{"meta":{"query_hash":"71d66566fd60","filters":{"venue":"Empirical Economics"},"cohort_total":107,"direct_labels_cover":0,"predictions_cover":107,"exported":107,"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/71d66566fd60","api":"https://metacan.xera.ac/api/v1/cohort?venue=Empirical+Economics"},"results":[{"id":"W1495085825","doi":"10.1007/s00181-014-0880-0","title":"Taxes, wages and working hours","year":2014,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for International Peace and Security","funders":"Riksbankens Jubileumsfond; Ragnar Söderbergs stiftelse","keywords":"Economics; Taxable income; Endogeneity; Econometrics; Hourly wage; Microsimulation; Wage; Panel Study of Income Dynamics; Panel data; Tax rate; Labour economics; Demographic economics; Percentage point; Macroeconomics","score_opus":0.04340689920841022,"score_gpt":0.2964219595051713,"score_spread":0.2530150602967611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1495085825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93699497,0.00011062281,0.0006198127,0.002362617,0.00044834692,0.000066954584,0.000004707208,0.000053700755,0.059338268],"genre_scores_gemma":[0.9949458,0.00062751886,0.0010448183,0.0019715952,0.00047802491,0.0000031047978,0.0000028849834,0.000012251409,0.0009139997],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99920684,0.00008114359,0.00014756642,0.00022114468,0.00005499407,0.00028828764],"domain_scores_gemma":[0.9994423,0.0001838153,0.000055977922,0.00013018186,0.00001661913,0.00017110117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048681596,0.00008904723,0.0001502724,0.000037165722,0.0002954242,0.00012101716,0.00015870774,0.000120927914,0.000028897435],"category_scores_gemma":[0.00011935445,0.00009312584,0.00004017113,0.00007160144,0.00020499622,0.00009343172,0.000050640247,0.00011097637,0.00003704358],"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":[0.0000055169257,0.00003186857,0.8808708,0.000004279814,0.000017866534,8.750095e-7,0.0092341555,0.00016909865,0.0000029054618,0.07473518,0.0041101007,0.030817354],"study_design_scores_gemma":[0.00033761692,0.000040195686,0.28707397,0.000009105509,0.000016094122,0.0000011875746,0.0052735046,0.002720917,0.0000029390426,0.030774979,0.67340785,0.00034163942],"about_ca_topic_score_codex":0.00029350095,"about_ca_topic_score_gemma":0.0017301609,"teacher_disagreement_score":0.66929775,"about_ca_system_score_codex":0.00007021037,"about_ca_system_score_gemma":0.00007090061,"threshold_uncertainty_score":0.37975618},"labels":[],"label_agreement":null},{"id":"W1581051415","doi":"10.1007/s00181-003-0172-6","title":"An empirical note about additive outliers and nonstationarity in Latin-American inflation series","year":2004,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":16,"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 Ottawa","funders":"","keywords":"Series (stratigraphy); Outlier; Econometrics; Inflation (cosmology); Economics; Latin Americans; Statistics; Mathematics; Geology; Physics; Philosophy; Theoretical physics","score_opus":0.057744107095501374,"score_gpt":0.2959194010845525,"score_spread":0.23817529398905113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581051415","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988806,0.00007813441,0.0015271822,0.0043776142,0.00017077298,0.0002305408,0.0005065297,0.0000479226,0.004255314],"genre_scores_gemma":[0.991424,0.00028506434,0.005051545,0.0027795339,0.0001838486,0.000025200377,0.00013681868,0.00003468809,0.00007928528],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99789494,0.000031576652,0.0009190778,0.0006621122,0.000021242091,0.0004710492],"domain_scores_gemma":[0.99885935,0.000113223476,0.00040354618,0.00033074184,0.000011558998,0.00028159528],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00042142515,0.000268147,0.0006150098,0.00033612855,0.00014361521,0.00013436799,0.00018035874,0.0001666839,0.00017261099],"category_scores_gemma":[0.00013819907,0.0003410742,0.000092042326,0.0001830374,0.0003349148,0.0011114032,0.000054232598,0.00030061754,0.00031165118],"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":[0.00016121277,0.0002183996,0.89145005,0.000012737369,0.000042218566,0.0000068239556,0.00623078,0.0683096,0.000002816067,0.027905373,0.0003242524,0.0053357435],"study_design_scores_gemma":[0.001239475,0.00027860553,0.87627923,0.000008187758,0.000005342067,0.000009601121,0.00031378286,0.033261582,0.000023622015,0.07420513,0.013866444,0.0005090006],"about_ca_topic_score_codex":0.0014670762,"about_ca_topic_score_gemma":0.001332112,"teacher_disagreement_score":0.04629976,"about_ca_system_score_codex":0.00050356507,"about_ca_system_score_gemma":0.00007914324,"threshold_uncertainty_score":0.99990416},"labels":[],"label_agreement":null},{"id":"W1965254116","doi":"10.1007/s00181-005-0035-4","title":"Testing the permanent-income hypothesis: new evidence from West-German states (Länder)","year":2006,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":33,"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 Waterloo","funders":"","keywords":"Economics; Permanent income hypothesis; German; Consumption (sociology); Empirical evidence; Econometrics; West germany; Market liquidity; Monetary economics; Geography","score_opus":0.10778290185039557,"score_gpt":0.26209868921831436,"score_spread":0.1543157873679188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965254116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97417927,0.0029361572,0.0014276176,0.007103684,0.00062105316,0.00026932172,0.00025060817,0.000118137745,0.013094159],"genre_scores_gemma":[0.99045074,0.00036315958,0.0036186317,0.0018561019,0.001250208,0.000028961367,0.00003283192,0.00007827002,0.002321113],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997295,0.000032401793,0.0012295039,0.00080382056,0.000028293138,0.0006109785],"domain_scores_gemma":[0.9969711,0.0013938809,0.0005923432,0.0008265095,0.000024996081,0.00019118967],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005831543,0.00034948904,0.00063698407,0.000111268404,0.00028660626,0.00035343197,0.0007863344,0.00016728323,0.0008420282],"category_scores_gemma":[0.0002314499,0.0003360611,0.0002123873,0.00014138619,0.00016117122,0.0005859315,0.00022013269,0.00028733065,0.0026994268],"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":[0.00014432103,0.00026368603,0.56502783,0.00005165717,0.00034466563,0.000018325123,0.0032905159,0.029494846,0.0000781393,0.3570363,0.033136148,0.011113552],"study_design_scores_gemma":[0.00051861414,0.000057618945,0.17864628,0.000037241774,0.000021696378,0.000008937059,0.00010484106,0.016134538,0.00008477949,0.74809396,0.055675477,0.00061602955],"about_ca_topic_score_codex":0.005689894,"about_ca_topic_score_gemma":0.00047395338,"teacher_disagreement_score":0.39105764,"about_ca_system_score_codex":0.00031831325,"about_ca_system_score_gemma":0.00010022249,"threshold_uncertainty_score":0.99990916},"labels":[],"label_agreement":null},{"id":"W1966905321","doi":"10.1007/s00181-012-0608-y","title":"Generalized measures of wage differentials","year":2012,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for International Peace and Security","funders":"","keywords":"Economics; Wage; Wage dispersion; Disadvantage; Econometrics; Inequality; Distribution (mathematics); Wage inequality; Compensating differential; Dispersion (optics); Risk aversion (psychology); Labour economics; Efficiency wage; Expected utility hypothesis; Wage share; Mathematics; Financial economics","score_opus":0.11699227436937486,"score_gpt":0.28470677871848843,"score_spread":0.16771450434911356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966905321","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98355156,0.0008496877,0.0022860547,0.0006328026,0.0008168385,0.00012960483,0.0003202457,0.00002947553,0.011383704],"genre_scores_gemma":[0.9973623,0.0002963569,0.001072759,0.0005405648,0.0002782737,0.000012771253,0.000028687247,0.000031355266,0.0003768958],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99821764,0.000042301173,0.0010032991,0.00028735853,0.000026245858,0.0004231745],"domain_scores_gemma":[0.99876857,0.00010013241,0.00046748217,0.00044497792,0.000029227429,0.00018963547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010898556,0.00018269247,0.0006573312,0.00012747826,0.0000544306,0.000036986505,0.00026338897,0.0001509023,0.000625063],"category_scores_gemma":[0.00017472696,0.00019585987,0.00023560323,0.00011506649,0.00007593897,0.0002470856,0.00010633869,0.00012116081,0.00019815007],"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":[0.000022516164,0.00017570355,0.3361235,0.000014020455,0.000073769916,2.0947603e-7,0.00019158535,0.000038375692,0.000028332921,0.66229564,0.00031254452,0.0007238059],"study_design_scores_gemma":[0.0016880638,0.0000795507,0.38083035,0.000010706644,0.000029989642,0.000004286287,0.00003746182,0.0023662522,0.0009173452,0.39727646,0.21585618,0.0009033546],"about_ca_topic_score_codex":0.00015653814,"about_ca_topic_score_gemma":0.000018458957,"teacher_disagreement_score":0.26501918,"about_ca_system_score_codex":0.00010555897,"about_ca_system_score_gemma":0.000019013614,"threshold_uncertainty_score":0.79869336},"labels":[],"label_agreement":null},{"id":"W1968044898","doi":"10.1007/s00181-010-0411-6","title":"Instrumental variable estimation of a nonlinear Taylor rule","year":2010,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Instrumental variable; Nonlinear system; Estimation; Taylor series; Inflation (cosmology); Econometrics; Series (stratigraphy); Variable (mathematics); Applied