{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":7,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":7,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"100d26f37300","filters":{"venue":"Journal of Business Cycle Research"}},"results":[{"id":"W3154035703","doi":"10.1007/s41549-021-00055-5","title":"Predicting the German Economy: Headline Survey Indices Under Test","year":2021,"lang":"en","type":"article","venue":"Journal of Business Cycle Research","topic":"German Economic Analysis & Policies","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Headline; Nowcasting; Gross domestic product; Tertiary sector of the economy; German; Sample (material); Economic indicator; Service (business); Economics; Quarter (Canadian coin); Publication; Gross value added; Predictive power; Private sector; Manufacturing sector; Business; Economy; Macroeconomics; Advertising; Geography; Economic growth","authors":[{"name":"Robert Lehmann","is_ca":false},{"name":"Magnus Reif","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1278880864179363,"gpt":0.3476423485552197,"spread":0.2197542621372834,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002389121,0.0006237568,0.0005054072,0.001230091,0.0001363117,0.001193867,0.0003295282,0.0005011012,0.002350391],"category_scores_gemma":[0.00668267,0.0001563452,0.0003002795,0.001508632,0.0001908452,0.000735738,0.0004284724,0.0004252201,0.001039564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005513721,"about_ca_system_score_gemma":0.0004765034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02520573,"about_ca_topic_score_gemma":0.01062246,"domain_scores_codex":[0.9992606,0.0002849871,0.00003266196,0.0001585796,0.0001482002,0.0001150516],"domain_scores_gemma":[0.9940752,0.002750608,0.001343228,0.0005314061,0.0009476067,0.0003519405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004865399,0.0001097121,0.9202942,0.00005407184,0.0001925056,0.00007731581,0.00007358161,0.04333616,0.0009792944,0.0006410605,0.005556555,0.02819889],"study_design_scores_gemma":[0.00006622788,0.0005037134,0.8077814,0.0000353723,0.0001649952,0.00005629749,0.0005049793,0.1801175,0.004358682,0.0006449748,0.005721705,0.00004420269],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9864226,0.0002022996,0.002570071,0.0002360017,0.00002805534,0.00003623285,0.007997203,0.0001644094,0.002343047],"genre_scores_gemma":[0.989267,0.0001547948,0.0009080858,0.00004259022,0.0000214126,0.00001579389,0.008849622,0.00001361829,0.0007270311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02520573,"threshold_uncertainty_score":0.05011803,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385879245","doi":"10.1007/s41549-023-00085-1","title":"The Usefulness of High-Frequency Alternative Data to Obtain Nowcasts for Japan’s GDP: Evidence from Credit Card Data","year":2023,"lang":"en","type":"article","venue":"Journal of Business Cycle Research","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Japan Society for the Promotion of Science London","keywords":"Nowcasting; Credit card; Real-time data; Computer science; Smart card; Coronavirus disease 2019 (COVID-19); Quarter (Canadian coin); Econometrics; Economics; Geography; Computer security; World Wide Web","authors":[{"name":"Satoshi Urasawa","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4472701139434734,"gpt":0.3895303812215156,"spread":0.05773973272195787,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009878321,0.0006060021,0.0005519552,0.004250531,0.0007932434,0.003585006,0.001507268,0.001794474,0.00286445],"category_scores_gemma":[0.05708117,0.0005290247,0.0005389071,0.004904631,0.0008649127,0.004118579,0.001311757,0.001487314,0.000732548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007219837,"about_ca_system_score_gemma":0.0009653193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03158366,"about_ca_topic_score_gemma":0.02967387,"domain_scores_codex":[0.9958777,0.001918177,0.0005186558,0.0006925056,0.0006866452,0.0003062588],"domain_scores_gemma":[0.8960028,0.06669977,0.01491248,0.008816388,0.01185693,0.001711748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001513683,0.0003808162,0.9198127,0.00036584,0.0008005982,0.0004799237,0.001786156,0.005064315,0.001663859,0.004483792,0.004876909,0.05877138],"study_design_scores_gemma":[0.0003678716,0.0002323942,0.950496,0.0002076117,0.0009886293,0.0001656921,0.002538654,0.0300208,0.002164202,0.003623035,0.009064101,0.0001310534],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802917,0.00124656,0.00561833,0.001000903,0.0001685194,0.00007271804,0.004949403,0.00006532168,0.00658659],"genre_scores_gemma":[0.9914356,0.0004949019,0.002812184,0.00008546984,0.0001388343,0.00002239338,0.004559447,0.00002318456,0.0004279822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03158366,"threshold_uncertainty_score":0.06279963,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4415622343","doi":"10.1007/s41549-025-00110-5","title":"Foreign Policy Uncertainty and Export Dynamics: Insights from a Developing Economy","year":2025,"lang":"en","type":"article","venue":"Journal of Business Cycle Research","topic":"Economic and Technological Innovation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Calgary","funders":"","keywords":"Causality (physics); Resilience (materials science); Developing country; Psychological resilience; Panel data","authors":[{"name":"S. M. Woahid Murad","is_ca":false},{"name":"Aklima Akter","is_ca":false},{"name":"Arifur Rahman","is_ca":false},{"name":"Mohammad Iqbal Hossain","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07727290100512266,"gpt":0.3165920868559663,"spread":0.2393191858508437,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008814643,0.0002149195,0.0004940195,0.0005524194,0.0005184498,0.002234087,0.0003829811,0.0008251557,0.002901407],"category_scores_gemma":[0.004153302,0.0001536734,0.0003788291,0.00124298,0.0007742787,0.001535367,0.0006353184,0.001464314,0.0001469861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001000442,"about_ca_system_score_gemma":0.001075168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03171478,"about_ca_topic_score_gemma":0.02372648,"domain_scores_codex":[0.9999319,0.0000237436,0.000004863785,0.000009487504,0.000008679255,0.00002120942],"domain_scores_gemma":[0.9962069,0.002973552,0.0004427849,0.00007945573,0.0001470931,0.0001502851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001637677,0.001023402,0.4211885,0.0002960353,0.0003572233,0.004172246,0.002912333,0.3415881,0.003267038,0.1773357,0.006704571,0.03951719],"study_design_scores_gemma":[0.000317203,0.0004814817,0.3230536,0.0001774161,0.000572593,0.000608555,0.01123016,0.456905,0.002521645,0.1922274,0.01176164,0.0001433586],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900672,0.000624647,0.001145431,0.001745537,0.00000670892,0.000007638546,0.0003059088,0.00001265234,0.00608424],"genre_scores_gemma":[0.9983204,0.0008180505,0.0001481873,0.00004416356,0.00001165678,0.000002202907,0.00009081145,0.000004232355,0.0005602934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03171478,"threshold_uncertainty_score":0.06306034,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4417490727","doi":"10.1007/s41549-025-00119-w","title":"Business Cycle Dating for Pakistan’s Economy","year":2025,"lang":"en","type":"article","venue":"Journal of Business Cycle Research","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Business cycle; Quarter (Canadian coin); Recession; Real gross domestic product; National accounts; Gross domestic product; Economic statistics; Work (physics); Dashboard","authors":[{"name":"Ateeb Akhter Shah Syed","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1573631720719315,"gpt":0.3681319841840492,"spread":0.2107688121121177,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009240189,0.0001417498,0.0001674414,0.002388577,0.001181927,0.001528084,0.000230904,0.0005361486,0.006164033],"category_scores_gemma":[0.006705423,0.0001308934,0.0001719886,0.002522121,0.000268657,0.001303702,0.0005528761,0.001031925,0.0008575877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001117078,"about_ca_system_score_gemma":0.001183311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03530649,"about_ca_topic_score_gemma":0.03888684,"domain_scores_codex":[0.9998305,0.00003493758,0.00001528839,0.00003715885,0.00003667421,0.00004545409],"domain_scores_gemma":[0.9973808,0.000750422,0.0004251671,0.0001580113,0.001123547,0.0001620172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004921686,0.000109337,0.5887419,0.0002207631,0.00009553197,0.001587259,0.002814909,0.01357546,0.0008776858,0.1227496,0.05292215,0.2158131],"study_design_scores_gemma":[0.00004304492,0.0001565442,0.7899421,0.000258569,0.0001054147,0.0007265238,0.004343639,0.02477944,0.001989024,0.03284483,0.1447176,0.00009320991],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9104908,0.002714023,0.004904483,0.00376195,0.0005574339,0.00003495392,0.006289717,0.0001291201,0.07111755],"genre_scores_gemma":[0.9947051,0.0006408935,0.0005796059,0.0000632566,0.00006737806,0.000005742568,0.001152996,0.00001472682,0.002770398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03530649,"threshold_uncertainty_score":0.07020193,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W36600390","doi":"10.1007/s41549-021-00058-2","title":"Trend-Cycle Interactions and the Subprime Crisis: Analysis of US and Canadian Output","year":2021,"lang":"en","type":"preprint","venue":"Journal of Business Cycle Research","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Heteroscedasticity; Subprime crisis; Volatility (finance); Economics; Structural break; Econometrics; Business cycle; Shock (circulatory); Variance decomposition of forecast errors; Variance (accounting); Vector autoregression; Financial crisis; Monetary economics; Macroeconomics","authors":[{"name":"Max Soloschenko","is_ca":false},{"name":"Enzo