":0.045525615855575526,"score_gpt":0.2636412218626133,"score_spread":0.21811560600703778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097494622","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19055004,0.0006666479,0.805175,0.0005822963,0.000074459254,0.00007446628,0.00023483411,0.00061629986,0.0020258403],"genre_scores_gemma":[0.93747765,0.00021945387,0.061079867,0.00009075465,0.00012383085,0.00017013156,0.00029327133,0.00013681385,0.0004082482],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9690392,0.024104444,0.0011047133,0.001575662,0.003532144,0.00064392603],"domain_scores_gemma":[0.5980081,0.36281693,0.01335968,0.016246198,0.0080838865,0.0014852649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.038298905,0.0012482111,0.0022066685,0.004759738,0.0007729962,0.002636621,0.0022412199,0.0020336215,0.0034339253],"category_scores_gemma":[0.2985599,0.0007947402,0.0015984259,0.0036451467,0.005474283,0.005911999,0.00332921,0.0025575259,0.0005516415],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00097005203,0.00038017682,0.084496595,0.0003815838,0.0012318575,0.0009989729,0.0006479873,0.569608,0.0024133509,0.19099846,0.0035623924,0.14431065],"study_design_scores_gemma":[0.00007431027,0.00019238422,0.010190114,0.00007328312,0.000042855914,0.00028211332,0.00013271693,0.85680914,0.0009429582,0.13073474,0.00044607598,0.00007927113],"about_ca_topic_score_codex":0.0015539253,"about_ca_topic_score_gemma":0.001020388,"teacher_disagreement_score":0.038298905,"about_ca_system_score_codex":0.0010127877,"about_ca_system_score_gemma":0.0015948367,"threshold_uncertainty_score":0.20254642},"labels":[],"label_agreement":null},{"id":"W2103573427","doi":"10.1111/j.1468-0084.2006.00153.x","title":"Consumption and Aggregate Constraints: International Evidence*","year":2006,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Openness to experience; Consumption (sociology); Economics; Aggregate (composite); Aggregate data; Sensitivity (control systems); Politics; Phenomenon; Econometrics; Monetary economics; Economy; Political science; Statistics; Psychology","score_opus":0.028402497469561885,"score_gpt":0.217768163653677,"score_spread":0.1893656661841151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103573427","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9566342,0.01266506,0.0007314479,0.0013363886,0.00003073009,0.000014008718,0.005877105,0.000022756183,0.022688357],"genre_scores_gemma":[0.99350584,0.003241825,0.000115451294,0.00013240901,0.000058318135,0.0000051709267,0.0024361906,0.000008664308,0.00049610966],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993156,0.00018263818,0.00007615075,0.00021924588,0.00012555256,0.00008077251],"domain_scores_gemma":[0.98300457,0.0052377023,0.008193992,0.0019860878,0.0010654253,0.0005121939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013858461,0.0003021245,0.00064133876,0.002286642,0.0002988475,0.0019339252,0.0004382112,0.0005316143,0.0076062838],"category_scores_gemma":[0.0063140774,0.00030243836,0.000441033,0.008170874,0.0010746082,0.0009109141,0.0012917393,0.0006832946,0.00077948236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005941638,0.00008876436,0.969773,0.0003484734,0.0009687102,0.00016459728,0.00050966284,0.0017982527,0.00027535667,0.0024769544,0.001925579,0.021076525],"study_design_scores_gemma":[0.000010114511,0.00003742289,0.9932706,0.00011591009,0.00015459271,0.00014900292,0.00027472014,0.00034072826,0.00020133943,0.00076576904,0.0046652555,0.000014613439],"about_ca_topic_score_codex":0.014078465,"about_ca_topic_score_gemma":0.010180791,"teacher_disagreement_score":0.014078465,"about_ca_system_score_codex":0.000538222,"about_ca_system_score_gemma":0.0002065662,"threshold_uncertainty_score":0.027993023},"labels":[],"label_agreement":null},{"id":"W2112007189","doi":"10.1111/j.1468-0084.2005.00122.x","title":"Globalization vs. Europeanization: A Business Cycles Race*","year":2005,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Global Financial Crisis and Policies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Business cycle; Race (biology); Club; Globalization; Emerging markets; Economics; Power (physics); Synchronization (alternating current); Economic geography; International economics; Monetary economics; Economy; Macroeconomics; Market economy; Sociology; Engineering; Channel (broadcasting)","score_opus":0.014176173729087421,"score_gpt":0.20475131772138835,"score_spread":0.19057514399230094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112007189","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98031116,0.00066039583,0.00034891733,0.00084976625,0.000011474552,0.000005253393,0.000069277194,0.000004261665,0.017739428],"genre_scores_gemma":[0.999574,0.000098116805,0.000040607418,0.00004524019,0.000014807236,0.0000012286234,0.000023934992,0.0000017273012,0.00020025623],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995204,0.00021055169,0.000023138202,0.00007282761,0.000069836606,0.000103296596],"domain_scores_gemma":[0.99582565,0.0019393512,0.0012747829,0.00019495455,0.00038424012,0.00038110669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001633295,0.00011599597,0.00042323003,0.001117519,0.00041999988,0.0021047725,0.00015958505,0.0002960353,0.005847759],"category_scores_gemma":[0.0035032239,0.00006421554,0.00022871941,0.0020224527,0.0017290012,0.0015149523,0.0016019904,0.0004759598,0.0002047631],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016196131,0.00011105951,0.8155691,0.000186014,0.00019254569,0.00037131537,0.006532752,0.0021050156,0.004101623,0.09566783,0.001701984,0.07184112],"study_design_scores_gemma":[0.000027695423,0.0001665206,0.95581174,0.000107103915,0.00008711365,0.0001612905,0.008697553,0.0018331746,0.0009251943,0.025598234,0.0065667164,0.000017743234],"about_ca_topic_score_codex":0.000826151,"about_ca_topic_score_gemma":0.0009176216,"teacher_disagreement_score":0.005847759,"about_ca_system_score_codex":0.0004619296,"about_ca_system_score_gemma":0.0002917837,"threshold_uncertainty_score":0.019562662},"labels":[],"label_agreement":null},{"id":"W2140117372","doi":"10.1111/1468-0084.t01-1-00227","title":"Child Growth in the Time of Drought","year":2001,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":496,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Economics; Demographic economics; Slowdown; Panel data; Economic growth; Econometrics","score_opus":0.007019001405057616,"score_gpt":0.1783094445797148,"score_spread":0.17129044317465716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140117372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99576783,0.0005955483,0.000072648356,0.0008353844,0.000013017992,0.000003219562,0.0011434397,0.0000050932827,0.0015637301],"genre_scores_gemma":[0.9988558,0.0003245871,0.000026981876,0.000038347036,0.000011158688,0.0000029721148,0.00046859912,0.0000015590057,0.0002699257],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996306,0.00007581412,0.000016229029,0.00003989397,0.000050916085,0.0001865898],"domain_scores_gemma":[0.99852246,0.0002636163,0.00075016264,0.000058075224,0.00015272912,0.00025298956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067327364,0.000174864,0.00026212083,0.0008959451,0.0005355822,0.0011165831,0.00025057181,0.0005350877,0.0018935999],"category_scores_gemma":[0.0046961918,0.00015792462,0.0002269544,0.0015807247,0.0005107253,0.000771958,0.0011856689,0.000893203,0.00026674403],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016247948,0.000033944318,0.9868913,0.00003464155,0.000055681394,0.00041946393,0.0020245318,0.00078265875,0.00023399813,0.000835654,0.00094061386,0.0075850473],"study_design_scores_gemma":[0.0000020448604,0.000025546658,0.9973738,0.000012673376,0.000007663303,0.00008165074,0.0010421769,0.00019480976,0.000041884192,0.00016596654,0.0010485798,0.0000032532994],"about_ca_topic_score_codex":0.051161256,"about_ca_topic_score_gemma":0.071349084,"teacher_disagreement_score":0.051161256,"about_ca_system_score_codex":0.0010711694,"about_ca_system_score_gemma":0.0004708677,"threshold_uncertainty_score":0.10172695},"labels":[],"label_agreement":null},{"id":"W2171283734","doi":"10.1111/j.1468-0084.2011.00664.x","title":"Does Ethnic Discrimination Vary Across Minority Groups? Evidence from a Field Experiment*","year":2011,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Names, Identity, and Discrimination Research","field":"Social Sciences","cited_by":316,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Ethnic group; Indigenous; Quarter (Canadian coin); Callback; Scale (ratio); Demography; Population; Demographic economics; Geography; Ethnic discrimination; Political