mathematics; Taylor rule; Mathematics; Economics; Computer science; Monetary policy; Keynesian economics; Mathematical analysis","score_opus":0.05291409403162019,"score_gpt":0.2560837444267851,"score_spread":0.20316965039516494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968044898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97247314,0.000036194244,0.0016465364,0.00070787733,0.00077679363,0.00014673462,0.0004814751,0.00003176419,0.023699453],"genre_scores_gemma":[0.968522,0.000020416057,0.03006024,0.0007021022,0.0002380516,0.0000107461265,0.000074853,0.000029019688,0.00034253436],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983779,0.0000070907754,0.0008997087,0.0003699422,0.000013724998,0.00033164283],"domain_scores_gemma":[0.99891156,0.00006809466,0.00042946465,0.00042237042,0.0000071272307,0.00016138604],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004277301,0.00017858867,0.0004906962,0.00017900426,0.00007637146,0.000052932188,0.0002706501,0.00019070205,0.0024234771],"category_scores_gemma":[0.00012372923,0.00021987058,0.00014073144,0.00009323277,0.00011094655,0.00043451594,0.000076053715,0.00026702075,0.0012339132],"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":[0.00032234195,0.0015942203,0.31157213,0.00021264283,0.0005061263,0.000004458558,0.002090021,0.13999663,0.00072377146,0.506641,0.009098484,0.027238173],"study_design_scores_gemma":[0.0011203758,0.00011880045,0.009810196,0.0000046150594,0.000010530212,0.0000209969,0.000028103335,0.83439463,0.0010842106,0.088169776,0.0647832,0.00045457156],"about_ca_topic_score_codex":0.00037147503,"about_ca_topic_score_gemma":0.000025696661,"teacher_disagreement_score":0.694398,"about_ca_system_score_codex":0.000076902106,"about_ca_system_score_gemma":0.000031640444,"threshold_uncertainty_score":0.9995437},"labels":[],"label_agreement":null},{"id":"W1969688870","doi":"10.1007/s00181-007-0164-z","title":"The absolute health income hypothesis revisited: a semiparametric quantile regression approach","year":2007,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Global Health Care Issues","field":"Health Professions","cited_by":6,"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 Guelph","funders":"","keywords":"Quantile regression; Econometrics; Semiparametric regression; Economics; Quantile; Population; Regression; Semiparametric model; Population health; Statistics; Mathematics; Demography; Nonparametric statistics","score_opus":0.12620460095613686,"score_gpt":0.460090332587219,"score_spread":0.33388573163108215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969688870","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9105176,0.008046328,0.0012285813,0.01968607,0.0023549376,0.002827879,0.00009381583,0.0004799533,0.054764856],"genre_scores_gemma":[0.9479599,0.005578282,0.013812768,0.02588469,0.0016966867,0.00014363215,0.00005279974,0.00015669533,0.0047145328],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9949156,0.00072798494,0.0017901885,0.000646358,0.00024446697,0.0016754166],"domain_scores_gemma":[0.9917349,0.005480948,0.00089886796,0.0010057668,0.0001538377,0.0007256853],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0063770316,0.00032737464,0.00073511957,0.00025940457,0.0022019213,0.000041236486,0.0006344901,0.00043783532,0.000089396446],"category_scores_gemma":[0.0014488363,0.0002269245,0.00018133872,0.0008142367,0.00014965114,0.00014803385,0.00032247248,0.0011853777,0.0018350811],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009030921,0.0003950899,0.16296713,0.0012096935,0.0001239632,0.000014837048,0.005181265,0.0001089816,0.0000033290332,0.017087696,0.7317996,0.08020534],"study_design_scores_gemma":[0.00073478033,0.00018085797,0.21361886,0.00023980066,0.000013976522,0.000010521286,0.0022822055,0.00161214,0.0000053996023,0.0027077184,0.77823454,0.00035921353],"about_ca_topic_score_codex":0.0004563625,"about_ca_topic_score_gemma":0.00037047287,"teacher_disagreement_score":0.07984613,"about_ca_system_score_codex":0.0016771022,"about_ca_system_score_gemma":0.0007270167,"threshold_uncertainty_score":0.99909705},"labels":[],"label_agreement":null},{"id":"W1971510606","doi":"10.1007/s001810000022","title":"Institutional specifics and unemployment insurance eligibility in Canada: How sensitive are employment duration effects?","year":2000,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Entitlement (fair division); Unemployment; Duration (music); Economics; Hazard; Jump; Demographic economics; Econometrics; Labour economics; Actuarial science; Macroeconomics; Microeconomics","score_opus":0.026477161357425866,"score_gpt":0.23452396270266967,"score_spread":0.2080468013452438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971510606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.991047,0.0002862539,0.00017221548,0.004796356,0.0003224141,0.00032318276,0.0006045369,0.000017176832,0.002430818],"genre_scores_gemma":[0.9972349,0.00094271376,0.0002081078,0.0012804777,0.00008944587,0.000025568173,0.00004280623,0.000017547522,0.00015843907],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99819815,0.000050842085,0.00073054543,0.0006417113,0.00004323726,0.00033549982],"domain_scores_gemma":[0.99909824,0.00015735858,0.00025663464,0.00031018292,0.000027735716,0.00014984171],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00052575103,0.00022610067,0.0005243589,0.00008182667,0.00010676146,0.00009550161,0.0001244563,0.000103631945,0.000102227714],"category_scores_gemma":[0.00010856033,0.00026602467,0.000062370746,0.00015841553,0.00008666895,0.00025764338,0.000051785133,0.00021616918,0.00003451596],"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":[0.00006512894,0.00010667688,0.9573308,0.00003082899,0.00003090945,0.000024949823,0.000111190355,0.0019071051,0.0000010899204,0.036005195,0.00017876741,0.0042073503],"study_design_scores_gemma":[0.00074954506,0.000031598756,0.9492766,0.00001769326,0.0000024863098,0.0000056337562,0.000030466892,0.008786943,0.000034392382,0.024686892,0.016037049,0.0003406583],"about_ca_topic_score_codex":0.1284211,"about_ca_topic_score_gemma":0.50855666,"teacher_disagreement_score":0.38013557,"about_ca_system_score_codex":0.0019089829,"about_ca_system_score_gemma":0.0002539586,"threshold_uncertainty_score":0.9999792},"labels":[],"label_agreement":null},{"id":"W1974685101","doi":"10.1007/s001810200135","title":"Model selection when estimating and predicting consumer demands using international, cross section data","year":2003,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":94,"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 Guelph","funders":"","keywords":"Almost ideal demand system; Economics; Econometrics; Cross-sectional data; Quadratic equation; Per capita; Engel curve; Consumer Expenditure Survey; Quadratic model; Consumer demand; Per capita income; Selection (genetic algorithm); Microeconomics; Demand management; Public economics; Mathematics; Macroeconomics; Aggregate expenditure; Statistics; Computer science; Price index","score_opus":0.13659964099292377,"score_gpt":0.3124181014488863,"score_spread":0.17581846045596256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974685101","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93153644,0.0004687136,0.047847237,0.0002764961,0.0012902258,0.00017063686,0.00018511675,0.00006664993,0.018158482],"genre_scores_gemma":[0.8707199,0.00015757496,0.12764083,0.00050805014,0.0004559535,0.000009430687,0.00008822305,0.000039667906,0.00038036794],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981649,0.000016928978,0.00076249434,0.0007450375,0.000019531131,0.00029111066],"domain_scores_gemma":[0.9989739,0.00008527647,0.00044191175,0.0003367656,0.000038786613,0.00012335795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008406073,0.00020271295,0.00034575784,0.00014109311,0.00025517517,0.00033862825,0.00029713378,0.00019978244,0.00010619182],"category_scores_gemma":[0.00031725975,0.00024222632,0.00006100025,0.00006578147,0.00006643341,0.001204906,0.00019074303,0.00023790238,0.000030666313],"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":[0.000032781627,0.000112814225,0.86061007,0.000035334466,0.0002745716,9.611537e-7,0.00047079095,0.0739375,0.000037078895,0.060840726,0.0029942559,0.0006531101],"study_design_scores_gemma":[0.00051058386,0.000019276453,0.004814536,0.000008548479,0.00001411059,0.000043505395,0.000033255394,0.92459005,0.000021674747,0.052840855,0.016808778,0.0002948],"about_ca_topic_score_codex":0.000054388194,"about_ca_topic_score_gemma":0.00005916534,"teacher_disagreement_score":0.85579556,"about_ca_system_score_codex":0.00021638318,"about_ca_system_score_gemma":0.000045362558,"threshold_uncertainty_score":0.98777026},"labels":[],"label_agreement":null},{"id":"W1975114548","doi":"10.1007/s00181-014-0851-5","title":"Identifying extreme values of exchange market pressure","year":2014,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Econometrics; Estimator; Extreme value theory; Currency; Variance (accounting); Monte Carlo method; Sample (material); Identification (biology); Series (stratigraphy); Economics; Bias of an estimator; Computer science; Statistics; Mathematics; Minimum-variance unbiased