Weber","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1414982049107943,"gpt":0.326701248246754,"spread":0.1852030433359597,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009895958,0.0005255655,0.0006491291,0.002527808,0.00152152,0.002935771,0.0009869735,0.0007667786,0.004718566],"category_scores_gemma":[0.006619725,0.0002826656,0.00086869,0.006673754,0.0007259612,0.0009714266,0.0009043636,0.001067733,0.0003280425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02046586,"about_ca_system_score_gemma":0.01724265,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9906411,"about_ca_topic_score_gemma":0.989489,"domain_scores_codex":[0.9996458,0.00002935295,0.00001298403,0.00004676767,0.0001134179,0.0001516652],"domain_scores_gemma":[0.9981107,0.0003840422,0.0001786902,0.00006658411,0.0009444425,0.0003154762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00139026,0.0001658265,0.878307,0.0001823781,0.0005210364,0.0005324404,0.002797655,0.041482,0.002171521,0.01519221,0.02023079,0.0370268],"study_design_scores_gemma":[0.00002379564,0.0000162807,0.9673029,0.00002389001,0.0001145216,0.00003271436,0.00147169,0.02455335,0.0003097424,0.0006762451,0.005429288,0.00004553728],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895403,0.0006297159,0.0001806037,0.0004925383,0.00001191688,0.00001494458,0.004894105,0.00003821888,0.004197638],"genre_scores_gemma":[0.9927631,0.0006120588,0.0001416025,0.0000404912,0.000008846459,0.000006814163,0.004261054,0.00003058769,0.0021355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02046586,"threshold_uncertainty_score":0.1484909,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4404049309","doi":"10.1007/s41549-024-00101-y","title":"Output Gaps: Editor’s Introduction","year":2024,"lang":"en","type":"article","venue":"Journal of Business Cycle Research","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"","keywords":"Computer science","authors":[{"name":"Simon van Norden","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1335818549059233,"gpt":0.32355152173741,"spread":0.1899696668314866,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008107577,0.00404192,0.003623808,0.003849047,0.001962551,0.007914631,0.003724586,0.01290872,0.01593533],"category_scores_gemma":[0.04980272,0.001099347,0.002601862,0.003223104,0.001786536,0.004423426,0.002448014,0.0149387,0.007870881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002317631,"about_ca_system_score_gemma":0.003845011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002163718,"about_ca_topic_score_gemma":0.003794353,"domain_scores_codex":[0.9961123,0.0006540227,0.0007674554,0.0007847816,0.001328502,0.0003530069],"domain_scores_gemma":[0.9551296,0.01684905,0.004032837,0.001287138,0.02017785,0.00252357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004485889,0.00001964575,0.0001082419,0.0004454268,0.00002957243,0.00005798267,0.00001300116,0.00005937535,0.00004960561,0.0003079332,0.9916569,0.007207449],"study_design_scores_gemma":[0.0001505174,0.0000836125,0.002585429,0.002314358,0.0002159405,0.000272197,0.00009746054,0.0004325266,0.0003562447,0.002952212,0.9904596,0.00007994286],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00007412731,0.008343385,0.0001723477,0.04469566,0.945921,0.00001266576,0.0002068557,0.00003756249,0.0005363884],"genre_scores_gemma":[0.001044777,0.00637636,0.0002235742,0.03267273,0.956025,0.00003357999,0.00009835186,0.00005500858,0.003470544],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01593533,"threshold_uncertainty_score":0.05330902,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4417474217","doi":"10.1007/s41549-025-00117-y","title":"Structural Breaks in Uncertainty and the Business Cycle in a Small and Open Economy","year":2025,"lang":"en","type":"article","venue":"Journal of Business Cycle Research","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Comisión Sectorial de Investigación Científica","keywords":"Business cycle; Open economy; Small open economy; Quarter (Canadian coin); Construct (python library); Differential (mechanical device); Structural break; World economy","authors":[{"name":"Bibiana Lanzilotta","is_ca":false},{"name":"Gabriela Mordecki","is_ca":false},{"name":"Pablo Tapie","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05351983778401807,"gpt":0.3150140480417731,"spread":0.261494210257755,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002328641,0.0002216954,0.0008657051,0.0006155652,0.000590608,0.002541198,0.0006020166,0.001659483,0.002343683],"category_scores_gemma":[0.02185915,0.0003814199,0.0005427279,0.0008318123,0.0017751,0.003160276,0.001011128,0.00202588,0.0001375554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001218522,"about_ca_system_score_gemma":0.0004818028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004916724,"about_ca_topic_score_gemma":0.00421883,"domain_scores_codex":[0.9995652,0.0001326912,0.00003906063,0.00009203726,0.00007250294,0.00009849432],"domain_scores_gemma":[0.9851539,0.01024159,0.002998132,0.00051436,0.0004614384,0.000630584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00181191,0.0004218892,0.1607617,0.0001992889,0.0005429851,0.001784221,0.001800398,0.3964645,0.006153468,0.3889342,0.003565705,0.03755973],"study_design_scores_gemma":[0.0001437782,0.0002539358,0.09473387,0.0000305989,0.0001109368,0.0002210742,0.0009700608,0.3930365,0.0007159243,0.5083001,0.001394976,0.00008838571],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874949,0.0004215941,0.00864869,0.001582761,0.00002623101,0.000009804815,0.0001590182,0.00002669142,0.00163034],"genre_scores_gemma":[0.999521,0.00009185634,0.0001377422,0.00001523488,0.00001510104,0.000002028875,0.00002491385,0.000002475331,0.0001895638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004916724,"threshold_uncertainty_score":0.01231515,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}