science; Sociology; Economics; Law","score_opus":0.09437534557655264,"score_gpt":0.3580702402982448,"score_spread":0.26369489472169216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171283734","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939427,0.000088072615,0.0005734595,0.00024606037,0.000044427656,0.00025268784,0.0000931094,0.000005553592,0.0047539673],"genre_scores_gemma":[0.9955041,0.00008587969,0.0011480695,0.00072458683,0.000038461032,0.00052615517,0.00015628723,0.0000066987827,0.0018099345],"study_design_codex":"observational","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.97959006,0.015518208,0.0006941535,0.0019251979,0.0017404504,0.0005319544],"domain_scores_gemma":[0.8318529,0.12123841,0.02259114,0.01596463,0.0050687944,0.003283999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.030927753,0.00046407696,0.000735118,0.00055735337,0.0016925635,0.001578437,0.0013318063,0.0015411576,0.006169533],"category_scores_gemma":[0.045392953,0.0005338984,0.0004851713,0.0004981454,0.0033630307,0.0014424255,0.0014561518,0.0012940352,0.0009245899],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.05108468,0.12655474,0.60897774,0.001732354,0.0014146001,0.0010026293,0.04873329,0.00085827085,0.04553284,0.011184561,0.007288897,0.095635384],"study_design_scores_gemma":[0.0047967294,0.048909925,0.8895422,0.0004701017,0.00062753377,0.00056482776,0.020467386,0.002597556,0.010836185,0.0072483593,0.013716778,0.00022240747],"about_ca_topic_score_codex":0.003805192,"about_ca_topic_score_gemma":0.00410146,"teacher_disagreement_score":0.030927753,"about_ca_system_score_codex":0.00055042375,"about_ca_system_score_gemma":0.0005760913,"threshold_uncertainty_score":0.16356349},"labels":[],"label_agreement":null},{"id":"W2259411487","doi":"10.1111/obes.12015","title":"Density Nowcasts and Model Combination: Nowcasting Euro‐Area GDP Growth over the 2008–09 Recession*","year":2013,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Recession; Econometrics; Quarter (Canadian coin); Aggregate (composite); Real gross domestic product; Economics; Receipt; Dynamic factor; Macroeconomics; Meteorology; Geography","score_opus":0.04360909450057632,"score_gpt":0.20727361110387685,"score_spread":0.16366451660330053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2259411487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7540594,0.0019663514,0.21348514,0.004458364,0.0013425614,0.00018170809,0.009671127,0.0031474961,0.011687995],"genre_scores_gemma":[0.97574246,0.00030698394,0.016814196,0.00012865521,0.00025903108,0.00004766303,0.005014464,0.00021967165,0.0014669148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99837804,0.00093809096,0.00008324569,0.0002740944,0.0002245198,0.00010211866],"domain_scores_gemma":[0.98790354,0.007992667,0.00091064407,0.0014124016,0.001445771,0.0003348542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006124537,0.0010132915,0.0012167941,0.0016927152,0.00048909103,0.0025607892,0.001365576,0.0015363649,0.002794278],"category_scores_gemma":[0.027281247,0.0009467166,0.0012047103,0.001783465,0.00052560813,0.0019779077,0.0015992695,0.003620187,0.0005550507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050686684,0.00007489318,0.033455703,0.00011347672,0.00051583815,0.00014012719,0.00019941994,0.9139956,0.00055219105,0.0066135586,0.0071559045,0.03667642],"study_design_scores_gemma":[0.00006179364,0.00006083713,0.014400195,0.000052524967,0.00013170754,0.000043049153,0.00011573409,0.97530603,0.0006834172,0.005606129,0.003467648,0.00007099657],"about_ca_topic_score_codex":0.045947332,"about_ca_topic_score_gemma":0.031570774,"teacher_disagreement_score":0.045947332,"about_ca_system_score_codex":0.0008966317,"about_ca_system_score_gemma":0.0009159261,"threshold_uncertainty_score":0.091359794},"labels":[],"label_agreement":null},{"id":"W2580086330","doi":"10.1111/obes.12259","title":"Olley and Pakes‐style Production Function Estimators with Firm Fixed Effects","year":2018,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Estimator; Function (biology); Production (economics); Econometrics; Productivity; Control (management); Mathematics; Statistics; Economics; Biology; Microeconomics","score_opus":0.010519843919798346,"score_gpt":0.1832138525073364,"score_spread":0.17269400858753806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2580086330","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09066239,0.0017207531,0.89728713,0.0013397278,0.00016258867,0.00023780238,0.0009909024,0.00039409098,0.0072047077],"genre_scores_gemma":[0.87035745,0.0011209622,0.11973096,0.0004497148,0.0002497222,0.0005112447,0.0017558468,0.000105424275,0.005718603],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9914608,0.005536007,0.00042014106,0.0010618299,0.001184859,0.00033633073],"domain_scores_gemma":[0.897679,0.077586494,0.009669526,0.011139941,0.003506704,0.00041835775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017603235,0.0008945909,0.0014260318,0.002796099,0.00058091886,0.002344082,0.0018608024,0.0013033907,0.0055171223],"category_scores_gemma":[0.10484287,0.00047550473,0.0011888389,0.0032308963,0.00217552,0.003669403,0.0017321414,0.0022467352,0.001004345],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023042459,0.00023445985,0.070613235,0.0006286315,0.00094003766,0.0003645414,0.0008788409,0.13025135,0.0009855123,0.55097526,0.01431394,0.2295838],"study_design_scores_gemma":[0.00027995097,0.00035532526,0.03758953,0.0003060714,0.00041075025,0.00024514404,0.00043097665,0.44045848,0.0041266372,0.491398,0.02424019,0.00015900338],"about_ca_topic_score_codex":0.005966983,"about_ca_topic_score_gemma":0.003038319,"teacher_disagreement_score":0.017603235,"about_ca_system_score_codex":0.0011820591,"about_ca_system_score_gemma":0.001474633,"threshold_uncertainty_score":0.0930959},"labels":[],"label_agreement":null},{"id":"W2591451634","doi":"10.1111/obes.12162","title":"The Macroeconomic Effects of Shocks to Large Banks’ Capital","year":2017,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Université du Québec à Montréal","funders":"","keywords":"Leverage (statistics); Economics; Monetary economics; Macro; Shock (circulatory); Capital (architecture); Monetary policy; Capital requirement; Macroeconomic model; Econometrics; Macroeconomics; Microeconomics; Computer science","score_opus":0.0091562986799562,"score_gpt":0.21462588522830295,"score_spread":0.20546958654834674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2591451634","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98306686,0.00040368258,0.009001246,0.0021319392,0.00006084286,0.000019011073,0.00085041556,0.00014343341,0.0043225987],"genre_scores_gemma":[0.9994968,0.000055265235,0.000070354494,0.000056835983,0.000013507521,0.0000020223993,0.00007467231,0.0000032259868,0.00022727957],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995839,0.00010951446,0.000030976644,0.00009323829,0.000058632846,0.00012370032],"domain_scores_gemma":[0.9967301,0.0012546948,0.0012924656,0.00020575129,0.00026961288,0.0002473333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009619751,0.00041249426,0.00047856997,0.0005836861,0.00027451958,0.0025012626,0.0004399182,0.0011630583,0.0028345801],"category_scores_gemma":[0.007039829,0.00038631965,0.00034455824,0.0006846025,0.0007650068,0.0013273623,0.0011749001,0.0015429365,0.00026213782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007764198,0.00044509486,0.32052946,0.000110840105,0.0004551197,0.0011654665,0.00039793982,0.56478405,0.016074827,0.072262734,0.005939499,0.017058484],"study_design_scores_gemma":[0.00008254774,0.0003170344,0.43067133,0.00006289971,0.00016842067,0.00021137169,0.00066258834,0.47701043,0.005716999,0.082885005,0.0020966479,0.00011480135],"about_ca_topic_score_codex":0.006735011,"about_ca_topic_score_gemma":0.0035709941,"teacher_disagreement_score":0.006735011,"about_ca_system_score_codex":0.0012398497,"about_ca_system_score_gemma":0.00040451234,"threshold_uncertainty_score":0.013391614},"labels":[],"label_agreement":null},{"id":"W2619453511","doi":"10.1111/obes.12323","title":"Economic Policy Uncertainty Spillovers in Booms and Busts","year":2019,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":144,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Australian Research Council","keywords":"Economics; Spillover effect; Unemployment; Boom; Recession; Counterfactual thinking; Unemployment rate; Monetary economics; Macroeconomics; Econometrics","score_opus":0.00903693324618125,"score_gpt":0.20498813471743682,"score_spread":0.19595120147125558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619453511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99038285,0.00032532972,0.0030526263,0.0005917763,0.000033647742,0.000017313288,0.0009840174,0.00008253645,0.004529842],"genre_scores_gemma":[0.99902964,0.000084307096,0.00012979038,0.00002244238,0.0000068553118,0.000002120141,0.000268925,0.0000039429037,0.0004519258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996147,0.000059105638,0.000014679396,0.00007386528,0.00007815043,0.00015942079],"domain_scores_gemma":[0.9985586,0.00063401606,0.00038494202,0.000058075446,0.00020817699,0.00015613402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010473786,0.00034085722,0.00053227774,0.0006899501,0.00057780114,0.001859894,0.00032135504,0.00061842747,0.0035924027],"category_scores_gemma":[0.005398506,0.00027221665,0.00056907634,0.0006606146,0.0006744514,0.0007026571,0.00079955085,0.0013097442,0.00015711399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011600335,0.00017582554,0.37097305,0.00014457692,0.00055931194,0.00069160847,0.00060930016,0.5690447,0.0037461848,0.029803965,0.00454451,0.018546931],"study_design_scores_gemma":[0.000052006704,0.0001313253,0.43222347,0.00006295843,0.0001610281,0.000071977214,0.00076752563,0.5529744,0.001310675,0.008498733,0.0036477603,0.0000981779],"about_ca_topic_score_codex":0.4386404,"about_ca_topic_score_gemma":0.2662115,"teacher_disagreement_score":0.4386404,"about_ca_system_score_codex":0.0029039653,"about_ca_system_score_gemma":0.0017216637,"threshold_uncertainty_score":0.87217444},"labels":[],"label_agreement":null},{"id":"W2621295890","doi":"10.1111/obes.12175","title":"Is