estimator; Geology","score_opus":0.1854920964997817,"score_gpt":0.2761966124626359,"score_spread":0.09070451596285417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975114548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8088096,0.0023735662,0.00654536,0.0015328119,0.0010798668,0.00028038735,0.00037933624,0.00007890465,0.17892016],"genre_scores_gemma":[0.98990273,0.00039999007,0.0016388076,0.0010096594,0.00044541564,0.000012662705,0.000017761546,0.000044519198,0.0065284716],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979136,0.00004078548,0.0010345918,0.00053724064,0.000019738323,0.00045406877],"domain_scores_gemma":[0.99843836,0.00016867675,0.00058370014,0.0006157679,0.000010153085,0.00018335965],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0010798426,0.00023638167,0.00074005104,0.0002444584,0.000089721194,0.000070230344,0.00041255273,0.00018395802,0.0044662673],"category_scores_gemma":[0.00017882549,0.00028904437,0.00025980952,0.000084128485,0.0001121453,0.0004148202,0.00013316375,0.00016796733,0.0007829516],"study_design_candidate":"not_applicable","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":[0.00032800186,0.00068337296,0.5532097,0.00095081027,0.0010271427,0.0000037514199,0.0057147476,0.016209617,0.000043382228,0.15745135,0.24914062,0.015237499],"study_design_scores_gemma":[0.0010594584,0.00014267159,0.06372102,0.00002264143,0.00003072437,0.000009010061,0.000050196744,0.19912508,0.00016986608,0.1540765,0.5809463,0.00064648344],"about_ca_topic_score_codex":0.00021602075,"about_ca_topic_score_gemma":0.00001873034,"teacher_disagreement_score":0.48948866,"about_ca_system_score_codex":0.0000682105,"about_ca_system_score_gemma":0.000012592022,"threshold_uncertainty_score":0.99999505},"labels":[],"label_agreement":null},{"id":"W1976944923","doi":"10.1007/s001810200131","title":"Statistical analysis of inequality with decompositions: the Canadian experience","year":2003,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Inequality; Economics; Theil index; Bootstrapping (finance); Marital status; Econometrics; Income inequality metrics; Economic inequality; Demographic economics; Recession; Statistical inference; Mathematics; Statistics; Demography; Sociology; Macroeconomics","score_opus":0.06939110167235789,"score_gpt":0.3719216118336345,"score_spread":0.3025305101612766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976944923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.935239,0.000018163073,0.0021615769,0.0018437549,0.00009499512,0.000114520015,0.0001069156,0.000010875942,0.060410187],"genre_scores_gemma":[0.99713266,0.000015013771,0.0010021382,0.0017188396,0.000029623905,0.0000104434175,0.000012966662,0.0000039805745,0.00007434109],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9987681,0.0003699964,0.00029516566,0.00017911456,0.00011490407,0.0002727523],"domain_scores_gemma":[0.9989057,0.0004523592,0.00009288589,0.000243155,0.00007979917,0.00022607706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093915605,0.00007585982,0.00022866316,0.00008417892,0.00057472434,0.000064854816,0.00020913385,0.0000700999,0.00073465845],"category_scores_gemma":[0.00036391782,0.00005515948,0.00006993114,0.00044975718,0.00057439966,0.00011153522,0.000010308343,0.00009969926,0.000012328874],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009778086,0.000048743288,0.4562293,0.0000018436706,0.00012125936,0.0000010311926,0.011356825,0.00034665628,3.414113e-7,0.5311953,0.0005063984,0.00018255459],"study_design_scores_gemma":[0.00032707932,0.00010113325,0.76351774,0.00000481608,0.00033539234,0.0000011174284,0.011941238,0.0018013805,0.000053861953,0.016829042,0.2046668,0.0004204021],"about_ca_topic_score_codex":0.2474202,"about_ca_topic_score_gemma":0.86591107,"teacher_disagreement_score":0.6184909,"about_ca_system_score_codex":0.00034947594,"about_ca_system_score_gemma":0.0008233777,"threshold_uncertainty_score":0.8043995},"labels":[],"label_agreement":null},{"id":"W1978975824","doi":"10.1007/s001810100108","title":"Specification and sensitivity analysis of cross-country growth regressions","year":2002,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":8,"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 Guelph","funders":"","keywords":"Econometrics; Inflation (cosmology); Sensitivity (control systems); Standard deviation; Economics; Regression analysis; Regression; Statistics; Mathematics; Engineering","score_opus":0.07487940840141641,"score_gpt":0.27514276374878494,"score_spread":0.20026335534736853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978975824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97004426,0.00073898624,0.00068798236,0.0013074327,0.00022312789,0.00010688998,0.0004336269,0.000027121712,0.026430553],"genre_scores_gemma":[0.99782324,0.0008048634,0.00045508362,0.0003157031,0.00012086614,0.0000059330255,0.000034187608,0.000017338107,0.00042277022],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99830496,0.000027537562,0.0007711871,0.000626458,0.000016317821,0.0002535349],"domain_scores_gemma":[0.99861866,0.00020780214,0.0005134579,0.000477609,0.000041434,0.00014105925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007128603,0.00016827574,0.00068623194,0.0004135401,0.000113618065,0.00007912877,0.00010129704,0.00015304073,0.0006343511],"category_scores_gemma":[0.00030104604,0.00020258121,0.00017894733,0.00043569267,0.00023906915,0.0004278967,0.00007600361,0.00016122498,0.00016697681],"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":[0.0000132917485,0.000108193926,0.90771204,0.000015244767,0.0002732651,0.0000011919967,0.00022888558,0.0003381855,0.000011549718,0.090089634,0.00070748816,0.0005010174],"study_design_scores_gemma":[0.00034712465,0.00003199016,0.90673304,0.0000032517974,0.00007223332,0.0000062343406,0.000018496808,0.0603005,0.00014919363,0.020332191,0.0116916485,0.0003141068],"about_ca_topic_score_codex":0.00014294816,"about_ca_topic_score_gemma":0.00007686134,"teacher_disagreement_score":0.06975744,"about_ca_system_score_codex":0.00009641882,"about_ca_system_score_gemma":0.000008757357,"threshold_uncertainty_score":0.8261022},"labels":[],"label_agreement":null},{"id":"W1984271971","doi":"10.1007/s001810000030","title":"Bank acquisitions of investment dealers: Canadian evidence and implications for Glass-Steagall reform","year":2000,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Underwriting; Investment banking; Business; Scope (computer science); Legislation; Equity (law); Economies of scope; Investment (military); Regulatory reform; Financial system; Commercial banking; Finance; Economics; Accounting; Monetary economics; Market economy; Economies of scale; Marketing","score_opus":0.06878774779415714,"score_gpt":0.2877531205908746,"score_spread":0.21896537279671746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984271971","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.968982,0.0012394222,0.00047819052,0.010573905,0.00009871928,0.0005322496,0.0007615748,0.000025472991,0.017308488],"genre_scores_gemma":[0.99473375,0.00042857954,0.002836981,0.0014626613,0.00006434831,0.00008796944,0.000042484546,0.000021623111,0.0003216094],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99844503,0.000010981313,0.0007488546,0.00046157115,0.00001360207,0.00031993366],"domain_scores_gemma":[0.99886686,0.00017509033,0.0002098541,0.00048125078,0.000048840946,0.00021812251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000491288,0.00013842697,0.0003257615,0.00019240787,0.00019172933,0.000055970624,0.00023152858,0.00012676413,0.00044611093],"category_scores_gemma":[0.00012191251,0.00016997087,0.00010602583,0.00017004488,0.00017303207,0.0003038562,0.00002659401,0.000072035196,0.00006728421],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021807182,0.00017099256,0.22037886,0.00006931125,0.000056879217,1.2961034e-7,0.00080430653,0.0014748069,0.000005035826,0.766778,0.0014726612,0.008767201],"study_design_scores_gemma":[0.00032026292,0.000108370354,0.7668334,0.000017915005,0.000011123657,0.0000042507063,0.000028077426,0.004933086,0.00001534014,0.16342972,0.064048685,0.000249736],"about_ca_topic_score_codex":0.008550578,"about_ca_topic_score_gemma":0.015078489,"teacher_disagreement_score":0.60334826,"about_ca_system_score_codex":0.00083982974,"about_ca_system_score_gemma":0.00017834644,"threshold_uncertainty_score":0.9980516},"labels":[],"label_agreement":null},{"id":"W1985756507","doi":"10.1007/s00181-005-0032-7","title":"Are some taxes different than others? An empirical investigation of the effects of tax policy in Canada","year":2006,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; Tax policy; Value-added tax; Variation (astronomy); Affect (linguistics); Indirect tax; Tax reform; Monetary economics; Econometrics; Public economics; Sign (mathematics); Macroeconomics","score_opus":0.02715155823967159,"score_gpt":0.22983835926813434,"score_spread":0.20268680102846276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985756507","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99349475,0.0001740047,0.000008972819,0.0035230578,0.0003443386,0.00024035882,0.00037019045,0.000007847859,0.0018364801],"genre_scores_gemma":[0.997612,0.000015285977,0.000030215977,0.0018999199,0.00027985856,0.000018922183,0.000011087021,0.00003010889,0.00010262669],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980125,0.000058052585,0.0011210182,0.0004017586,0.000032040403,0.00037466487],"domain_scores_gemma":[0.99812233,0.00021406046,0.0010478776,0.00047914236,0.000011144765,0.00012541177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001918046,0.0002286981,0.0007181518,0.00022468623,0.000052144238,0.000021471922,0.0004390733,0.0001483287,0.000015412626],"category_scores_gemma":[0.00019033242,0.00021281373,0.0001626075,0.00020464935,0.0001784668,0.00024588025,0.00010314424,0.00020212722,0.000008600898],"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":[0.000014112788,0.00007640518,0.9644161,0.00008033677,0.000018532066,6.3506366e-7,0.00018940032,0.00040333296,0.000021832346,0.033062905,0.0016721882,0.00004421803],"study_design_scores_gemma":[0.00047719426,0.000039417984,0.7708115,0.000021706332,0.0000036610923,8.3972225e-7,0.000044946995,0.0017687376,0.0015192592,0.22456743,0.0005658781,0.00017941064],"about_ca_topic_score_codex":0.51206315,"about_ca_topic_score_gemma":0.6318874,"teacher_disagreement_score":0.19360457,"about_ca_system_score_codex":0.00089518167,"about_ca_system_score_gemma":0.00028303894,"threshold_uncertainty_score":0.8678292},"labels":[],"label_agreement":null},{"id":"W1987879456","doi":"10.1007/s00181-008-0248-4","title":"Economic