{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":6,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":6,"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":"180b2de319c7","filters":{"venue":"Review of Economic Perspectives"}},"results":[{"id":"W1977826978","doi":"10.2478/revecp-2014-0003","title":"Using Data Envelopment Analysis: A Case of Universities","year":2014,"lang":"en","type":"article","venue":"Review of Economic Perspectives","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Data envelopment analysis; Construct (python library); Point (geometry); Stakeholder; Operations research; Computer science; Management science; Environmental economics; Economics; Engineering; Mathematics; Statistics; Management","authors":[{"name":"Tomáš Rosenmayer","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1857000248472012,"gpt":0.4505164293760519,"spread":0.2648164045288506,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005307613,0.0001183074,0.0009595325,0.000662039,0.00006119413,0.00002138278,0.001111059,0.0000280198,0.0004771979],"category_scores_gemma":[0.0007250084,0.0001002615,0.0003321277,0.0009594045,0.0002753525,0.0003640131,0.0003550855,0.00005310638,0.00003043895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001876522,"about_ca_system_score_gemma":0.0002572927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004939722,"about_ca_topic_score_gemma":0.0001781915,"domain_scores_codex":[0.9977144,0.0003785567,0.0009226504,0.0005875765,0.0002637736,0.0001330612],"domain_scores_gemma":[0.996347,0.0007278388,0.0009443656,0.001690513,0.0002367634,0.00005359133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002005307,0.002477417,0.03160609,0.007632412,0.02979451,0.0003745923,0.06117211,0.1338662,0.00207462,0.4879678,0.01831039,0.2245234],"study_design_scores_gemma":[0.000848245,0.0001810554,0.004095433,0.003653795,0.009803154,0.0003393162,0.1759447,0.7726461,0.0003633078,0.00525154,0.02567165,0.001201702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8466727,0.1096384,0.02576672,0.0006067295,0.000148128,0.0002913638,0.0003429666,0.00002197148,0.0165111],"genre_scores_gemma":[0.9891945,0.005551818,0.00502808,0.00004238704,0.00002597859,4.74968e-7,0.000005842372,0.00000480418,0.0001461234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6387799,"threshold_uncertainty_score":0.5224983,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2291730400","doi":"10.1515/revecp-2015-0028","title":"Residential Real Estate in Europe: An Exploration of Common Risk Factors","year":2015,"lang":"en","type":"article","venue":"Review of Economic Perspectives","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Bishop's University","funders":"","keywords":"Real estate; Renting; Proxy (statistics); Economics; Econometrics; Portfolio; Capital asset pricing model; Market liquidity; Financial economics; Explanatory power; Diversification (marketing strategy); Capitalization rate; Real estate investment trust; Business; Finance; Marketing","authors":[{"name":"Elena Druică","is_ca":false},{"name":"Călin Vâlsan","is_ca":true},{"name":"Rodica Ianole","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.09571902757410418,"gpt":0.3046373249332094,"spread":0.2089182973591052,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001506627,0.0001590684,0.0008468592,0.0002496516,0.00002546806,0.00002232275,0.0002500881,0.0000568552,0.0001195338],"category_scores_gemma":[0.000271844,0.0001865273,0.0001129814,0.0001569484,0.0001007154,0.001238487,0.00005452138,0.0001153651,0.00007926657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002943061,"about_ca_system_score_gemma":0.00009346838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005442545,"about_ca_topic_score_gemma":0.001091987,"domain_scores_codex":[0.9981905,0.0001019028,0.001139228,0.0003686974,0.00002130556,0.0001784032],"domain_scores_gemma":[0.9983298,0.00005490753,0.001081334,0.0003832984,0.00005818384,0.00009243051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003243497,0.001118388,0.6920017,0.002610274,0.0002882421,0.000007167911,0.04615918,0.004641188,0.00003250979,0.2297374,0.001620453,0.02145911],"study_design_scores_gemma":[0.01135823,0.003587297,0.6098483,0.006637162,0.000343722,0.00001887058,0.06621461,0.02700829,0.001494479,0.2095437,0.05854808,0.005397248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8947278,0.00569464,0.00005151587,0.0000992196,0.0002275632,0.0002417225,0.0001172254,0.00001575402,0.09882452],"genre_scores_gemma":[0.7090029,0.2906698,0.0001937963,0.0000068507,0.00005179878,0.000005977226,0.00002387148,0.00002078137,0.00002430375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2849751,"threshold_uncertainty_score":0.8227537,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3116709495","doi":"10.2478/revecp-2020-0020","title":"The