the Quarter of Birth Endogenous? New Evidence from Taiwan, the US, and Indonesia","year":2017,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Instrumental variable; Demography; Odds; Earnings; Census; Population; Sample (material); Demographic economics; Economics; Geography; Medicine; Logistic regression; Econometrics; Sociology","score_opus":0.038157863297274636,"score_gpt":0.2590234351663031,"score_spread":0.22086557186902847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621295890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99015325,0.0032188436,0.00059036876,0.0015386419,0.000066763154,0.000013785308,0.0009672527,0.0000066827142,0.0034444279],"genre_scores_gemma":[0.99819946,0.0006341589,0.00007816298,0.00021427394,0.000031804175,0.000005901928,0.00047217341,0.0000051559773,0.00035889007],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981832,0.0008825891,0.0001557283,0.00031039963,0.00019877231,0.00026930362],"domain_scores_gemma":[0.9688219,0.016579416,0.00903852,0.0026182358,0.0013796765,0.0015622755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004488583,0.00020243824,0.00062940636,0.0011117333,0.00063664396,0.0016606261,0.0009556959,0.0005199611,0.0042966045],"category_scores_gemma":[0.014040221,0.0002167932,0.0009079942,0.0024476093,0.0009995197,0.0006414956,0.0014238817,0.0011824161,0.0003417921],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001977388,0.000051613657,0.99154156,0.000057775564,0.00039156838,0.00032755316,0.00074307545,0.0001593597,0.0000703542,0.0006765456,0.00067380077,0.0051090973],"study_design_scores_gemma":[0.000017828052,0.000045577573,0.9924971,0.000115093666,0.00045330854,0.00010829232,0.0029905885,0.00095601403,0.00015012275,0.00056944834,0.0020826228,0.00001401442],"about_ca_topic_score_codex":0.053602282,"about_ca_topic_score_gemma":0.037384946,"teacher_disagreement_score":0.053602282,"about_ca_system_score_codex":0.00063551794,"about_ca_system_score_gemma":0.0007461641,"threshold_uncertainty_score":0.106580555},"labels":[],"label_agreement":null},{"id":"W2899503691","doi":"10.1111/obes.12271","title":"The migration response to local labour market shocks: Evidence from EU regions during the global economic crisis","year":2018,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Unemployment; Economics; Context (archaeology); Estimation; Economic geography; Demographic economics; Geography; Macroeconomics","score_opus":0.015986053194336134,"score_gpt":0.22130917333273406,"score_spread":0.20532312013839793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899503691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984036,0.00028461835,0.00004886318,0.0001502393,0.0000050553863,0.0000036927454,0.00041974307,0.000001657195,0.0006826282],"genre_scores_gemma":[0.9991234,0.00018019223,0.000025844412,0.000044526372,0.000006259605,0.0000039611505,0.000466796,0.0000020545474,0.00014701238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99937564,0.0002582158,0.000056943238,0.00010981991,0.000057493828,0.00014189718],"domain_scores_gemma":[0.9972,0.0006083695,0.001320922,0.00022116207,0.00041644328,0.00023307011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013125133,0.00021858026,0.00037669248,0.0009721877,0.00041736354,0.0010614162,0.0003985074,0.00054145884,0.0016067643],"category_scores_gemma":[0.003470366,0.00012709199,0.00030361535,0.0023501809,0.000635846,0.00057836535,0.0016924813,0.00048785828,0.00033512706],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006094467,0.00009357665,0.98160326,0.00014423169,0.00017551413,0.00045442313,0.005137575,0.001041213,0.00048015924,0.00045387566,0.0012794469,0.008527262],"study_design_scores_gemma":[0.0000071040954,0.000046085468,0.9926403,0.00004290664,0.000023774111,0.00005827272,0.0060593984,0.00014245597,0.00009296133,0.000058255217,0.0008216231,0.0000068289714],"about_ca_topic_score_codex":0.024365354,"about_ca_topic_score_gemma":0.023419268,"teacher_disagreement_score":0.024365354,"about_ca_system_score_codex":0.00037424508,"about_ca_system_score_gemma":0.00026355774,"threshold_uncertainty_score":0.048447073},"labels":[],"label_agreement":null},{"id":"W2909615567","doi":"10.1111/obes.12292","title":"Heterogeneous Treatment Under Regression Discontinuity Design: Application to Female High School Enrolment","year":2019,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Regression discontinuity design; Islam; Demographic economics; Adversary; Educational attainment; Econometrics; Demography; Political science; Economics; Statistics; Sociology; Geography; Economic growth; Mathematics","score_opus":0.03057829746420822,"score_gpt":0.30074015066763515,"score_spread":0.27016185320342695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909615567","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25210324,0.0019524021,0.72819877,0.0029866192,0.0010068745,0.0042579887,0.0025708436,0.0012009293,0.005722362],"genre_scores_gemma":[0.8652479,0.0003491905,0.11850218,0.00077294925,0.0003444543,0.0060358476,0.0011236337,0.00012941021,0.007494407],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.885378,0.10194924,0.0017344009,0.0055198316,0.0025988885,0.0028195984],"domain_scores_gemma":[0.8313286,0.1341615,0.013112964,0.016025418,0.004043909,0.0013276865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.088022545,0.0014568127,0.0050528497,0.002999786,0.0023092919,0.0029699113,0.008474042,0.0058206078,0.02214025],"category_scores_gemma":[0.16913532,0.0009264669,0.0053535677,0.0036726817,0.003746218,0.002088485,0.0042717275,0.0065310546,0.0013917119],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01474132,0.0054396363,0.22827923,0.0027687326,0.010440717,0.0038848126,0.0053078076,0.13516626,0.0021034079,0.3765279,0.0158822,0.19945797],"study_design_scores_gemma":[0.0032077993,0.0043555023,0.053157963,0.0005135799,0.0025597794,0.00038534967,0.0022517252,0.75640863,0.0027088532,0.1615406,0.012601147,0.00030914205],"about_ca_topic_score_codex":0.009380428,"about_ca_topic_score_gemma":0.0034739543,"teacher_disagreement_score":0.088022545,"about_ca_system_score_codex":0.0028683995,"about_ca_system_score_gemma":0.0019709424,"threshold_uncertainty_score":0.4655133},"labels":[],"label_agreement":null},{"id":"W2912622056","doi":"10.1111/obes.12300","title":"Markov Switching Oil Price Uncertainty","year":2019,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Economics; Bivariate analysis; Oil price; Econometrics; Markov chain; Aggregate (composite); Order (exchange); Monetary economics; Statistics; Mathematics","score_opus":0.010686608854423189,"score_gpt":0.19428701357891193,"score_spread":0.18360040472448874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912622056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9594604,0.00013966733,0.032312945,0.0010874477,0.000039113875,0.00001968351,0.00030038328,0.00006730063,0.0065731457],"genre_scores_gemma":[0.9989059,0.000043083557,0.00039979155,0.000040107163,0.00001940708,0.00000448917,0.000060531707,0.000003255399,0.0005233632],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901676,0.00032116554,0.000042534757,0.00022790863,0.00019679805,0.00019492663],"domain_scores_gemma":[0.9878479,0.007977216,0.0026150972,0.00067197985,0.00057942106,0.00030833745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022472464,0.0002714627,0.0008422132,0.0005099273,0.0002419328,0.0010774246,0.00050086837,0.0008400617,0.0046950663],"category_scores_gemma":[0.01925005,0.00023975133,0.00050434674,0.00049632374,0.00079045136,0.0012624069,0.0006501718,0.001229978,0.00027394542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011320299,0.00034524783,0.17392948,0.00015939659,0.0004997981,0.0009279583,0.0006078115,0.49141154,0.008374175,0.27547982,0.004596345,0.042536415],"study_design_scores_gemma":[0.00005308214,0.000115498195,0.03920564,0.000016992028,0.000067693705,0.00010121899,0.0001628826,0.83260727,0.0013184863,0.12556945,0.0007369118,0.000044912013],"about_ca_topic_score_codex":0.0039764545,"about_ca_topic_score_gemma":0.0019385002,"teacher_disagreement_score":0.0046950663,"about_ca_system_score_codex":0.0007213817,"about_ca_system_score_gemma":0.00040800852,"threshold_uncertainty_score":0.01570654},"labels":[],"label_agreement":null},{"id":"W2918011399","doi":"10.1111/j.1468-0084.2004.00082.x","title":"On