determinants of the consumption of alcoholic beverages in Canada: a panel data analysis","year":2009,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Wine Industry and Tourism","field":"Business, Management and Accounting","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Brock University","funders":"","keywords":"Wine; Economics; Unemployment; Consumption (sociology); Panel data; Panel analysis; Tax revenue; Revenue; Public economics; Econometrics; Macroeconomics; Food science","score_opus":0.09062329097983746,"score_gpt":0.2863719408773013,"score_spread":0.19574864989746382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987879456","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970726,0.000012793777,0.0000027820774,0.0020122766,0.00011314555,0.00007519583,0.000042016643,0.000003687129,0.00066551036],"genre_scores_gemma":[0.99881476,0.0000075930984,0.000015109549,0.00079595955,0.00031123497,8.9534734e-7,0.000023398363,0.000004457963,0.00002658513],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99915695,0.000009544135,0.00044211536,0.00020922249,0.0000401081,0.00014208101],"domain_scores_gemma":[0.9990875,0.000046220972,0.00033780697,0.00050656474,0.000012553031,0.00000931421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019087421,0.00009226897,0.00030880453,0.00012519916,0.000028493943,0.000020254796,0.00050309644,0.000054105174,0.00010765521],"category_scores_gemma":[0.00003745895,0.00007845076,0.00006353527,0.0001692574,0.000034244335,0.00036119082,0.0001704048,0.00009499615,0.00000895701],"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":[0.000010396525,0.00002631599,0.98822194,0.0000123787995,0.000039165792,0.000001643608,0.000008254,0.006378702,0.0000025361007,0.000086871936,0.0029983444,0.002213472],"study_design_scores_gemma":[0.00022113665,0.000002159028,0.9392298,0.000008964495,0.0001032984,6.30951e-7,0.000019370755,0.056066096,0.000059198723,0.0004133873,0.0037906473,0.00008534774],"about_ca_topic_score_codex":0.35665002,"about_ca_topic_score_gemma":0.6141792,"teacher_disagreement_score":0.25752917,"about_ca_system_score_codex":0.00011292027,"about_ca_system_score_gemma":0.00022544009,"threshold_uncertainty_score":0.6476341},"labels":[],"label_agreement":null},{"id":"W1989164894","doi":"10.1007/s00181-014-0853-3","title":"An environmental degradation index based on stochastic dominance","year":2014,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Sustainable Development and Environmental Policy","field":"Environmental Science","cited_by":25,"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 Guelph","funders":"","keywords":"Index (typography); Dominance (genetics); Stochastic dominance; Economics; Econometrics; Environmental degradation; Degradation (telecommunications); Environmental science; Mathematics; Computer science; Ecology; Chemistry; Biology","score_opus":0.010097442103259142,"score_gpt":0.22753502951634164,"score_spread":0.2174375874130825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989164894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98015106,0.0000013891367,0.012416578,0.00048794167,0.00009048953,0.00016699982,0.000005843865,0.00003731377,0.0066423733],"genre_scores_gemma":[0.9950259,0.0000028955103,0.00066089287,0.0036159756,0.00007674624,0.000027214652,0.000051217023,0.000027977885,0.0005112018],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9987669,0.000055028893,0.00023240616,0.00045556927,0.00013244011,0.00035765435],"domain_scores_gemma":[0.99927455,0.00007470899,0.00008456919,0.00036153125,5.564554e-7,0.00020406439],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00021630636,0.00020370296,0.00015896522,0.000047962974,0.00015822594,0.00003966163,0.00025548192,0.0000946852,0.0018314024],"category_scores_gemma":[0.000022955628,0.00020859575,0.000051476607,0.00006427414,0.00018937343,0.00028403566,0.00008127394,0.00012483656,0.0016383424],"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":[0.00014085993,0.0004811016,0.30323774,0.000003439851,0.000006406187,0.0000021932035,0.00019024566,0.6255771,0.00024900213,0.00016824031,0.0017674674,0.06817618],"study_design_scores_gemma":[0.00077727705,0.00023105495,0.59245574,0.0000029175267,0.000006296366,0.0000020333182,0.000058934173,0.38848904,0.00026235063,0.0015930571,0.015741032,0.0003802398],"about_ca_topic_score_codex":0.000045217053,"about_ca_topic_score_gemma":0.000018673794,"teacher_disagreement_score":0.289218,"about_ca_system_score_codex":0.00073741196,"about_ca_system_score_gemma":0.000011326099,"threshold_uncertainty_score":0.999139},"labels":[],"label_agreement":null},{"id":"W1989206910","doi":"10.1007/s00181-014-0807-9","title":"A nonparametric analysis of firm size, leverage and labour productivity distribution dynamics","year":2014,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Lakehead University; Bank of Canada","funders":"","keywords":"Econometrics; Nonparametric statistics; Pairwise comparison; Stochastic dominance; Leverage (statistics); Economics; Statistics; Parametric statistics; Mathematics","score_opus":0.022939371652521,"score_gpt":0.23949290293511613,"score_spread":0.21655353128259514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989206910","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9789974,0.000085298794,0.014482254,0.0019624385,0.00015667168,0.00011510406,0.00086267263,0.00002399592,0.0033141687],"genre_scores_gemma":[0.9982527,0.00008481777,0.00061499694,0.00038998813,0.00005338795,0.000007666842,0.00016767003,0.000013875837,0.0004148793],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99854547,0.000022594928,0.00071646925,0.00047579187,0.000023868253,0.00021580454],"domain_scores_gemma":[0.9987866,0.00024124856,0.0004673598,0.00036761392,0.00005492187,0.00008223604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007731629,0.00015073906,0.00064260553,0.00039657258,0.00007065499,0.00005392929,0.00014719264,0.0001308654,0.0001311746],"category_scores_gemma":[0.0008701202,0.00018069617,0.00014796505,0.0015483068,0.00009974809,0.00020048495,0.00007429665,0.00014004155,0.000040959225],"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":[0.000018228742,0.00012840978,0.5116262,0.000024177236,0.00025269625,1.7031776e-7,0.00006839796,0.0009604528,0.0000015285945,0.48427784,0.00027841883,0.002363471],"study_design_scores_gemma":[0.0003341626,0.000058321926,0.77476114,0.0000015192436,0.000042656557,8.972379e-7,0.000009605434,0.17654029,0.00002239863,0.020447154,0.027574023,0.00020781513],"about_ca_topic_score_codex":0.0001445647,"about_ca_topic_score_gemma":0.00011123121,"teacher_disagreement_score":0.4638307,"about_ca_system_score_codex":0.00017947011,"about_ca_system_score_gemma":0.000018198283,"threshold_uncertainty_score":0.7368576},"labels":[],"label_agreement":null},{"id":"W1993809491","doi":"10.1007/s00181-011-0521-9","title":"The influence of measurement error and unobserved heterogeneity in estimating immigrant returns to foreign and host-country sources of human capital","year":2011,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Swedish Foundation for International Cooperation in Research and Higher Education; University of Ottawa","keywords":"Endogeneity; Human capital; Economics; Immigration; Econometrics; Estimation; Work (physics); Demographic economics; Capital (architecture); Labour economics; Geography; Economic growth","score_opus":0.07031260341118349,"score_gpt":0.3084555947314737,"score_spread":0.2381429913202902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993809491","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99930465,0.00007337548,0.00001473297,0.00019294828,0.00002201228,0.00017070198,0.000009913412,0.000005810345,0.00020582488],"genre_scores_gemma":[0.9991933,0.00003978786,0.0006246549,0.00011323872,0.000012756783,0.000005854976,4.829204e-7,0.0000043074474,0.000005599583],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992498,0.00006844753,0.00031578864,0.00013554767,0.00008885867,0.00014152804],"domain_scores_gemma":[0.99954444,0.00006424542,0.00014191533,0.000103478895,0.00006738418,0.00007853152],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087039504,0.000068620335,0.00015122707,0.000031346273,0.00015759189,0.000025688267,0.00012968906,0.00005383378,0.000004222615],"category_scores_gemma":[0.0002037691,0.000055830373,0.000022143167,0.00006918382,0.00025667192,0.000077980934,0.000047307145,0.000059712584,3.2308904e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004728494,0.000054536784,0.8405699,0.000032293236,0.000025650686,6.1545654e-7,0.12891224,0.0010206122,0.00054115866,0.02843068,0.000010774149,0.00035424187],"study_design_scores_gemma":[0.0003266896,0.00015152222,0.9700604,0.00004236118,0.000012880893,6.720335e-7,0.019134797,0.004634271,0.0006361151,0.004694728,0.00013806544,0.00016747063],"about_ca_topic_score_codex":0.004275915,"about_ca_topic_score_gemma":0.18615037,"teacher_disagreement_score":0.18187445,"about_ca_system_score_codex":0.000056029592,"about_ca_system_score_gemma":0.000061435756,"threshold_uncertainty_score":0.82870024},"labels":[],"label_agreement":null},{"id":"W1997228601","doi":"10.1007/s00181-011-0499-3","title":"On