{"meta":{"query_hash":"c2cc4082afed","filters":{"venue":"Research in Applied Economics"},"cohort_total":7,"direct_labels_cover":0,"predictions_cover":7,"exported":7,"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/c2cc4082afed","api":"https://metacan.xera.ac/api/v1/cohort?venue=Research+in+Applied+Economics"},"results":[{"id":"W1995702300","doi":"10.5296/rae.v5i2.3505","title":"The Incidence and Costs of Education-Occupation Mismatches in Canada: Evidence from Census Data","year":2013,"lang":"en","type":"article","venue":"Research in Applied Economics","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Carleton University","funders":"","keywords":"Census; Residence; Multinomial logistic regression; Earnings; Demographic economics; Incidence (geometry); Demography; Immigration; Foreign born; Multinomial distribution; Geography; Economics; Econometrics; Sociology; Statistics; Population; Mathematics","score_opus":0.11239675938755365,"score_gpt":0.386348263660652,"score_spread":0.27395150427309833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995702300","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":[0.98014885,0.0034967999,0.00051105476,0.0017408222,0.000020910325,0.00003548861,0.010249237,0.000018880135,0.0037778548],"genre_scores_gemma":[0.99205023,0.0026157994,0.00031942298,0.00010400304,0.000011478338,0.0000111314375,0.004212336,0.000006554909,0.0006689801],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954721,0.000741056,0.00043396163,0.00037599955,0.0023455403,0.0006313725],"domain_scores_gemma":[0.9728548,0.0066902614,0.011369961,0.0016882197,0.005994818,0.0014020066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026037064,0.00025519222,0.00035384655,0.0029637897,0.0015864166,0.0016589874,0.0013497736,0.00053506985,0.0022091875],"category_scores_gemma":[0.02824288,0.00035432333,0.0005194759,0.009013176,0.0013355667,0.0011054024,0.0018613002,0.00091325,0.00015873079],"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":[0.00006448855,0.000017169028,0.98734087,0.00007449271,0.00008256253,0.00007808862,0.0003914936,0.0006978,0.000022419776,0.0007481634,0.0012457094,0.009236765],"study_design_scores_gemma":[0.0000052192695,0.0000083195555,0.9955996,0.00006272655,0.000030303258,0.00006352044,0.0009121304,0.0011131916,0.000052244315,0.0002401637,0.0019006522,0.00001206344],"about_ca_topic_score_codex":0.9739612,"about_ca_topic_score_gemma":0.98581266,"teacher_disagreement_score":0.026038826,"about_ca_system_score_codex":0.014919106,"about_ca_system_score_gemma":0.014149154,"threshold_uncertainty_score":0.10824615},"labels":[],"label_agreement":null},{"id":"W2143859916","doi":"10.5296/rae.v7i4.8123","title":"The Analysis of External Debt Sustainability by Periodic Unit Root Test with Structural Break: The Case of Turkey","year":2015,"lang":"en","type":"article","venue":"Research in Applied Economics","topic":"Monetary Policy and Economic Impact","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":"Structural break; Unit root; Economics; Debt; Unit root test; Stock (firearms); Monetary economics; External debt; Sustainability; Debt ratio; Turkish economy; Quarter (Canadian coin); Turkish; Econometrics; Cointegration; Macroeconomics; Geography; Philosophy","score_opus":0.10076932081998845,"score_gpt":0.3183515379766133,"score_spread":0.21758221715662485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143859916","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":[0.99483347,0.00025892953,0.0028967734,0.0003166649,0.0000097780785,0.0000113828855,0.0001896104,0.000017207505,0.0014662117],"genre_scores_gemma":[0.9990497,0.00007390919,0.00047793257,0.000014309366,0.000008647855,0.000005191353,0.00018819669,0.0000051411043,0.00017697002],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897206,0.00036126663,0.00008635426,0.0002362248,0.00012647784,0.00021770352],"domain_scores_gemma":[0.99007684,0.0050127627,0.0032821512,0.00052995613,0.0007955296,0.00030273123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026775608,0.00037709757,0.0007157527,0.0013536466,0.0005175279,0.0012836276,0.000793981,0.0008889214,0.0022823666],"category