Business Cycle Asymmetries in G7 Countries","year":2004,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Business cycle; Business; Economics; Keynesian economics","score_opus":0.023598705160002304,"score_gpt":0.2007392111473681,"score_spread":0.17714050598736578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2918011399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974963,0.00010531801,0.0006332042,0.00007737564,0.0000016087804,0.000006951711,0.00018604002,0.000010022184,0.001483043],"genre_scores_gemma":[0.9995389,0.000038392664,0.00012732633,0.000014048562,0.000003412632,0.0000024784583,0.00022738062,0.000002314811,0.00004577723],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986576,0.0004868221,0.00010533187,0.00020433824,0.00023850292,0.0003074697],"domain_scores_gemma":[0.9791669,0.009793807,0.0072149946,0.0015348519,0.0018093359,0.0004801939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031255896,0.00025732274,0.0009428423,0.002150151,0.00040678924,0.0018151298,0.0004534789,0.0006285156,0.0022932682],"category_scores_gemma":[0.013918077,0.00017055357,0.0007210445,0.0023295004,0.0009898957,0.0011492443,0.0013861338,0.00070922653,0.00018406974],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052554783,0.00006923513,0.9190598,0.00008350626,0.0006201284,0.00063778774,0.0010285929,0.028067093,0.0021169237,0.023570472,0.00089772936,0.023323195],"study_design_scores_gemma":[0.000072035495,0.00023570476,0.8975521,0.00008900899,0.00037707546,0.00030288709,0.0015862514,0.077484466,0.0022573867,0.017758891,0.0022029842,0.00008129674],"about_ca_topic_score_codex":0.011598603,"about_ca_topic_score_gemma":0.006678218,"teacher_disagreement_score":0.011598603,"about_ca_system_score_codex":0.0010617069,"about_ca_system_score_gemma":0.000611539,"threshold_uncertainty_score":0.02306223},"labels":[],"label_agreement":null},{"id":"W2964128792","doi":"10.1111/obes.12327","title":"Time‐Varying Relationship between Inflation and Inflation Uncertainty","year":2019,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; Inflation (cosmology); Econometrics; Volatility (finance); Stochastic volatility; Physics","score_opus":0.04653366211138501,"score_gpt":0.22311249571466057,"score_spread":0.17657883360327556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964128792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890324,0.0006236977,0.0075258976,0.00048228548,0.000020850624,0.000006791353,0.00040725063,0.000038446295,0.0018623522],"genre_scores_gemma":[0.99935025,0.00006579799,0.00018626371,0.000011378534,0.000009237872,0.0000015008989,0.00015276622,0.0000025914912,0.00022016744],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988274,0.00030467636,0.00010836068,0.0003149825,0.00029298262,0.00015159826],"domain_scores_gemma":[0.984339,0.008613916,0.005090787,0.0005931603,0.0009942001,0.00036890307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018240849,0.0001293656,0.00038397824,0.0006633018,0.00020421423,0.0012248125,0.00041357425,0.00082077057,0.0019050846],"category_scores_gemma":[0.017712789,0.00022670052,0.00039249557,0.0014120478,0.0005059313,0.00089387054,0.00058813463,0.0013840505,0.00027820384],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026910705,0.00004949766,0.9348833,0.000074070675,0.0003079243,0.00046678315,0.00043636296,0.030812884,0.0020107508,0.012721032,0.0006125123,0.017355843],"study_design_scores_gemma":[0.000010374799,0.00008806074,0.9124529,0.000025946287,0.00009330581,0.0002694427,0.0002524712,0.07713291,0.0009624191,0.0070561585,0.001612279,0.000043797456],"about_ca_topic_score_codex":0.0069333436,"about_ca_topic_score_gemma":0.0040618945,"teacher_disagreement_score":0.0069333436,"about_ca_system_score_codex":0.0005282487,"about_ca_system_score_gemma":0.00027810043,"threshold_uncertainty_score":0.013785958},"labels":[],"label_agreement":null},{"id":"W2987234290","doi":"10.1111/obes.12350","title":"Job Reallocation Dynamics in India: Evidence from Large Manufacturing Plants","year":2019,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Workforce; Job creation; Labour economics; Economics; Demographic economics; Business; Economic growth","score_opus":0.015152642025164443,"score_gpt":0.21213870508643762,"score_spread":0.19698606306127317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2987234290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970433,0.00013673789,0.00013012726,0.00014265689,0.000004455174,0.000006516578,0.0006417378,0.000008821657,0.0018856731],"genre_scores_gemma":[0.99922025,0.000084991756,0.00003549453,0.000021213458,0.000006320621,0.0000035313572,0.00029119465,0.0000020117363,0.00033498692],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999383,0.00014014651,0.000033180433,0.000100141006,0.00012960285,0.00021389591],"domain_scores_gemma":[0.9942027,0.001997347,0.0023596168,0.0003790145,0.0005957943,0.00046556376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005761755,0.0001681601,0.0002609337,0.0020732267,0.0007697934,0.0012191063,0.0006178702,0.00035620795,0.0037519631],"category_scores_gemma":[0.0022989418,0.00017829,0.0002756376,0.004029126,0.0005876037,0.000431461,0.0012782223,0.00071080646,0.0007590725],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002523711,0.00022878371,0.975021,0.0001521623,0.000073210336,0.0004720582,0.004695477,0.0016286038,0.0006815092,0.00081107276,0.0017017903,0.014281913],"study_design_scores_gemma":[0.0000033907336,0.000054325923,0.9935929,0.000022020777,0.00001422829,0.00008555524,0.004722456,0.0003546234,0.00014272805,0.00010120674,0.00089764944,0.000008859571],"about_ca_topic_score_codex":0.03825519,"about_ca_topic_score_gemma":0.045804325,"teacher_disagreement_score":0.03825519,"about_ca_system_score_codex":0.00095213234,"about_ca_system_score_gemma":0.0007874626,"threshold_uncertainty_score":0.076065004},"labels":[],"label_agreement":null},{"id":"W3021446320","doi":"10.1111/obes.12371","title":"A Simple Estimator of  Two‐Dimensional Copulas, with Applications1","year":2020,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Russian Science Foundation","keywords":"Copula (linguistics); Estimator; Mathematics; Bivariate analysis; Applied mathematics; Parametric statistics; Mathematical optimization; Piecewise; Regular polygon; Econometrics; Mathematical analysis; Statistics; Geometry","score_opus":0.027392840956939977,"score_gpt":0.22043747905085753,"score_spread":0.19304463809391756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021446320","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008297836,0.00021903822,0.990717,0.0001177575,0.000028026225,0.000028690354,0.000031021995,0.000071391056,0.0004891689],"genre_scores_gemma":[0.31542346,0.0006752228,0.68173444,0.00010021582,0.00014125957,0.0002186513,0.00018349304,0.000091396454,0.0014317721],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978161,0.0015263992,0.0000813262,0.00020942593,0.0002986278,0.00006805363],"domain_scores_gemma":[0.98433614,0.011797132,0.0007586642,0.0018511616,0.0010518009,0.00020515517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060921866,0.00076563004,0.0009710644,0.0013956717,0.00042570662,0.001190787,0.0012499129,0.0012477,0.0021513791],"category_scores_gemma":[0.030754121,0.000653472,0.0010491132,0.0019440869,0.0011409156,0.0011020078,0.0018522207,0.0019536891,0.00042154698],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016352943,0.00020715722,0.008097917,0.00024916482,0.00021748933,0.00039743207,0.00020997357,0.55246836,0.005818011,0.23045152,0.0032267626,0.19849274],"study_design_scores_gemma":[0.00002633138,0.00006108297,0.0014547278,0.00002329954,0.000016633716,0.00010041035,0.000022923072,0.95819277,0.0010483259,0.037370346,0.0016576969,0.000025402702],"about_ca_topic_score_codex":0.0024136845,"about_ca_topic_score_gemma":0.0017590633,"teacher_disagreement_score":0.0060921866,"about_ca_system_score_codex":0.0005578843,"about_ca_system_score_gemma":0.00077130424,"threshold_uncertainty_score":0.032218993},"labels":[],"label_agreement":null},{"id":"W3033451938","doi":"10.1111/obes.12438","title":"International Effects of Euro Area Forward Guidance","year":2020,"lang":"en","type":"preprint","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; Balsillie School of International Affairs","funders":"","keywords":"Interest rate; Economics; Shock (circulatory); Equity (law); Monetary policy; Monetary economics; Inflation (cosmology); International economics; Political