statistical inference for inequality measures calculated from complex survey data","year":2011,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":6,"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 Victoria","funders":"","keywords":"Wald test; Econometrics; Inference; Bootstrapping (finance); Statistics; Mathematics; Statistical inference; Linearization; Inequality; Survey data collection; Statistical hypothesis testing; Computer science","score_opus":0.5465929849389194,"score_gpt":0.4508400846838015,"score_spread":0.0957529002551179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997228601","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91068876,0.000014757989,0.052165635,0.0006824267,0.00085159834,0.00052968273,0.013592129,0.00012158827,0.021353452],"genre_scores_gemma":[0.9932387,0.000025163943,0.0027370064,0.0020312553,0.00020444732,0.000008778366,0.001686394,0.000015025694,0.000053248612],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99760556,0.00077488786,0.0005224003,0.0005357965,0.00015824813,0.0004031277],"domain_scores_gemma":[0.9956087,0.0031614846,0.00014964929,0.0006923245,0.00013626117,0.00025161938],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0028817272,0.0001604736,0.00037716966,0.0000314197,0.0003314754,0.0000832195,0.0008195046,0.00018917093,0.0010855825],"category_scores_gemma":[0.0057352227,0.00015349462,0.00005327804,0.00008283145,0.00033715033,0.00023986219,0.00017612746,0.0001695255,0.00013307662],"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":[0.0010464537,0.00097218563,0.5638595,0.000020603646,0.00018573717,0.000002991408,0.011897654,0.000036253394,0.000005570783,0.34449586,0.06608046,0.011396688],"study_design_scores_gemma":[0.0006288534,0.00012881984,0.8347908,0.0000057609477,0.000022374492,5.8304174e-8,0.00027981476,0.0075100493,0.000013826821,0.11167454,0.0445542,0.00039085373],"about_ca_topic_score_codex":0.056117844,"about_ca_topic_score_gemma":0.053658552,"teacher_disagreement_score":0.2709313,"about_ca_system_score_codex":0.00017907812,"about_ca_system_score_gemma":0.00036660302,"threshold_uncertainty_score":0.99982756},"labels":[],"label_agreement":null},{"id":"W2000322953","doi":"10.1007/s00181-010-0428-x","title":"The properties of survey-based inflation expectations in Sweden","year":2010,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Sveriges Riksbanken","keywords":"Inflation (cosmology); Economics; Survey data collection; Survey of Professional Forecasters; Quarter (Canadian coin); Autoregressive model; Econometrics; Monetary economics; Monetary policy; Statistics; Mathematics","score_opus":0.19471482457954106,"score_gpt":0.2834365196956798,"score_spread":0.08872169511613873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000322953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946269,0.0001801147,0.000096846525,0.00166947,0.0003665664,0.00016644923,0.00008401358,0.000012195666,0.0027974525],"genre_scores_gemma":[0.9992275,0.00003295171,0.00020830714,0.0002352608,0.00007546179,0.000023661294,0.000018550258,0.00001598982,0.00016227669],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99864054,0.000027311418,0.00083269755,0.00023620728,0.000011447409,0.0002517745],"domain_scores_gemma":[0.99899167,0.00024072263,0.00033153454,0.00035916673,0.000011865943,0.0000650637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008424845,0.00011818365,0.00029333646,0.00015796753,0.00010595548,0.00006296761,0.00025575946,0.00011285306,0.00011087168],"category_scores_gemma":[0.00039408734,0.00010926263,0.00008876213,0.00010682474,0.00013984073,0.00021474117,0.000030245807,0.00021511347,0.00026260383],"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":[0.00008494014,0.00009688773,0.9676002,0.000012223964,0.000026591852,2.2738918e-7,0.00093926984,0.016675165,0.000078338024,0.013119392,0.00071895594,0.0006477967],"study_design_scores_gemma":[0.00086925784,0.00005739063,0.76636523,0.0000066285234,0.0000027855826,0.0000013429045,0.000118201155,0.1963717,0.0009902386,0.013830274,0.021050608,0.000336366],"about_ca_topic_score_codex":0.0012938001,"about_ca_topic_score_gemma":0.0050888523,"teacher_disagreement_score":0.20123501,"about_ca_system_score_codex":0.00006431879,"about_ca_system_score_gemma":0.000050103255,"threshold_uncertainty_score":0.4455601},"labels":[],"label_agreement":null},{"id":"W2012470065","doi":"10.1007/s00181-006-0075-4","title":"Absenteeism in the workplace: results from Danish sample survey data","year":2006,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Absenteeism; Danish; Negative binomial distribution; Sample (material); Econometrics; Distribution (mathematics); Statistics; Beta-binomial distribution; Binomial distribution; Survey data collection; Demography; Demographic economics; Psychology; Economics; Mathematics; Social psychology; Poisson distribution; Sociology","score_opus":0.24181906452814278,"score_gpt":0.4408017200192658,"score_spread":0.19898265549112304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012470065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9444609,0.00014651469,0.00008374878,0.02653875,0.00072202506,0.00045782555,0.0046880315,0.000052610358,0.022849537],"genre_scores_gemma":[0.9812246,0.0002116836,0.0003829817,0.0071872803,0.0012711746,0.000042515014,0.0074805194,0.000032810265,0.00216641],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99761957,0.0006450639,0.0007616477,0.00046593472,0.00008005506,0.00042771793],"domain_scores_gemma":[0.99167305,0.007093276,0.00018601111,0.0009766018,0.000028637702,0.00004244978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020668805,0.00015276132,0.0002846061,0.00003759523,0.00042146945,0.000027367569,0.0007329788,0.0001479143,0.00013835811],"category_scores_gemma":[0.00085248565,0.00011287756,0.00003436056,0.00013054776,0.00006735231,0.00014119376,0.00051072333,0.00047618418,0.0003099741],"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":[0.00007964264,0.00004873212,0.6176171,0.0000024015442,0.000010160404,0.0000012962367,0.0008468328,0.000023548937,1.2657357e-7,0.00026218544,0.38091096,0.00019705026],"study_design_scores_gemma":[0.0008134692,0.000010043594,0.69960576,0.0000132834875,0.0000057335637,7.61759e-8,0.00060728635,0.00029567926,2.4377783e-7,0.004866581,0.29367626,0.00010557061],"about_ca_topic_score_codex":0.049862944,"about_ca_topic_score_gemma":0.14324313,"teacher_disagreement_score":0.09338018,"about_ca_system_score_codex":0.000112779235,"about_ca_system_score_gemma":0.00010936643,"threshold_uncertainty_score":0.9564641},"labels":[],"label_agreement":null},{"id":"W2013192938","doi":"10.1007/s00181-003-0168-2","title":"Pricing-to-market tests in instrumental regressions: Case of the transportation equipment industry","year":2004,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada; Université Laval","funders":"","keywords":"Endogeneity; Econometrics; Spurious relationship; Economics; Wald test; Instrumental variable; Monopolistic competition; Simultaneous equations model; Bayesian econometrics; Statistical hypothesis testing; Microeconomics; Statistics; Mathematics; Bayes factor; Bayes' theorem; Bayesian probability","score_opus":0.03465044512480235,"score_gpt":0.28496139151171573,"score_spread":0.25031094638691337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013192938","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99403894,0.000010749914,0.000010474921,0.0017557481,0.00025785295,0.0002760406,0.0000067495043,0.000017806562,0.0036256523],"genre_scores_gemma":[0.9982448,0.0000050437948,0.00012129531,0.0014722998,0.00008139555,0.000016627533,0.00000617659,0.00001435392,0.000037967926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991204,0.000009261384,0.00040270542,0.00021351741,0.000061993465,0.00019213354],"domain_scores_gemma":[0.999539,0.000054532215,0.00016314119,0.00020446043,0.000017875036,0.00002095901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024777377,0.00012763121,0.00016915251,0.00015797434,0.00008540136,0.000047779657,0.00016919347,0.000114458824,0.00021544758],"category_scores_gemma":[0.00006822079,0.000104439816,0.00006795467,0.0003519325,0.00003949823,0.00032626654,0.00007592112,0.00025483483,0.000012847268],"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":[0.00004887854,0.00014380619,0.97938544,0.00003889048,0.000007669047,0.00004672574,0.00025703822,0.0008858217,0.00006664998,0.00048288607,0.00029034115,0.01834587],"study_design_scores_gemma":[0.0009904171,0.000011102036,0.9900282,0.00015141715,0.00003611435,0.000019080537,0.00046987852,0.0003839338,0.00016528498,0.0011719951,0.006362772,0.00020979471],"about_ca_topic_score_codex":0.0018285435,"about_ca_topic_score_gemma":0.0058885054,"teacher_disagreement_score":0.018136075,"about_ca_system_score_codex":0.00012143676,"about_ca_system_score_gemma":0.000059582155,"threshold_uncertainty_score":0.42589322},"labels":[],"label_agreement":null},{"id":"W2013238662","doi":"10.1007/s00181-010-0387-2","title":"An analysis of the impact of the self-sufficiency project on wages","year":2010,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Earnings; Wage; Economics; Welfare; Demographic economics; Treatment and control groups; Percentage point; Randomized experiment; Work (physics); Labour