Wagner’s law testing in the Visegrád Four countries","year":2020,"lang":"en","type":"article","venue":"Review of Economic Perspectives","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"China Scholarship Council","keywords":"Cointegration; Economics; Czech; Quarter (Canadian coin); Gross domestic product; Johansen test; Gross fixed capital formation; Macroeconomics; Econometrics; Error correction model; Geography","authors":[{"name":"Žaneta Tesařová","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08425647872933285,"gpt":0.2662199521389003,"spread":0.1819634734095675,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001279868,0.0001738409,0.0005858409,0.00003867404,0.000176465,0.00007675953,0.0006514921,0.00004620915,0.0001207009],"category_scores_gemma":[0.0005857271,0.0001286591,0.0001905146,0.0001357683,0.0002836307,0.0002515058,0.00007479869,0.0001988104,0.0005532698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001508913,"about_ca_system_score_gemma":0.00004115678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003028196,"about_ca_topic_score_gemma":0.00008030406,"domain_scores_codex":[0.9983469,0.00005458805,0.0009117028,0.0003714936,0.00002253209,0.0002928163],"domain_scores_gemma":[0.9985111,0.0005463861,0.0005060023,0.0003610697,0.00001937541,0.00005605274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007804504,0.0000140255,0.002947697,0.0004389419,0.00003071162,0.000001036402,0.001591125,0.00001204601,8.30141e-7,0.9918637,0.002812934,0.0002791957],"study_design_scores_gemma":[0.001139706,0.0003105235,0.0249333,0.001294122,0.0000410776,0.0000303714,0.005686261,0.003402595,0.00003089001,0.3384603,0.6237949,0.000875952],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02682348,0.2917087,0.00002604547,0.0794078,0.0002382513,0.0008651317,0.0001862667,0.00003692681,0.6007074],"genre_scores_gemma":[0.9630527,0.02909175,0.00008704266,0.007284478,0.0003650343,0.00005334228,0.00000226205,0.00002031889,0.00004306988],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9362292,"threshold_uncertainty_score":0.7111348,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2304680947","doi":"10.1515/revecp-2015-0013","title":"Determinants of Gratuity Size in the Czech Republic: Evidence from Four Inexpensive Restaurants in Brno","year":2015,"lang":"en","type":"article","venue":"Review of Economic Perspectives","topic":"Psychology of Social Influence","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Czech; Advertising; Business; Consumption (sociology); Demographic economics; Economics; Sociology","authors":[{"name":"Michal Kvasnička","is_ca":false},{"name":"Monika Szalaiová","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1521456892386997,"gpt":0.4414634041383583,"spread":0.2893177148996586,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00392664,0.0001210076,0.0005985877,0.00007366818,0.00005305709,0.00001677411,0.0008083583,0.00009907374,0.00007557043],"category_scores_gemma":[0.009460267,0.0001029039,0.0001053379,0.0002985905,0.0008251634,0.0005915377,0.00006417521,0.0001909898,0.0000172315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004090388,"about_ca_system_score_gemma":0.0005673764,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02283894,"about_ca_topic_score_gemma":0.02118051,"domain_scores_codex":[0.9975951,0.0009914815,0.0006267106,0.0003502263,0.0001913979,0.0002450383],"domain_scores_gemma":[0.9974589,0.001383011,0.0005148763,0.0003978547,0.0001802401,0.00006516139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001164021,0.0002324852,0.7361634,0.0003718213,0.00003483405,0.00003796831,0.2479744,0.000003861376,0.000222099,0.005807383,0.002669991,0.006365361],"study_design_scores_gemma":[0.000480056,0.00008416735,0.8857803,0.006655713,0.00001908975,0.00000400169,0.09318558,0.00000473777,0.0000657543,0.01251697,0.0009886449,0.0002150037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9317542,0.05888833,4.242271e-7,0.0037718,0.000146023,0.0005117207,0.00001367992,0.000007468318,0.004906333],"genre_scores_gemma":[0.9324701,0.06686774,0.0002000709,0.0003273982,0.00007683996,0.0000271075,2.971258e-7,0.000005390953,0.00002498337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1547888,"threshold_uncertainty_score":0.9988835,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2338290027","doi":"10.1515/revecp-2015-0018","title":"An