science","score_opus":0.0438837896239402,"score_gpt":0.22367881475185455,"score_spread":0.17979502512791434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033451938","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38256484,0.031566016,0.0011835506,0.027223185,0.0052055693,0.000049591636,0.024672654,0.00055422564,0.52698034],"genre_scores_gemma":[0.9141967,0.009246862,0.00045091464,0.0011992971,0.00067676074,0.000030665993,0.0050717066,0.00028525668,0.06884182],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99773693,0.00050369673,0.00012073144,0.0002646788,0.0008203469,0.0005535847],"domain_scores_gemma":[0.99346393,0.0017108094,0.0015661241,0.00036682398,0.0023471182,0.00054510054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023742614,0.0006812071,0.0009196347,0.0031997887,0.00065956055,0.006594396,0.00043041655,0.0020630616,0.018933432],"category_scores_gemma":[0.015760045,0.00031291696,0.0007064453,0.0060336343,0.0007744631,0.0020914904,0.0014817254,0.0031058341,0.002814126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050957343,0.00069942133,0.0625929,0.00086790585,0.0007381461,0.0012644773,0.0014236775,0.048853945,0.0015397376,0.34240854,0.342496,0.19201955],"study_design_scores_gemma":[0.00062595453,0.0004661153,0.33700463,0.0009826745,0.00097060425,0.00043351945,0.002831678,0.012125579,0.0038851043,0.064292826,0.57621527,0.00016606513],"about_ca_topic_score_codex":0.06164436,"about_ca_topic_score_gemma":0.05220786,"teacher_disagreement_score":0.06164436,"about_ca_system_score_codex":0.0040831943,"about_ca_system_score_gemma":0.0028925475,"threshold_uncertainty_score":0.12257111},"labels":[],"label_agreement":null},{"id":"W3085810308","doi":"10.1111/obes.12431","title":"The Impact of Pessimistic Expectations on the Effects of COVID‐19‐Induced Uncertainty in the Euro Area*","year":2021,"lang":"en","type":"preprint","venue":"Oxford Bulletin of Economics and Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Pessimism; Shock (circulatory); Coronavirus disease 2019 (COVID-19); Inflation (cosmology); Economics; Econometrics; Production (economics); Industrial production; Monetary economics; Macroeconomics; Physics; Medicine","score_opus":0.0331084242503427,"score_gpt":0.26051701668610944,"score_spread":0.22740859243576672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3085810308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900081,0.00036172944,0.004578527,0.0012092668,0.00006444832,0.00001402885,0.00073120324,0.00009810229,0.0029344787],"genre_scores_gemma":[0.99900997,0.0000676481,0.00027994392,0.000060930488,0.000015526868,0.0000051556876,0.00023847948,0.000009554037,0.00031279447],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992112,0.00037676826,0.00004178126,0.00013025409,0.000057252335,0.00018261874],"domain_scores_gemma":[0.9881748,0.008587608,0.0019161993,0.00042501063,0.00043546205,0.00046088448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003008206,0.00070332095,0.000657538,0.00045025334,0.00041478226,0.0026649374,0.00069078436,0.0017348944,0.003068445],"category_scores_gemma":[0.0138421785,0.0004273861,0.0008755816,0.000492222,0.0008561727,0.0012230206,0.0012057108,0.0021990319,0.00023174187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005682257,0.00015525911,0.07401626,0.00006923634,0.00017970154,0.00039661812,0.00010782458,0.9058569,0.0010287707,0.011704387,0.0018354038,0.004081412],"study_design_scores_gemma":[0.000071323324,0.00033089612,0.02872865,0.000033627803,0.00008936458,0.00008804348,0.00021376794,0.9627324,0.0008605188,0.0060304184,0.0007642748,0.000056861198],"about_ca_topic_score_codex":0.021625066,"about_ca_topic_score_gemma":0.010067517,"teacher_disagreement_score":0.021625066,"about_ca_system_score_codex":0.0009144934,"about_ca_system_score_gemma":0.00062209176,"threshold_uncertainty_score":0.042998374},"labels":[],"label_agreement":null},{"id":"W3125375764","doi":"10.1111/obes.12030","title":"Peer Effects in UK Adolescent Substance Use: Never Mind the Classmates?","year":2013,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"School Choice and Performance","field":"Social Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University; University of the West of England; Queen's University Belfast; Joseph Rowntree Foundation","keywords":"Psychology; Substance use; Cannabis; Peer group; Peer influence; Association (psychology); Peer effects; Developmental psychology; Social psychology; Clinical psychology; Psychiatry","score_opus":0.020487809356049165,"score_gpt":0.24806135072253818,"score_spread":0.22757354136648902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125375764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986891,0.00028143122,0.00008044751,0.00009960808,0.0000126248215,0.0000035560631,0.00014280109,0.0000024329445,0.0006880424],"genre_scores_gemma":[0.99941003,0.00014059115,0.00002994923,0.000010110561,0.000015268979,0.000003132879,0.00009154795,0.0000018893957,0.00029745384],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99874485,0.00056015066,0.00008228889,0.00018012911,0.00026545502,0.00016713036],"domain_scores_gemma":[0.99473155,0.0014669028,0.0021681332,0.00025294072,0.0005368812,0.00084354036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079979387,0.00027837418,0.00052716024,0.0011810467,0.0004670359,0.0008923022,0.0003403959,0.00042291143,0.0037041493],"category_scores_gemma":[0.006865043,0.00019824013,0.00040605018,0.0010026433,0.00053482206,0.00063034915,0.0015262876,0.00053508795,0.00041665832],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049349237,0.000041184336,0.9953053,0.000016202832,0.00007152006,0.000090756665,0.0006703142,0.000110115405,0.00010552826,0.00013324346,0.00023770957,0.0031688688],"study_design_scores_gemma":[0.000002368681,0.00004595341,0.9985927,0.000014493474,0.000031907013,0.000054283468,0.00064452895,0.00024004294,0.00006043349,0.000027712938,0.0002822181,0.0000033052206],"about_ca_topic_score_codex":0.08372609,"about_ca_topic_score_gemma":0.08331444,"teacher_disagreement_score":0.08372609,"about_ca_system_score_codex":0.0007821144,"about_ca_system_score_gemma":0.00035484543,"threshold_uncertainty_score":0.16647756},"labels":[],"label_agreement":null},{"id":"W3126002596","doi":"10.1111/obes.12220","title":"To Pool or Not to Pool: Revisited","year":2017,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Estimator; Pooling; Mathematics; Dimension (graph theory); Panel data; Hausman test; Monte Carlo method; Fixed effects model; Statistics; Econometrics; Combinatorics; Computer science","score_opus":0.046978006882690306,"score_gpt":0.25778206798683123,"score_spread":0.21080406110414093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126002596","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21120419,0.013941495,0.68445444,0.03704946,0.0012254935,0.00046506687,0.001855326,0.0007946547,0.049009893],"genre_scores_gemma":[0.9209267,0.0028284993,0.062247787,0.004997267,0.00071619474,0.00030046413,0.0005860826,0.0002918849,0.007105071],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9641268,0.026736006,0.0009898489,0.0041535934,0.002766445,0.0012273919],"domain_scores_gemma":[0.8750748,0.08203292,0.011298773,0.021366706,0.008793219,0.0014335916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05317074,0.0007565918,0.0028677706,0.0016299278,0.0014219878,0.0052148616,0.003337164,0.0026924736,0.0119675975],"category_scores_gemma":[0.20503256,0.0007404199,0.0023962783,0.0028406573,0.004973774,0.010021813,0.0043221693,0.002696221,0.0012640613],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00082570355,0.00022142651,0.03349254,0.0011531884,0.0021072773,0.00082788995,0.004449759,0.02147092,0.0007996249,0.58977944,0.024480868,0.3203914],"study_design_scores_gemma":[0.00021018424,0.0005491301,0.018454526,0.0011973887,0.0012364422,0.00066343567,0.0035706433,0.051550608,0.002779106,0.88010275,0.039506152,0.0001796663],"about_ca_topic_score_codex":0.0055696634,"about_ca_topic_score_gemma":0.003603312,"teacher_disagreement_score":0.05317074,"about_ca_system_score_codex":0.0016973168,"about_ca_system_score_gemma":0.0037148604,"threshold_uncertainty_score":0.28119713},"labels":[],"label_agreement":null},{"id":"W3134412143","doi":"10.1111/obes.12435","title":"Work disability and the Northern Irish Troubles*","year":2021,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Economic and Social Research Council; Office of the First Minister and Deputy First Minister; Queen's University; Health and Social Care Research and Development Division; Public Health Agency; Atlantic Philanthropies; Centre for Ageing Research and Development in Ireland; United Kingdom Clinical Research Collaboration; Wellcome Trust; Queen's University Belfast","keywords":"Endogeneity; Causation; Irish; Politics; Patrolling; Work (physics); Terrorism; Criminology; Demographic economics; Psychology; Political