economics; Statistics; Mathematics","score_opus":0.029221598776911564,"score_gpt":0.35047111505201906,"score_spread":0.3212495162751075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013238662","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983887,0.0000036756621,0.000008226376,0.00038252736,0.00030186927,0.00018001467,0.000059525242,0.000016256481,0.015160871],"genre_scores_gemma":[0.99955636,0.000028124383,0.000092236405,0.00015378316,0.000071251015,0.0000024634824,0.0000018729534,0.0000066109437,0.00008730516],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99906516,0.00015421968,0.00025500395,0.00018987634,0.0001249456,0.00021080399],"domain_scores_gemma":[0.998974,0.00014737017,0.00021141997,0.0005401365,0.00006677294,0.000060301947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055747456,0.000096100026,0.00023138776,0.00008771267,0.00023760597,0.000032236443,0.0007443892,0.00012562756,0.00004510151],"category_scores_gemma":[0.00014081685,0.000053072767,0.00040834324,0.00074974075,0.00033228428,0.000075774886,0.000053259013,0.00020014787,0.000002075264],"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":[0.0000061473424,0.00031737186,0.96590894,0.000002010675,0.000164179,5.1551083e-8,0.014981101,0.004630619,0.00011516538,0.013421617,0.00017268074,0.00028011942],"study_design_scores_gemma":[0.00007692701,0.00007076886,0.9767809,0.0000011256778,0.000117644406,9.359782e-8,0.0025456687,0.01888642,0.000027861357,0.00061207067,0.00079912937,0.00008138865],"about_ca_topic_score_codex":0.0028936935,"about_ca_topic_score_gemma":0.00651834,"teacher_disagreement_score":0.015669318,"about_ca_system_score_codex":0.00010350641,"about_ca_system_score_gemma":0.0006868839,"threshold_uncertainty_score":0.43744183},"labels":[],"label_agreement":null},{"id":"W2015996691","doi":"10.1007/s00181-014-0910-y","title":"Key features and determinants of credit-less recoveries","year":2015,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada; Wilfrid Laurier University","funders":"","keywords":"Probit model; Currency; Economics; Monetary economics; Emerging markets; Probit; Bond market; Financial system; Econometrics; Finance","score_opus":0.06574051091996731,"score_gpt":0.27803067176684093,"score_spread":0.21229016084687363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015996691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99084806,0.0012632973,0.00021542206,0.00049139495,0.00057225843,0.0001285173,0.00014130035,0.000026709788,0.0063130204],"genre_scores_gemma":[0.99777406,0.00013180025,0.0014996049,0.00014463003,0.00011839441,0.000006838803,0.000008876733,0.00002184506,0.00029391737],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99861866,0.000018069539,0.00068970677,0.0004161802,0.000025101706,0.00023226623],"domain_scores_gemma":[0.99896514,0.0001104919,0.0003799694,0.00036636644,0.00004768974,0.00013032484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064027,0.00015113754,0.00049047254,0.00013499285,0.00005683961,0.000063105595,0.00020852516,0.00015021005,0.000046515586],"category_scores_gemma":[0.00040918853,0.00017474474,0.00007594525,0.000118370604,0.00023558016,0.0002817324,0.0001158664,0.00010110538,0.000040955027],"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":[0.000037155773,0.00008908177,0.9581409,0.00003346151,0.000015665233,6.8967086e-7,0.0014888346,0.00033498026,8.1141525e-7,0.03424969,0.0023049433,0.0033037488],"study_design_scores_gemma":[0.00073049706,0.00017762255,0.81525046,0.000012083058,0.000007142847,0.0000187147,0.00021986835,0.0046686847,0.0001540996,0.15173265,0.026661964,0.00036621423],"about_ca_topic_score_codex":0.00014256626,"about_ca_topic_score_gemma":0.00015848731,"teacher_disagreement_score":0.14289048,"about_ca_system_score_codex":0.00012366034,"about_ca_system_score_gemma":0.00005988043,"threshold_uncertainty_score":0.71258837},"labels":[],"label_agreement":null},{"id":"W2018524283","doi":"10.1007/s00181-013-0784-4","title":"Imposing curvature conditions on flexible functional forms for GNP functions","year":2014,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Curvature; Convexity; Function (biology); Quadratic equation; Dominance (genetics); Econometrics; Mathematics; Sign (mathematics); Economics; Mathematical analysis; Geometry","score_opus":0.13934746336877252,"score_gpt":0.2840379347412201,"score_spread":0.14469047137244756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018524283","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83567435,0.00016786673,0.049320385,0.01120674,0.0025729234,0.0006553397,0.0024529037,0.00021221295,0.097737275],"genre_scores_gemma":[0.98436284,0.000029395413,0.0007155537,0.008034122,0.0010741052,0.000112593174,0.0005455301,0.000057706602,0.0050681443],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980445,0.000012591683,0.00076534273,0.0006142446,0.000017248442,0.0005461032],"domain_scores_gemma":[0.99864477,0.0003298419,0.00031594743,0.00045714853,0.000015270602,0.00023702468],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004906509,0.00027151592,0.00050730095,0.00027892523,0.0004454457,0.00014116972,0.00019740991,0.00024024777,0.0010423668],"category_scores_gemma":[0.00016696157,0.00030902188,0.00035869415,0.00009757841,0.00008584951,0.00044640613,0.000039040104,0.0002583018,0.002665623],"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":[0.00021156138,0.00027973606,0.029353218,0.000036509417,0.0002203472,2.6575714e-7,0.00017485677,0.10444568,0.000011135807,0.6940775,0.17014012,0.0010490734],"study_design_scores_gemma":[0.0012957004,0.0003309488,0.022232523,0.000008188108,0.000017877846,0.0000096454605,0.000025446932,0.07530606,0.00007162346,0.20222867,0.69797266,0.0005006602],"about_ca_topic_score_codex":0.00003670105,"about_ca_topic_score_gemma":0.00002030818,"teacher_disagreement_score":0.5278325,"about_ca_system_score_codex":0.00027021725,"about_ca_system_score_gemma":0.000030819723,"threshold_uncertainty_score":0.99993616},"labels":[],"label_agreement":null},{"id":"W2025172040","doi":"10.1007/s00181-007-0120-y","title":"Demographic versus expenditure flexibility in Engel curves","year":2007,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":5,"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 Guelph","funders":"","keywords":"Engel curve; Economics; Econometrics; Logarithm; Rank (graph theory); Welfare; Flexibility (engineering); Mathematics; Consumption (sociology); Price index","score_opus":0.07054597796861156,"score_gpt":0.28506541122705126,"score_spread":0.2145194332584397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025172040","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8638907,0.0072578383,0.000169558,0.0027445154,0.0013601152,0.00033268568,0.000091826994,0.000076385404,0.12407636],"genre_scores_gemma":[0.99322045,0.0028875656,0.0007264632,0.0023915474,0.00035613577,0.000021817472,0.000063048,0.000035736404,0.00029725485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971515,0.000019371857,0.0012831575,0.0008447841,0.000024350784,0.00067685655],"domain_scores_gemma":[0.9984478,0.00034528313,0.00037014956,0.00055914774,0.00002062499,0.0002570134],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00185284,0.00030828736,0.00069628423,0.0003552054,0.00008399897,0.00006285933,0.00047606905,0.0003336998,0.00044968122],"category_scores_gemma":[0.00020349942,0.00035159205,0.0002886822,0.00028201856,0.000110695226,0.00046200643,0.00012939163,0.00046096812,0.00054453785],"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":[0.0011891423,0.0011845265,0.7275639,0.00023155748,0.0003406407,0.000043523716,0.00097026076,0.00033197406,0.000015696849,0.22218928,0.04118088,0.0047586346],"study_design_scores_gemma":[0.0037045358,0.00030531132,0.5939858,0.000057161233,0.000015752172,0.000012051653,0.00027061455,0.00043974217,0.00013398986,0.07890041,0.3208627,0.0013119528],"about_ca_topic_score_codex":0.0001000264,"about_ca_topic_score_gemma":0.0014556092,"teacher_disagreement_score":0.27968183,"about_ca_system_score_codex":0.00033288877,"about_ca_system_score_gemma":0.000032422657,"threshold_uncertainty_score":0.9998936},"labels":[],"label_agreement":null},{"id":"W2028475724","doi":"10.1007/s00181-009-0261-2","title":"Exchange rate pass-through, menu costs and threshold cointegration","year":2009,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":12,"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; Université Laval","funders":"","keywords":"Cointegration; Economics; Econometrics; Currency; Market power; Exchange rate; tar (computing); Exchange-rate pass-through; Unit root; Value (mathematics); Standard deviation; Autoregressive model; Monetary economics; Microeconomics; Statistics; Mathematics; Computer science","score_opus":0.11017757944486202,"score_gpt":0.27959430532388596,"score_spread":0.16941672587902395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028475724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8813238,0.0013647187,0.0011194869,0.012150052,0.0004085156,0.00028320646,0.00015402566,0.00007266849,0.10312352],"genre_scores_gemma":[0.9840825,0.001658925,0.0007044635,0.011859176,0.0003429322,0.000012440967,0.000057366266,0.000026912117,0.0012552552],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981254,0.000019249177,0.0007496738,0.0006155465,0.000012681437,0.00047748943],"domain_scores_gemma":[0.9990033,0.00007471452,0.00031336196,0.00039941375,0.000007790602,0.00020140478],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005226254,0.00027288077,0.0005679763,0.00013810865,0.00014560547,0.00017208746,0.00019342665,0.00019339567,0.00046642378],"category_scores_gemma":[0.00006446675,0.00031581262,0.00012896085,0.000080738464,0.00008131767,0.0007349796,0.000046415174,0.00021753566,0.0008451627],"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":[0.00035353086,0.0005369789,0.07255772,0.000068106456,0.00026747704,0.00002198736,0.004826375,0.00406781,0.00007237003,0.7708023,0.11576335,0.03066199],"study_design_scores_gemma":[0.002241232,0.0005954192,0.081683606,0.000020947258,0.000020585303,0.000043754964,0.000112451504,0.099792734,0.00020666872,0.28074205,0.5333559,0.0011846785],"about_ca_topic_score_codex":0.00013786813,"about_ca_topic_score_gemma":0.00007978058,"teacher_disagreement_score":0.49006024,"about_ca_system_score_codex":0.00027556662,"about_ca_system_score_gemma":0.000016179978,"threshold_uncertainty_score":0.99993277},"labels":[],"label_agreement":null},{"id":"W2029310076","doi":"10.1007/s00181-010-0384-5","title":"Power