_scores_gemma":[0.013105251,0.00022162993,0.00075509545,0.0017447028,0.00088827166,0.0014411885,0.00079452706,0.0011205017,0.00019574842],"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":[0.00047090615,0.00022298543,0.809496,0.00026222062,0.000536097,0.008244138,0.0010228893,0.0903611,0.0017098753,0.030623155,0.003818389,0.05323227],"study_design_scores_gemma":[0.00011640269,0.00045941648,0.5770387,0.0000906151,0.00038178664,0.0012811008,0.0038226026,0.38808852,0.0016908952,0.024151506,0.0028044921,0.00007400297],"about_ca_topic_score_codex":0.018482203,"about_ca_topic_score_gemma":0.008866141,"teacher_disagreement_score":0.018482203,"about_ca_system_score_codex":0.0011002163,"about_ca_system_score_gemma":0.000846675,"threshold_uncertainty_score":0.036749244},"labels":[],"label_agreement":null},{"id":"W2525600950","doi":"10.5296/rae.v8i3.10071","title":"The Compostable Coffee Pod: Is PürPod100tm the Best Thing Since Sliced Bread? A Case Study on Club Coffee","year":2016,"lang":"en","type":"article","venue":"Research in Applied Economics","topic":"Innovation and Socioeconomic Development","field":"Business, Management and Accounting","cited_by":2,"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 Regina","funders":"","keywords":"Club; Supply chain; Business; Distribution (mathematics); Sustainability; Agricultural science; Marketing; Mathematics; Environmental science","score_opus":0.10890785123848146,"score_gpt":0.33480393866075436,"score_spread":0.2258960874222729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2525600950","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":[0.9419448,0.00086090405,0.0016154518,0.0038477455,0.00008998639,0.00014892993,0.00016324651,0.000024464745,0.051304568],"genre_scores_gemma":[0.97592384,0.0009943438,0.0020672455,0.00039677185,0.000029015286,0.000032846536,0.00008755551,0.00003118323,0.020437207],"study_design_codex":"qualitative","study_design_gemma":"case_report","domain_scores_codex":[0.9990421,0.0004970546,0.000026311896,0.0000853406,0.0001420304,0.00020708349],"domain_scores_gemma":[0.99863356,0.00060709,0.00013503032,0.000059008726,0.00013462965,0.00043064155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011633935,0.00031448473,0.00026682238,0.00072840194,0.00820596,0.0025821505,0.0012129482,0.0017984324,0.0058774594],"category_scores_gemma":[0.0025634908,0.0002103186,0.00037351457,0.0014379546,0.0033298212,0.0015437742,0.001586138,0.0011395615,0.0004413444],"study_design_candidate":"case_report","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":[0.0010138982,0.002220557,0.054496855,0.0015014563,0.00007209271,0.2698156,0.44074196,0.003172358,0.01339624,0.06025717,0.03413497,0.119176894],"study_design_scores_gemma":[0.000025750764,0.00033749128,0.020006236,0.00035281072,0.000037990805,0.013163304,0.76096237,0.0018210717,0.005412551,0.0025307357,0.19528905,0.000060636114],"about_ca_topic_score_codex":0.04806794,"about_ca_topic_score_gemma":0.16475005,"teacher_disagreement_score":0.04806794,"about_ca_system_score_codex":0.005033049,"about_ca_system_score_gemma":0.0026383721,"threshold_uncertainty_score":0.09557629},"labels":[],"label_agreement":null},{"id":"W2605177464","doi":"10.5296/rae.v9i1.10900","title":"Who Really Benefits from Mandatory Adoption of IFRS? A Closer Look at Preparers and Users of Financial Information","year":2017,"lang":"en","type":"article","venue":"Research in Applied Economics","topic":"Auditing, Earnings Management, Governance","field":"Business, Management and Accounting","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":"HEC Montréal; Université du Québec à Montréal","funders":"","keywords":"Business; Accounting; Creditor; International Financial Reporting Standards; Capital market; Accounting information system; Sample (material); Earnings; Notice; European