science; Psychiatry; Economics; Law","score_opus":0.03166299152256683,"score_gpt":0.30988923079668856,"score_spread":0.2782262392741217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134412143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9772485,0.0007693198,0.000061329614,0.0022554044,0.00005567566,0.000018747569,0.005110719,0.0000058294336,0.014474571],"genre_scores_gemma":[0.99589527,0.00022720452,0.000035190544,0.00015547096,0.000045202538,0.000012924043,0.0018825016,0.0000028168668,0.0017433596],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988158,0.00032872905,0.00007059761,0.000111609486,0.000251296,0.0004219886],"domain_scores_gemma":[0.99600285,0.00044619397,0.0021776462,0.00024124664,0.00042733553,0.00070468825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008721718,0.0001649078,0.00027624745,0.0018203702,0.00065105944,0.0014805892,0.00040592693,0.00028674497,0.008273847],"category_scores_gemma":[0.004248428,0.00012813482,0.00027847505,0.002274114,0.00089117175,0.0004512005,0.0018270462,0.00070902146,0.00078384246],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091396556,0.00009803026,0.9796205,0.0000617463,0.00003964023,0.00028734296,0.0010323601,0.00024017769,0.000068034504,0.0004069958,0.006045814,0.012007969],"study_design_scores_gemma":[0.000005034812,0.00001727517,0.99495983,0.00003608037,0.0000045613406,0.000109041546,0.0019159602,0.000066523666,0.00001803058,0.00010805242,0.002754939,0.0000046761675],"about_ca_topic_score_codex":0.108239524,"about_ca_topic_score_gemma":0.15114525,"teacher_disagreement_score":0.108239524,"about_ca_system_score_codex":0.0021486017,"about_ca_system_score_gemma":0.0012690538,"threshold_uncertainty_score":0.21521902},"labels":[],"label_agreement":null},{"id":"W3152804186","doi":"10.1111/obes.12437","title":"Disentangling the Effects of Uncertainty, Monetary Policy and Leverage Shocks on the Economy*","year":2021,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Monetary policy; Economics; Leverage (statistics); Bayesian vector autoregression; Business cycle; Autoregressive model; Vector autoregression; Monetary economics; Econometrics; Inflation (cosmology); Real economy; Context (archaeology); Interest rate; Index (typography); Bayesian probability; Macroeconomics","score_opus":0.011603188417710701,"score_gpt":0.20091114709000527,"score_spread":0.18930795867229455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152804186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98493814,0.0010891695,0.009322809,0.00086043717,0.000018349288,0.000012477354,0.00025680766,0.00002961644,0.0034722148],"genre_scores_gemma":[0.9990976,0.00023747906,0.00039932254,0.00002177023,0.00002224766,0.0000015017191,0.0000901656,0.0000027405265,0.00012721769],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99943906,0.0002410471,0.00005285471,0.00006741788,0.00012781359,0.0000716998],"domain_scores_gemma":[0.97321534,0.022042457,0.0029074226,0.00060952216,0.00074315007,0.00048208624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023295083,0.0004723188,0.0005909838,0.0016030617,0.00023916525,0.002432993,0.00025021634,0.00062312634,0.0015378995],"category_scores_gemma":[0.019197969,0.00024982015,0.00041480796,0.0013190171,0.00050984515,0.0023103775,0.0009957891,0.0009880131,0.00017780921],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056201656,0.0001675441,0.79315734,0.00012350487,0.00079580786,0.00042100946,0.000200477,0.119006075,0.002089638,0.017315969,0.00054267084,0.06561804],"study_design_scores_gemma":[0.000019239127,0.00018485915,0.5140014,0.000116706404,0.00026109317,0.00017727542,0.00030243726,0.43710527,0.0022231513,0.044508222,0.0010297502,0.0000706196],"about_ca_topic_score_codex":0.003015008,"about_ca_topic_score_gemma":0.0026990806,"teacher_disagreement_score":0.003015008,"about_ca_system_score_codex":0.0003596982,"about_ca_system_score_gemma":0.00043848052,"threshold_uncertainty_score":0.012319803},"labels":[],"label_agreement":null},{"id":"W3205861099","doi":"10.1111/j.1468-0084.2011.00668.x","title":"Are Short‐lived Jobs Stepping Stones to Long‐Lasting Jobs?*","year":2011,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Counterfactual thinking; Spell; Unemployment; Duration (music); Quarter (Canadian coin); Economics; Labour economics; Demographic economics; Displaced workers; Stepping stone; Term (time); Psychology; Macroeconomics; Sociology; History; Social psychology","score_opus":0.06744127795661542,"score_gpt":0.23064288914349734,"score_spread":0.16320161118688192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205861099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99806195,0.00030978827,0.00026521154,0.00033372478,0.000009499719,0.0000037850389,0.00015329929,0.0000039481934,0.0008586105],"genre_scores_gemma":[0.9996106,0.000056364886,0.00004783037,0.000016795613,0.0000048594034,8.1867887e-7,0.00007506561,0.0000012641669,0.00018645605],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99955887,0.000109757326,0.000028573235,0.00006539144,0.00006339049,0.00017402331],"domain_scores_gemma":[0.99544203,0.00091396464,0.0019448,0.00016915829,0.00025034163,0.0012796667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008144943,0.000111784546,0.0002159455,0.0005800132,0.00054560363,0.0011661479,0.00051473576,0.00059272716,0.0056322333],"category_scores_gemma":[0.0042274804,0.00015236493,0.00035320432,0.0006202804,0.0008265762,0.00094952463,0.00087753014,0.0008149108,0.00055664225],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038168774,0.00010999056,0.97644866,0.00005394549,0.00007743719,0.00029087882,0.0008702368,0.0010767645,0.00045522,0.0019245442,0.000484362,0.017826257],"study_design_scores_gemma":[0.000009910577,0.0001502362,0.9923637,0.000060332874,0.00001978966,0.000233214,0.0026351146,0.001606953,0.0001414563,0.0015745,0.0011933321,0.000011522705],"about_ca_topic_score_codex":0.008776636,"about_ca_topic_score_gemma":0.01636851,"teacher_disagreement_score":0.008776636,"about_ca_system_score_codex":0.0004307451,"about_ca_system_score_gemma":0.00040069054,"threshold_uncertainty_score":0.018841684},"labels":[],"label_agreement":null},{"id":"W3211087980","doi":"10.1111/obes.12466","title":"Systemic Financial Stress and Macroeconomic Amplifications in the United Kingdom*","year":2021,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Financial crisis; Vector autoregression; Index (typography); Economics; Composite index; Financial market; Composite indicator; Coronavirus disease 2019 (COVID-19); Monetary economics; Financial system; Macroeconomics; Finance; Medicine; Internal medicine","score_opus":0.028940721794845126,"score_gpt":0.22536446812119823,"score_spread":0.1964237463263531,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211087980","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99440044,0.0010149017,0.0000997547,0.000932634,0.0000302476,0.000004208153,0.00068029814,0.000004524016,0.002833003],"genre_scores_gemma":[0.9992632,0.00022726979,0.00002620677,0.000046931444,0.000008907361,0.0000018375717,0.00019726042,9.634621e-7,0.0002273526],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996532,0.0000854209,0.00005538057,0.000047719597,0.00008083741,0.00007743188],"domain_scores_gemma":[0.9973748,0.00034678026,0.0013729244,0.000094625146,0.0005150313,0.0002958352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052958244,0.00018777826,0.0002481293,0.00080896576,0.00018456904,0.0012464295,0.00014040928,0.00026788248,0.0021596588],"category_scores_gemma":[0.0033633262,0.000100791825,0.00016320118,0.0013308991,0.00036802643,0.00049372733,0.0010315749,0.00030587747,0.00022083406],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024042214,0.000027294618,0.97071934,0.00011890481,0.00008688187,0.000554618,0.0015382315,0.0012745201,0.0006935637,0.0012118956,0.0028375417,0.020696769],"study_design_scores_gemma":[0.000004277559,0.00003178574,0.996573,0.00003898439,0.000011925816,0.00009948929,0.00093582977,0.00045488938,0.00008133029,0.00015236465,0.0016085051,0.000007694497],"about_ca_topic_score_codex":0.072377935,"about_ca_topic_score_gemma":0.06792662,"teacher_disagreement_score":0.072377935,"about_ca_system_score_codex":0.0014069437,"about_ca_system_score_gemma":0.0005577315,"threshold_uncertainty_score":0.14391327},"labels":[],"label_agreement":null},{"id":"W4283217532","doi":"10.1111/obes.12511","title":"Testing the Presence of Outliers in Regression Models*","year":2022,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"British Academy; Robertson Foundation","keywords":"Outlier; Econometrics; Statistics; Regression analysis; Linear regression; Regression; Scaling; Simple linear regression; Mathematics","score_opus":0.04818734289392757,"score_gpt":0.2175785361223709,"score_spread":0.16939119322844334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283217532","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58690524,0.0008438294,0.4008482,0.0026141664,0.00035960285,0.00039194326,0.0018934638,0.0017846603,0.004358804],"genre_scores_gemma":[0.97061026,0.000098819364,0.026826581,0.00022390051,0.0002383238,0.00020020113,0.0012459392,0.00009707295,0.00045893455],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.8659273,0.09781558,0.0098428875,0.010284934,0.012881167,0.0032482848],"domain_scores_gemma":[0.29759377,0.6156022,0.050316315,0.024011383,0.009879701,0.0025966803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07538104,0.0021640025,0.00326171,0.004443812,0.0017101387,0.0040615974,0.005122613,0.0038519863,0.0052354955],"category_scores_gemma":[0.3436742,0.0012800723,0.003402506,0.0054444135,0.0049901167,0.0056409137,0.005224513,0.0041776155,0.00075368065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018413458,0.00086664123,0.82900375,0.0005920256,0.005895502,0.0017977994,0.0015392271,0.07059903,0.0023208878,0.018672056,0.0052553904,0.061616335],"study_design_scores_gemma":[0.0005213005,0.0024040395,0.27308863,0.000247466,0.00093968364,0.001324148,0.0020901156,0.6446224,0.0060106297,0.06306849,0.0052851215,0.00039795556],"about_ca_topic_score_codex":0.0034488002,"about_ca_topic_score_gemma":0.0023758307,"teacher_disagreement_score":0.07538104,"about_ca_system_score_codex":0.0011061581,"about_ca_system_score_gemma":0.0016668966,"threshold_uncertainty_score":0.3986578},"labels":[],"label_agreement":null},{"id":"W4306404174","doi":"10.1111/obes.12528","title":"The