laws in top wealth distributions: evidence from Canada","year":2010,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Brock University","funders":"","keywords":"Zipf's law; Pareto distribution; Exponent; Econometrics; Economics; Power law; Power (physics); Wealth distribution; Pareto principle; Distribution (mathematics); Estimation; Statistics; Law; Mathematics; Inequality; Political science; Physics; Mathematical analysis","score_opus":0.033834385495154495,"score_gpt":0.24926658208938504,"score_spread":0.21543219659423055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029310076","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9847065,0.0006916167,0.00031868438,0.005559977,0.00088201545,0.00012222766,0.00071626017,0.000017879265,0.006984799],"genre_scores_gemma":[0.9981311,0.00011168839,0.0004472402,0.0006303678,0.00016665498,0.000017810371,0.000048853377,0.000016680126,0.00042963147],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981924,0.000014770077,0.0008909867,0.00052212796,0.000024810271,0.00035485023],"domain_scores_gemma":[0.99874634,0.00020632416,0.00028460711,0.0005599522,0.000022778819,0.00018000693],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00035723497,0.00016675971,0.00053375814,0.000100039906,0.000097621334,0.000096751784,0.00034197085,0.00011809772,0.004425236],"category_scores_gemma":[0.00025753732,0.00019741313,0.00012211582,0.00023010896,0.00004911252,0.00024156022,0.000103572536,0.000324712,0.00034722147],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017205668,0.00006631563,0.92249495,0.0000074129593,0.000055759745,0.000007865288,0.00019060157,0.0001977208,0.000009759345,0.06825683,0.008239184,0.0004563732],"study_design_scores_gemma":[0.0003031479,0.00002573966,0.4716168,0.000013765385,0.0000044261496,0.000002632692,0.00008888822,0.005030631,0.00002354249,0.021011563,0.5014955,0.0003833595],"about_ca_topic_score_codex":0.7445312,"about_ca_topic_score_gemma":0.88605756,"teacher_disagreement_score":0.4932563,"about_ca_system_score_codex":0.00041077106,"about_ca_system_score_gemma":0.00024370538,"threshold_uncertainty_score":0.9964849},"labels":[],"label_agreement":null},{"id":"W2029755180","doi":"10.1007/s00181-009-0285-7","title":"Multilateral trade and export-led growth in the world economy: some post-war evidence","year":2009,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Economics; Nexus (standard); Cointegration; Free trade; World economy; International economics; World trade; International trade; Real gross domestic product; Granger causality; World War II; Macroeconomics; Econometrics; Geography; Political science","score_opus":0.07891958640665463,"score_gpt":0.2651021490755954,"score_spread":0.18618256266894073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029755180","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94289064,0.0020278192,0.000012352548,0.038446523,0.00028201827,0.00037773693,0.000075413205,0.00004504681,0.015842456],"genre_scores_gemma":[0.97070825,0.0009009373,0.0003756742,0.027467337,0.00028305972,0.000025606989,0.000015840207,0.000025981304,0.00019731109],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9972744,0.00003636302,0.0012136903,0.00081058854,0.000019418798,0.0006455428],"domain_scores_gemma":[0.9987088,0.00025878882,0.00035119374,0.00047116246,0.0000104342425,0.00019966245],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008257397,0.00035495317,0.0007238683,0.00033718537,0.00013206614,0.00023225104,0.00061186246,0.00017920241,0.0001967383],"category_scores_gemma":[0.00010239019,0.0003587964,0.00020659821,0.00019851011,0.00011940946,0.001348693,0.00006705064,0.00040194928,0.00033829443],"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":[0.00021963067,0.0005767683,0.42574698,0.00006615907,0.000099243814,0.00005446957,0.004413475,0.00035999756,0.00001239606,0.556783,0.00914265,0.0025252264],"study_design_scores_gemma":[0.0014196598,0.00028326802,0.69001,0.000032523058,0.0000127350895,0.00004801922,0.00027599582,0.005793469,0.000065416614,0.2328906,0.06828996,0.000878364],"about_ca_topic_score_codex":0.000071136,"about_ca_topic_score_gemma":0.00022365838,"teacher_disagreement_score":0.32389238,"about_ca_system_score_codex":0.00026771092,"about_ca_system_score_gemma":0.00004706844,"threshold_uncertainty_score":0.9998864},"labels":[],"label_agreement":null},{"id":"W2030672461","doi":"10.1007/s00181-014-0894-7","title":"Nonlinear attractors and asymmetries between non-life insurance premiums and financial markets","year":2014,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":6,"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 Manitoba; Queen's University","funders":"","keywords":"Economics; Financial market; Nonlinear system; Attractor; Econometrics; Financial economics; Monetary economics; Finance; Mathematics; Physics","score_opus":0.028132873415034742,"score_gpt":0.2365343205425305,"score_spread":0.20840144712749578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030672461","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9824575,0.00066393183,0.0023705163,0.0011636775,0.00042709056,0.00025532037,0.00022193823,0.000039308197,0.0124006905],"genre_scores_gemma":[0.9946199,0.0014325347,0.0012735974,0.0017249251,0.00061215466,0.000019747296,0.00002079761,0.00003868333,0.0002576575],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980033,0.000019921825,0.0008113684,0.00068642636,0.00003214617,0.00044681283],"domain_scores_gemma":[0.9988433,0.00021083717,0.0003451275,0.00033693152,0.000024318722,0.00023949516],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00080056954,0.00028611254,0.0007518852,0.00022613638,0.00021046658,0.00014804484,0.0002208834,0.00023664755,0.00003123187],"category_scores_gemma":[0.000571051,0.0003374555,0.00009874722,0.00018875371,0.00019552925,0.0003935918,0.00017799488,0.00026993552,0.00017532476],"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":[0.000042774747,0.000048935184,0.96370935,0.00005348706,0.000029384597,0.0000010131334,0.0002489968,0.00001671952,4.5900362e-7,0.01589258,0.0012465446,0.01870977],"study_design_scores_gemma":[0.00065214786,0.000096101125,0.7464724,0.000010561361,0.000006578521,0.0000010351538,0.000012958089,0.0015124915,0.000016467158,0.010019479,0.24085517,0.00034461162],"about_ca_topic_score_codex":0.00008801732,"about_ca_topic_score_gemma":0.000028423174,"teacher_disagreement_score":0.23960862,"about_ca_system_score_codex":0.0000667203,"about_ca_system_score_gemma":0.0000334211,"threshold_uncertainty_score":0.99990773},"labels":[],"label_agreement":null},{"id":"W2033226799","doi":"10.1007/s001810050006","title":"Cointegration and causality in the exports-GDP nexus: The post-war evidence for Canada","year":2000,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Cointegration; Nexus (standard); Economics; Bivariate analysis; Causality (physics); Granger causality; Unit root; Econometrics; Real gross domestic product; Monetary economics; Macroeconomics; International economics; Mathematics; Statistics","score_opus":0.17401953152046176,"score_gpt":0.29523097901264467,"score_spread":0.1212114474921829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033226799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9668246,0.001080318,0.00007215634,0.027870692,0.00018664189,0.0004669352,0.0003093925,0.000008114593,0.00318118],"genre_scores_gemma":[0.98351246,0.0006226346,0.00007993488,0.015072466,0.00019991174,0.00006359247,0.000027211294,0.000014996272,0.00040678825],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99848,0.000039397106,0.0007145696,0.0003921327,0.00001754846,0.0003563174],"domain_scores_gemma":[0.99860495,0.0006839501,0.00019178019,0.00042943473,0.000007905351,0.00008197874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011613416,0.00017453253,0.0003330752,0.00004667596,0.00019180251,0.000100110185,0.00032411414,0.00008373447,0.00046707268],"category_scores_gemma":[0.00023682028,0.00013383232,0.00008560594,0.00006896516,0.00009403599,0.000358113,0.000022474369,0.00018897107,0.00006268631],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085511815,0.00034737345,0.6558233,0.00015339578,0.00024243127,0.000018934837,0.026564231,0.047250986,0.000003336321,0.059233505,0.17713831,0.032369073],"study_design_scores_gemma":[0.0010668944,0.00021710635,0.38697535,0.000023334798,0.00002037343,0.000057383077,0.0015768904,0.11988313,0.000012024628,0.047830887,0.44166148,0.0006751414],"about_ca_topic_score_codex":0.304341,"about_ca_topic_score_gemma":0.3697914,"teacher_disagreement_score":0.26884794,"about_ca_system_score_codex":0.00026081756,"about_ca_system_score_gemma":0.00013378823,"threshold_uncertainty_score":0.70029145},"labels":[],"label_agreement":null},{"id":"W2038804276","doi":"10.1007/s00181-003-0193-1","title":"Reinterpreting