Evaluation of Selected Economic Areas according to Similarity of Supply and Demand Shocks","year":2015,"lang":"en","type":"article","venue":"Review of Economic Perspectives","topic":"Global Financial Crisis and Policies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Economics; Demand shock; Supply shock; Supply and demand; Structural vector autoregression; International economics; Similarity (geometry); Vector autoregression; International trade; Monetary policy; Monetary economics; Macroeconomics","authors":[{"name":"Stanislav Kappel","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0596362512138521,"gpt":0.326839473170587,"spread":0.2672032219567348,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00203106,0.0001548036,0.0009438703,0.0001918394,0.00002697613,0.00001520395,0.0002073488,0.00006476135,0.0001424171],"category_scores_gemma":[0.0004105453,0.0001772853,0.0001138719,0.000120675,0.00008580274,0.0002837255,0.00005598303,0.00005686672,0.00002323008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003549933,"about_ca_system_score_gemma":0.0001876307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001109846,"about_ca_topic_score_gemma":0.000138652,"domain_scores_codex":[0.9984773,0.00006600412,0.0008984468,0.0003499825,0.00004066425,0.0001676177],"domain_scores_gemma":[0.9985961,0.00004378551,0.0006820157,0.0003341632,0.0002208242,0.0001231097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001216421,0.0003026882,0.4782146,0.002002217,0.0003247228,2.821595e-7,0.0079705,0.002283949,0.0002605727,0.4988649,0.00348332,0.006170596],"study_design_scores_gemma":[0.004197225,0.002132078,0.8531793,0.003780597,0.0005365196,0.0000234276,0.01396651,0.01129379,0.004312756,0.08881634,0.0159872,0.001774294],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9054146,0.08528769,0.00005061982,0.0002627551,0.0001077504,0.0004357941,0.0003764647,0.000006905456,0.008057463],"genre_scores_gemma":[0.9831817,0.01630856,0.0003395019,0.00005433192,0.00006708664,0.00001680953,0.0000120214,0.00001241574,0.000007637869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4100485,"threshold_uncertainty_score":0.7229486,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2061944853","doi":"10.2478/v10135-012-0014-6","title":"Job Differentiation vs. Unemployment","year":2013,"lang":"en","type":"article","venue":"Review of Economic Perspectives","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec en Outaouais; Université du Québec à Montréal","funders":"","keywords":"Comparative statics; Economics; Unemployment; Labour economics; Matching (statistics); Incentive; Productivity; Wage; Unemployment rate; Minimum wage; Microeconomics; Macroeconomics","authors":[{"name":"Samir Amine","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02131163997961645,"gpt":0.251335051763907,"spread":0.2300234117842906,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005059414,0.0001519268,0.0006329879,0.00009781105,0.00003844125,0.00003596074,0.0002201698,0.00004705279,0.004518039],"category_scores_gemma":[0.0001061232,0.000156737,0.0002187266,0.00007691709,0.00005663707,0.0002760045,0.00006067161,0.00007805345,0.0008134511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002805559,"about_ca_system_score_gemma":0.00002200749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000504091,"about_ca_topic_score_gemma":0.00001381368,"domain_scores_codex":[0.9985558,0.00003046042,0.0008349407,0.0003671281,0.00002320321,0.0001884442],"domain_scores_gemma":[0.9988747,0.00004803534,0.0005599804,0.0004001426,0.0000534092,0.00006378014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000003205001,0.00007548653,0.03887129,0.0009208396,0.0000943647,1.609879e-7,0.0002181693,0.000004920334,0.00001029931,0.9575184,0.001185841,0.001097012],"study_design_scores_gemma":[0.0009812324,0.0001806017,0.5087782,0.001829962,0.00004565902,0.000003936448,0.0004140904,0.003151241,0.00005580526,0.4596269,0.02399185,0.0009405511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7911798,0.1406919,0.0005421952,0.004775699,0.0004412473,0.0008848892,0.0002206841,0.00004388078,0.06121971],"genre_scores_gemma":[0.9103596,0.08839729,0.0002661046,0.0003010177,0.00007976434,0.00006871831,0.00001488142,0.00001772098,0.0004949567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4978915,"threshold_uncertainty_score":0.9999645,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}