All‐Gap Phillips Curve","year":2022,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; Dalhousie University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Output gap; Phillips curve; Inflation (cosmology); Economics; Unemployment; Econometrics; Variable (mathematics); Yield (engineering); Keynesian economics; Inflation rate; Monetary policy; Mathematics; Macroeconomics; Thermodynamics; Physics","score_opus":0.06302799741038599,"score_gpt":0.2184634873520236,"score_spread":0.15543548994163758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306404174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41775453,0.002927759,0.3766677,0.017533809,0.00048660726,0.00007057979,0.0021928498,0.0008428694,0.18152322],"genre_scores_gemma":[0.9903301,0.000494344,0.0020357056,0.00015212751,0.000089880974,0.000010328995,0.00019287177,0.00003454246,0.006660184],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99959165,0.000101904116,0.000021858406,0.000114733855,0.000089085086,0.0000808093],"domain_scores_gemma":[0.9984042,0.00065624,0.00032102247,0.00024285907,0.0002672204,0.00010855013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007732836,0.00031031718,0.00050531974,0.00040833128,0.00041029902,0.002031925,0.0005867265,0.0010917733,0.007305554],"category_scores_gemma":[0.008839689,0.00025789574,0.0005056168,0.0006132375,0.0012561339,0.0021699963,0.0007332377,0.0012098905,0.0008554437],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005906485,0.000023143499,0.008621258,0.00012556273,0.000047669553,0.00022569476,0.00028864984,0.04736265,0.00061161857,0.906339,0.0074292603,0.028866403],"study_design_scores_gemma":[0.000011235746,0.000039659437,0.0073527396,0.00003259721,0.00002456747,0.00015446804,0.00018847611,0.07180686,0.00041198503,0.9076856,0.012269171,0.000022539562],"about_ca_topic_score_codex":0.0056037144,"about_ca_topic_score_gemma":0.0022444297,"teacher_disagreement_score":0.007305554,"about_ca_system_score_codex":0.0008954526,"about_ca_system_score_gemma":0.0007346009,"threshold_uncertainty_score":0.024439514},"labels":[],"label_agreement":null},{"id":"W4312778257","doi":"10.1111/obes.70087","title":"The Effect of Brazil's Family Health Program on Cognitive Skills","year":2022,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Cognition; Psychology; Medicine; Developmental psychology; Psychiatry","score_opus":0.007402684500410067,"score_gpt":0.2810393278974532,"score_spread":0.2736366433970431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312778257","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9829075,0.0022016498,0.00008983942,0.004519375,0.0000733025,0.000049081547,0.0008351235,0.00002222183,0.009301917],"genre_scores_gemma":[0.99743795,0.0005586796,0.000076666794,0.00020157464,0.000022204751,0.000014536035,0.00011488039,0.0000055546566,0.0015678339],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99814177,0.0006500872,0.000050443505,0.00016099874,0.0001679974,0.0008287185],"domain_scores_gemma":[0.99254143,0.0032350388,0.0010978355,0.00032247216,0.0006008246,0.0022023544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016809009,0.00045291623,0.00053962594,0.0005434907,0.0010388339,0.0008430057,0.00087334524,0.0008634395,0.0070047607],"category_scores_gemma":[0.011297136,0.00017779379,0.0011250366,0.0008634305,0.0010137226,0.0005066695,0.0014327528,0.0012505137,0.00024184745],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036141712,0.0050570793,0.87662375,0.00045727068,0.0009109529,0.0008170489,0.00375149,0.0012367881,0.0016779646,0.006890701,0.0029920856,0.09597069],"study_design_scores_gemma":[0.00008533342,0.0007929482,0.99403244,0.00013011073,0.00034939416,0.00007214463,0.0010937515,0.0002606284,0.00027320132,0.00041524877,0.0024857149,0.000009073093],"about_ca_topic_score_codex":0.22171101,"about_ca_topic_score_gemma":0.30303618,"teacher_disagreement_score":0.22171101,"about_ca_system_score_codex":0.0031571907,"about_ca_system_score_gemma":0.00802552,"threshold_uncertainty_score":0.44084102},"labels":[],"label_agreement":null},{"id":"W4377287105","doi":"10.1111/obes.12569","title":"Information Equivalence among Transformations of Semi‐parametric Nonlinear Panel Data Models*","year":2023,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Mathematics; Multiplicative function; Equivalence (formal languages); Nonlinear system; Parametric statistics; Moment (physics); Applied mathematics; Upper and lower bounds; Algebraic number; Rank (graph theory); Transformation (genetics); Inference; Econometrics; Mathematical analysis; Statistics; Pure mathematics; Combinatorics; Computer science","score_opus":0.08009366656807947,"score_gpt":0.23504515816529814,"score_spread":0.15495149159721866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377287105","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051168583,0.00013028253,0.9422785,0.00056965696,0.000036241556,0.00006414478,0.00032763398,0.00014923638,0.0052756453],"genre_scores_gemma":[0.88750005,0.0004610152,0.10643866,0.00029793722,0.00016831946,0.00033665958,0.0012304999,0.00018423707,0.0033826088],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9892536,0.007008812,0.00057268696,0.0011445468,0.0015582262,0.00046218955],"domain_scores_gemma":[0.9470886,0.040396027,0.0041652285,0.0051917504,0.0026313043,0.00052709464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012284055,0.00055716775,0.0009446577,0.001530608,0.0005128622,0.0027587097,0.0010915643,0.0008570852,0.0049039116],"category_scores_gemma":[0.060812086,0.0004936339,0.001600741,0.0014689743,0.0032569016,0.0038882184,0.0030266992,0.0029901338,0.0008461549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012735222,0.000088435925,0.00174464,0.000072754636,0.00006310137,0.00013618177,0.00029390276,0.0751322,0.0011286861,0.88439745,0.0011744597,0.035640787],"study_design_scores_gemma":[0.000021307407,0.00006732478,0.0008589109,0.000025660518,0.000015282201,0.000054566313,0.000055843168,0.2757944,0.0009524906,0.720784,0.0013479834,0.000022266962],"about_ca_topic_score_codex":0.001065259,"about_ca_topic_score_gemma":0.00046425572,"teacher_disagreement_score":0.012284055,"about_ca_system_score_codex":0.0013231579,"about_ca_system_score_gemma":0.0010802277,"threshold_uncertainty_score":0.06496507},"labels":[],"label_agreement":null},{"id":"W4387640272","doi":"10.1111/obes.12577","title":"Non‐parametric Estimator for Conditional Mode with Parametric Features*","year":2023,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Social Sciences and Humanities Research Council of Canada; University of California, Riverside; University of Victoria","keywords":"Estimator; Mathematics; Parametric statistics; Modal; Conditional expectation; Applied mathematics; Statistics","score_opus":0.05613055512945646,"score_gpt":0.3572227645406896,"score_spread":0.3010922094112331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387640272","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006733729,0.00004628395,0.9924285,0.000056500714,0.000011422425,0.000024080684,0.000047307898,0.00021265066,0.0004394514],"genre_scores_gemma":[0.54760605,0.00021349946,0.44701868,0.0002207915,0.000092087714,0.0003520098,0.00047870958,0.0002606105,0.0037575832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974146,0.0013789491,0.00008794724,0.0004700235,0.0005277323,0.000120694516],"domain_scores_gemma":[0.98071575,0.013737946,0.0016073582,0.0024198762,0.0013589509,0.00016004375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007617374,0.0006911271,0.0010296989,0.0013172916,0.00033217805,0.0011146745,0.0024341375,0.0008994589,0.005702805],"category_scores_gemma":[0.04338217,0.0004395946,0.0011426846,0.001109335,0.0011479263,0.0020837837,0.0020147401,0.0020852895,0.0007469335],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003796264,0.00023461568,0.02266575,0.00048000074,0.0004620132,0.00028059407,0.0004342531,0.32217103,0.008129911,0.32566458,0.004614155,0.31448355],"study_design_scores_gemma":[0.00001870194,0.00007997737,0.0036501882,0.000052921834,0.000046896523,0.00012325426,0.00004001827,0.92157054,0.0024221656,0.06959796,0.0023541641,0.000043212785],"about_ca_topic_score_codex":0.001801142,"about_ca_topic_score_gemma":0.0015497435,"teacher_disagreement_score":0.007617374,"about_ca_system_score_codex":0.00063367595,"about_ca_system_score_gemma":0.00097039936,"threshold_uncertainty_score":0.04028499},"labels":[],"label_agreement":null},{"id":"W4390344511","doi":"10.1111/obes.12587","title":"Global