union; Finance; Debt","score_opus":0.02555718530014444,"score_gpt":0.25375181821977943,"score_spread":0.228194632919635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605177464","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":[0.98136544,0.0009979577,0.00018897468,0.009260846,0.00003386133,0.000017222994,0.00031004747,0.000010122192,0.007815519],"genre_scores_gemma":[0.99846303,0.00024941048,0.00006219209,0.0003528631,0.000056324025,0.0000040320597,0.00011489124,0.0000032440623,0.0006940823],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9956702,0.0013730781,0.00026161256,0.0003270173,0.0011235107,0.0012446024],"domain_scores_gemma":[0.93706304,0.024368575,0.028869737,0.0020033338,0.0031656967,0.004529763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043243947,0.000110474364,0.00026599586,0.001041629,0.00047348856,0.0021236644,0.00047102326,0.00086914876,0.005530917],"category_scores_gemma":[0.033254374,0.00014410712,0.00043517214,0.0012622386,0.00084743125,0.0033245066,0.0012563147,0.0014233685,0.00041174036],"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":[0.000244996,0.00031897606,0.92666185,0.00009105159,0.00006146428,0.0007368293,0.002195598,0.00023829765,0.0005403281,0.0037444679,0.0032004162,0.061965648],"study_design_scores_gemma":[0.000010268912,0.00013954756,0.9851424,0.000083851875,0.000038831866,0.00024319942,0.005148804,0.00028427577,0.000474219,0.0010343054,0.00738483,0.000015378035],"about_ca_topic_score_codex":0.0068370234,"about_ca_topic_score_gemma":0.009264384,"teacher_disagreement_score":0.0068370234,"about_ca_system_score_codex":0.001101364,"about_ca_system_score_gemma":0.0015152834,"threshold_uncertainty_score":0.022869825},"labels":[],"label_agreement":null},{"id":"W2896962570","doi":"10.5296/rae.v10i3.13223","title":"Monetary Policy Behaviour over the Long Run in a Small Open Economy: A Markov-Switching Vector Error-Correction Approach","year":2018,"lang":"en","type":"article","venue":"Research in Applied Economics","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":"Laurentian University","funders":"","keywords":"Economics; Monetary policy; Markov chain; Inflation (cosmology); Econometrics; Error correction model; Weighting; Variance (accounting); Monetary economics; Cointegration; Statistics; Mathematics","score_opus":0.16605064452508975,"score_gpt":0.33009180884737127,"score_spread":0.16404116432228152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896962570","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":[0.7267295,0.00049627334,0.26647052,0.0012905207,0.00008141389,0.00004804423,0.00025998734,0.00019595773,0.0044278046],"genre_scores_gemma":[0.9920922,0.000349787,0.0043017524,0.00003893341,0.000029011155,0.000022952492,0.00012670005,0.000017613262,0.0030210041],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994205,0.00020496684,0.00002807865,0.00011870628,0.000094826464,0.00013292408],"domain_scores_gemma":[0.99560577,0.0029529529,0.000708361,0.00016192146,0.00038974645,0.00018122655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019795708,0.0004681946,0.0010393838,0.00090887235,0.0008351511,0.0018085015,0.0013097373,0.0011127674,0.0023535932],"category_scores_gemma":[0.009207134,0.0005620037,0.0009639945,0.0007202461,0.0014088261,0.0014091067,0.00095101714,0.001358055,0.00019646625],"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":[0.00012093971,0.00006387527,0.011905497,0.0000434941,0.00013485138,0.00028049745,0.00025496457,0.9006123,0.0009099122,0.07915479,0.0005018789,0.006017018],"study_design_scores_gemma":[0.000007673019,0.000010075534,0.0011398408,0.000004796001,0.00001814584,0.000010170064,0.000022091144,0.9904343,0.00007567555,0.008159141,0.00010596601,0.00001223644],"about_ca_topic_score_codex":0.13008189,"about_ca_topic_score_gemma":0.07854221,"teacher_disagreement_score":0.13008189,"about_ca_system_score_codex":0.0025369762,"about_ca_system_score_gemma":0.003032574,"threshold_uncertainty_score":0.25864947},"labels":[],"label_agreement":null},{"id":"W2929212771","doi":"10.5296/rae.v11i1.13826","title":"Do Oil Price Shocks Affect Household Consumption?","year":2019,"lang":"en","type":"article","venue":"Research in Applied Economics","topic":"Market Dynamics and Volatility","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":"Sveriges Regering; Lunds Universitet","keywords":"Oil price; Economics; Variance decomposition of forecast errors; Consumption (sociology); Econometrics; Distributed lag; Variance (accounting); Oil consumption; Crude oil; Macroeconomics; Monetary economics","score_opus":0.11158386238237486,"score_gpt":0.3112134496345696,"score_spread":0.19962958725219473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2929212771","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":[0.9915097,0.001128451,0.00032616832,0.0013785827,0.00004076223,0.000009024848,0.0015545416,0.000008839815,0.0040438445],"genre_scores_gemma":[0.99789125,0.0004958939,0.000039169685,0.00008188771,0.00002333439,0.0000026732314,0.000660594,0.0000024334154,0.0008028453],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997819,0.00005719202,0.000013641847,0.000042078875,0.0000305316,0.000074748976],"domain_scores_gemma":[0.99810874,0.000938564,0.00057287974,0.00011938164,0.00012840533,0.0001320404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003215012,0.00014455081,0.00028655806,0.00048238348,0.00012989488,0.000781305,0.00019175574,0.0006062225,0.0050479663],"category_scores_gemma":[0.0029827992,0.00012324147,0.000443582,0.0014122725,0.00026565394,0.0006792817,0.00028750626,0.00049666426,0.0005703274],"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":[0.00017152107,0.00007153835,0.9880874,0.00003416484,0.00019464524,0.00014027889,0.00026025236,0.00055295316,0.00014880112,0.0008152665,0.0008575826,0.008665631],"study_design_scores_gemma":[0.000003807366,0.00003424614,0.9958943,0.000015317792,0.00005396951,0.000042192423,0.0007915038,0.0009254799,0.00013834587,0.0007380515,0.001356904,0.0000059246245],"about_ca_topic_score_codex":0.017981922,"about_ca_topic_score_gemma":0.016571708,"teacher_disagreement_score":0.017981922,"about_ca_system_score_codex":0.00045898443,"about_ca_system_score_gemma":0.0002204369,"threshold_uncertainty_score":0.0357545},"labels":[],"label_agreement":null},{"id":"W4311964898","doi":"10.5296/rae.v14i2.20560","title":"Impact Analysis of Pandemic on Nigeria’s Stock Market Performance","year":2022,"lang":"en","type":"article","venue":"Research in Applied Economics","topic":"COVID-19 Pandemic Impacts","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":"University of Lethbridge","funders":"","keywords":"Stock market; Pandemic; Coronavirus disease 2019 (COVID-19); Stock (firearms); Economics; Stock market index; Business; Financial economics; Distributed lag; Econometrics; Monetary economics; Geography","score_opus":0.1323608243901826,"score_gpt":0.35667921688563636,"score_spread":0.22431839249545377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311964898","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":[0.9966893,0.00018672903,0.00035899135,0.0001283873,0.000008298051,0.00001762174,0.00033097423,0.0000048070565,0.0022748406],"genre_scores_gemma":[0.9991629,0.00011915199,0.0001418874,0.000013951716,0.000008273035,0.000006254804,0.0002631778,6.6851146e-7,0.0002837368],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996551,0.00007541029,0.0000454743,0.00005292001,0.00010766461,0.00006344227],"domain_scores_gemma":[0.99736243,0.0010618517,0.0009451102,0.00009980264,0.00039258215,0.00013819034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012328599,0.0002880089,0.0002414675,0.00077759154,0.00018172055,0.0008609905,0.00018668907,0.00032598327,0.0013747469],"category_scores_gemma":[0.004037493,0.00008932957,0.00032731707,0.0006721516,0.00023867933,0.0010688575,0.00034512285,0.00051602506,0.00013229201],"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":[0.00015284475,0.0001580448,0.9727606,0.00006651742,0.00010740647,0.00043198455,0.0002629902,0.008543777,0.0011880045,0.0019492399,0.000500123,0.013878384],"study_design_scores_gemma":[0.000010500383,0.00041404835,0.96103704,0.000038225473,0.000083646475,0.00012861394,0.00083050807,0.033376496,0.0017459937,0.0010747353,0.0012358336,0.000024407254],"about_ca_topic_score_codex":0.004732736,"about_ca_topic_score_gemma":0.0046741073,"teacher_disagreement_score":0.004732736,"about_ca_system_score_codex":0.0005987184,"about_ca_system_score_gemma":0.00041971952,"threshold_uncertainty_score":0.009410381},"labels":[],"label_agreement":null}]}