Demand and Supply Sentiment: Evidence From Earnings Calls*","year":2023,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Demand shock; Recession; Earnings; Supply and demand; Economics; Supply shock; Bayesian vector autoregression; Great recession; Vector autoregression; Monetary economics; Coronavirus disease 2019 (COVID-19); Econometrics; Bayesian probability; Macroeconomics; Labour economics; Computer science; Finance; Monetary policy","score_opus":0.020003467372627617,"score_gpt":0.2228679807457021,"score_spread":0.20286451337307448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390344511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99196786,0.00011354682,0.00018361557,0.0005835953,0.000022190094,0.000007217905,0.002090284,0.0000087559665,0.0050230366],"genre_scores_gemma":[0.9974025,0.00010931581,0.00008198744,0.000076550394,0.000042298936,0.000006981285,0.0016741189,0.000009694976,0.0005965542],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995913,0.00011232758,0.000042712392,0.000063508916,0.00012845437,0.0000617819],"domain_scores_gemma":[0.9933468,0.0020611011,0.0029607052,0.00030119013,0.0010153012,0.00031484425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00083271676,0.00015569913,0.00017762976,0.00092098856,0.00027328279,0.0008641989,0.00016075521,0.0003568468,0.0033129894],"category_scores_gemma":[0.0061799907,0.000101930906,0.00012032415,0.0015483245,0.0004112092,0.0007271733,0.00091605925,0.0004925515,0.0007957254],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041547918,0.00009465195,0.9628814,0.00010913048,0.000066094915,0.00032310557,0.003675021,0.000762359,0.0018879232,0.0009902733,0.0069938684,0.02180073],"study_design_scores_gemma":[0.0000056778476,0.00004607615,0.9910124,0.000023838384,0.000011552669,0.000062396466,0.0037630852,0.0010780037,0.0003003912,0.0003070099,0.0033748539,0.000014688334],"about_ca_topic_score_codex":0.0058457856,"about_ca_topic_score_gemma":0.007331879,"teacher_disagreement_score":0.0058457856,"about_ca_system_score_codex":0.0003147388,"about_ca_system_score_gemma":0.00014820007,"threshold_uncertainty_score":0.011623502},"labels":[],"label_agreement":null},{"id":"W4392167308","doi":"10.1111/obes.12602","title":"Multivariate Trend‐Cycle‐Seasonal Decompositions with Correlated Innovations*","year":2024,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Multivariate statistics; Econometrics; Seasonality; Seasonal adjustment; Exploit; Component (thermodynamics); Univariate; Multivariate analysis; Identification (biology); Consumption (sociology); Variable (mathematics); Economics; Statistics; Computer science; Mathematics","score_opus":0.013299858382768152,"score_gpt":0.21593736493471966,"score_spread":0.2026375065519515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392167308","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09423075,0.00032594046,0.90191,0.0003192889,0.000050726285,0.000041160103,0.0007783336,0.00028525005,0.0020585784],"genre_scores_gemma":[0.8924035,0.00080901466,0.09803302,0.000066774395,0.0001350709,0.00013080004,0.0013879066,0.00022092923,0.0068130125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99940264,0.00023815586,0.000037907146,0.00013337501,0.00010114821,0.00008683472],"domain_scores_gemma":[0.9976591,0.0010715231,0.00060214347,0.00031569367,0.00023806686,0.000113470596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002141866,0.0005915964,0.0006312143,0.0013795694,0.00022979749,0.0011413884,0.0004965258,0.0004083445,0.0046737855],"category_scores_gemma":[0.005734163,0.00039967915,0.0011218837,0.0019329848,0.0005534616,0.0011791594,0.00073543476,0.00094379456,0.00037655982],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019219148,0.000112987036,0.027605219,0.00019708398,0.00030673324,0.00032448818,0.00034144404,0.3316894,0.006395739,0.5243664,0.0048389463,0.10362939],"study_design_scores_gemma":[0.0000072447406,0.000024488969,0.0071074716,0.000016872356,0.000026413465,0.000044045853,0.000027157741,0.9184351,0.00036713475,0.07198356,0.0019383247,0.00002216677],"about_ca_topic_score_codex":0.0056125135,"about_ca_topic_score_gemma":0.004667364,"teacher_disagreement_score":0.0056125135,"about_ca_system_score_codex":0.0005326251,"about_ca_system_score_gemma":0.0009495622,"threshold_uncertainty_score":0.015635371},"labels":[],"label_agreement":null},{"id":"W4406856342","doi":"10.1111/obes.12662","title":"On My Own: Boosting Financial Literacy Among Disadvantaged Youth in Peru","year":2025,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Citi Foundation; International Development Research Centre; Ford Foundation","keywords":"Financial literacy; Disadvantaged; Boosting (machine learning); Economics; Literacy; Political science; Economic growth; Business; Finance; Computer science","score_opus":0.007108717576064414,"score_gpt":0.21051003584804273,"score_spread":0.20340131827197833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406856342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99117076,0.0019683426,0.0003347585,0.0011861508,0.00019665889,0.0014055603,0.00038326407,0.00007168114,0.0032828993],"genre_scores_gemma":[0.99353373,0.0009085261,0.0010064864,0.000608302,0.00007480184,0.002238686,0.00015344389,0.0000057931934,0.0014701297],"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.9989666,0.00074866624,0.000047989754,0.000076893186,0.00004719647,0.00011268374],"domain_scores_gemma":[0.9986638,0.0005707012,0.00021362175,0.00008434892,0.00008334046,0.0003843034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016053796,0.00035709998,0.00084473734,0.00044994574,0.00062321336,0.000560481,0.00053237035,0.0012497065,0.009702073],"category_scores_gemma":[0.0039603133,0.00019655356,0.00088799495,0.00035274398,0.0005740509,0.00044177796,0.001081114,0.0009742726,0.00063355337],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.26474598,0.13022228,0.06382019,0.01105018,0.0031110316,0.00050712336,0.004148586,0.0014112914,0.007997852,0.001431011,0.007932624,0.5036218],"study_design_scores_gemma":[0.1598405,0.5493588,0.2537451,0.0034004978,0.0043420726,0.00021435281,0.003050231,0.0020944416,0.0044093723,0.0017638649,0.017687002,0.00009371376],"about_ca_topic_score_codex":0.0032382219,"about_ca_topic_score_gemma":0.0036467111,"teacher_disagreement_score":0.009702073,"about_ca_system_score_codex":0.00029831805,"about_ca_system_score_gemma":0.0005554193,"threshold_uncertainty_score":0.032456696},"labels":[],"label_agreement":null},{"id":"W82695829","doi":"10.1111/obes.12236","title":"Income Inequality and Saving","year":2018,"lang":"en","type":"article","venue":"Oxford Bulletin of Economics and Statistics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Economics; Inequality; Consumption (sociology); Economic inequality; Demographic economics; Income distribution; Distribution (mathematics); Econometrics; Percentage point; Aggregate (composite); Panel Study of Income Dynamics; Labour economics; Mathematics","score_opus":0.029521224878094658,"score_gpt":0.28815712539794647,"score_spread":0.2586359005198518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W82695829","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9187676,0.0042746826,0.00070970005,0.0057817926,0.00008321772,0.000011681107,0.0027090732,0.000020250005,0.06764202],"genre_scores_gemma":[0.9978871,0.0005932575,0.000053779157,0.00008568997,0.000039201663,0.0000035538615,0.0003284156,0.0000022293966,0.0010067921],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996531,0.00010764396,0.000018485036,0.000042726882,0.00005479882,0.00012328419],"domain_scores_gemma":[0.9980197,0.0005538641,0.00086222554,0.00009102006,0.00022664282,0.00024656125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005383716,0.00014277465,0.0001504374,0.0013158056,0.00044261807,0.0008819775,0.00017167808,0.00024284681,0.0080238115],"category_scores_gemma":[0.0031427925,0.00005557212,0.00015367342,0.0018449965,0.0006516451,0.00063478004,0.0010186445,0.00055273704,0.00055576616],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008966202,0.00007390627,0.91825265,0.0000655613,0.00010621827,0.00028140788,0.0011897704,0.0018171642,0.00015559043,0.039401982,0.006398074,0.032168027],"study_design_scores_gemma":[0.0000039092306,0.00002672491,0.9689112,0.00009958233,0.00003100123,0.00016947315,0.0013177282,0.0010193049,0.00020436457,0.01673201,0.011474533,0.000010061344],"about_ca_topic_score_codex":0.006919706,"about_ca_topic_score_gemma":0.008204116,"teacher_disagreement_score":0.0080238115,"about_ca_system_score_codex":0.00057831575,"about_ca_system_score_gemma":0.00025569226,"threshold_uncertainty_score":0.026842296},"labels":[],"label_agreement":null}]}