the performance of immigrant wages from panel data","year":2004,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":59,"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 Manitoba","funders":"","keywords":"Instrumental variable; Immigration; Unobservable; Economics; Wage; Panel data; Omitted-variable bias; Native-Born; Econometrics; Fixed effects model; Estimation; Demographic economics; Disadvantage; Variable (mathematics); Panel Study of Income Dynamics; Variables; Labour economics; Geography; Statistics; Mathematics; Political science","score_opus":0.06513667599419071,"score_gpt":0.32462043074511227,"score_spread":0.25948375475092156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038804276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98907554,0.00006432696,0.00023128398,0.0075287553,0.00016977123,0.0000751377,0.00008006958,0.000020905325,0.0027541853],"genre_scores_gemma":[0.9975357,0.00062662957,0.0005747617,0.0008838136,0.00015157861,0.000001625895,0.00003684384,0.0000057422976,0.00018327203],"study_design_codex":"qualitative","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993426,0.000050315124,0.0002278712,0.00017291248,0.00006623558,0.00014007128],"domain_scores_gemma":[0.99927,0.0001629821,0.00010804946,0.00038556274,0.00002384478,0.000049532824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004625527,0.000059904694,0.00011163191,0.000014953973,0.00019119473,0.000045022207,0.0006170573,0.000056621444,0.00011957247],"category_scores_gemma":[0.00014658179,0.000045239063,0.000033534183,0.000070058704,0.00019993015,0.0001890518,0.000109915265,0.00010417522,0.000034771947],"study_design_candidate":"not_applicable","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":[0.00027775788,0.0005140168,0.18496498,0.00005463545,0.00031864332,0.00000608236,0.5174176,0.054881692,0.0004970417,0.14661035,0.01038656,0.08407062],"study_design_scores_gemma":[0.0013245154,0.00015483127,0.049010616,0.000119916214,0.00008365834,0.0000020259595,0.04013749,0.253938,0.0007882491,0.009921354,0.64375854,0.00076083426],"about_ca_topic_score_codex":0.0034820787,"about_ca_topic_score_gemma":0.016829414,"teacher_disagreement_score":0.63337195,"about_ca_system_score_codex":0.00006441841,"about_ca_system_score_gemma":0.00016134114,"threshold_uncertainty_score":0.9391208},"labels":[],"label_agreement":null},{"id":"W2040119961","doi":"10.1007/s001810100120","title":"On the choice of functional form in stochastic frontier modeling","year":2003,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":104,"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 Saskatchewan","funders":"","keywords":"Inefficiency; Functional specification; Specification; Transformation (genetics); Econometrics; Set (abstract data type); Identification (biology); Computer science; Truncation (statistics); Quadratic equation; Mathematical optimization; Mathematics; Economics; Software","score_opus":0.20382055969963414,"score_gpt":0.3767662309148916,"score_spread":0.17294567121525745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040119961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8452334,0.00002768225,0.14729588,0.0012872372,0.00022703414,0.00006658544,0.0000029855964,0.0000049476516,0.005854296],"genre_scores_gemma":[0.99834424,0.0000010062452,0.0002469572,0.0010169619,0.000027172384,0.0000043909035,6.8918314e-7,0.000006358489,0.00035221557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984215,0.000116008494,0.00066247286,0.00032945376,0.00028706057,0.00018353222],"domain_scores_gemma":[0.99635637,0.0029104855,0.00016209378,0.00044244557,0.00008164397,0.00004696094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023117089,0.00009535164,0.00024822212,0.00022574818,0.00008358761,0.000058764454,0.00036561568,0.000062765466,0.0004798083],"category_scores_gemma":[0.005165239,0.0000612332,0.00013615047,0.00043836204,0.00007904821,0.00012428137,0.000038100374,0.00016780337,0.00019396946],"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":[0.000011656216,0.00005919291,0.0023184253,2.3362367e-7,0.0000065479767,1.2704838e-7,0.00011154513,0.9766756,0.0000026386613,0.01895988,0.0014796284,0.0003744973],"study_design_scores_gemma":[0.00015504229,0.000020809195,0.0013903121,0.0000033245385,0.0000050048516,5.7314753e-7,0.00013356464,0.85261375,0.000011281056,0.14442651,0.0011702682,0.000069541646],"about_ca_topic_score_codex":0.000017048815,"about_ca_topic_score_gemma":0.00013541084,"teacher_disagreement_score":0.15311089,"about_ca_system_score_codex":0.00009815636,"about_ca_system_score_gemma":0.00011358599,"threshold_uncertainty_score":0.61836463},"labels":[],"label_agreement":null},{"id":"W2049786818","doi":"10.1007/s00181-012-0588-y","title":"Robust estimation of the simplified multivariate GARCH model","year":2012,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Environment and Climate Change Canada","keywords":"Estimator; Autoregressive conditional heteroskedasticity; Univariate; Multivariate statistics; Econometrics; Monte Carlo method; Statistics; Estimation; Mathematics; Computer science; Economics; Volatility (finance)","score_opus":0.1765927398752558,"score_gpt":0.29470252691391696,"score_spread":0.11810978703866115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049786818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84642303,0.00021764608,0.14651181,0.00058411947,0.000363849,0.00016489103,0.00008569724,0.000018621075,0.0056303227],"genre_scores_gemma":[0.9901569,0.00003304092,0.009142107,0.00030435916,0.00009831986,0.000010289956,0.000006823927,0.00002095259,0.0002271925],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986922,0.000014561455,0.00071302365,0.00023726019,0.000021132118,0.00032181208],"domain_scores_gemma":[0.9990839,0.000078141755,0.00032620155,0.000405243,0.00002055402,0.0000860037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062102545,0.00013054561,0.00033141827,0.000073109375,0.00011250696,0.000021591386,0.00025748505,0.00013703393,0.000052491],"category_scores_gemma":[0.00023890435,0.00012414098,0.00016659258,0.000116350006,0.00006705701,0.00030137307,0.00012286821,0.0001760983,0.000121563135],"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":[0.00002155608,0.00013215024,0.08318168,0.00001878019,0.000018099483,2.1020629e-8,0.0010113863,0.7205702,0.000008811203,0.1930018,0.00034305084,0.0016924258],"study_design_scores_gemma":[0.0002308347,0.000009102162,0.03778367,0.000004608524,0.0000046535188,4.864113e-7,0.000012978545,0.9064666,0.00011096819,0.05384145,0.0013975103,0.00013716125],"about_ca_topic_score_codex":0.00012857678,"about_ca_topic_score_gemma":0.000012966154,"teacher_disagreement_score":0.18589635,"about_ca_system_score_codex":0.00012231246,"about_ca_system_score_gemma":0.000040628176,"threshold_uncertainty_score":0.50623226},"labels":[],"label_agreement":null},{"id":"W2050588877","doi":"10.1007/s00181-015-0917-z","title":"Informed traders’ arrival in foreign exchange markets: Does geography matter?","year":2015,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Market microstructure; Database transaction; Profit (economics); Order (exchange); Foreign exchange market; Market maker; Economics; Transaction cost; Private information retrieval; Work (physics); Financial economics; Foreign exchange; Algorithmic trading; Econometrics; Microeconomics; Business; Monetary economics; Stock market; Finance; Geography; Computer science","score_opus":0.06642132706003336,"score_gpt":0.25166318547912214,"score_spread":0.1852418584190888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050588877","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6698135,0.0006525708,0.000102175654,0.0024633438,0.0006723212,0.00029131238,0.00012543803,0.0000453669,0.32583398],"genre_scores_gemma":[0.99294835,0.0008388739,0.00079688366,0.004345942,0.0002566263,0.000088151595,0.000046832214,0.000046823792,0.000631524],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99790204,0.000022684475,0.00095960364,0.0005117717,0.00003227677,0.00057165616],"domain_scores_gemma":[0.9989504,0.00010639125,0.00030263455,0.0003732812,0.000016631817,0.00025061917],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00059095677,0.00028289596,0.00059296284,0.0004625892,0.00006123487,0.00016006366,0.0003554477,0.00021124702,0.0008858732],"category_scores_gemma":[0.00013609945,0.00027725458,0.00018810527,0.00023917781,0.00016344286,0.0007546883,0.00009705444,0.0002114899,0.0007786546],"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":[0.0001183986,0.00013804497,0.841842,0.000059456586,0.000037113918,0.000006889785,0.00084974297,0.000049685557,1.6531672e-7,0.13501689,0.021300437,0.0005811763],"study_design_scores_gemma":[0.0013160888,0.0001049205,0.41720548,0.000016679696,0.0000035628475,0.0000038528106,0.0004956818,0.0007591576,0.0000066482553,0.3017378,0.27787495,0.0004752012],"about_ca_topic_score_codex":0.00026417957,"about_ca_topic_score_gemma":0.00030141592,"teacher_disagreement_score":0.4246365,"about_ca_system_score_codex":0.00028420758,"about_ca_system_score_gemma":0.00011395078,"threshold_uncertainty_score":0.99999934},"labels":[],"label_agreement":null},{"id":"W2053720812","doi":"10.1007/s001810100105","title":"Estimation of an effectively globally regular demand system: An application to United States meat consumption","year":2002,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Agriculture Food and Rural Development; University of Alberta","funders":"","keywords":"Almost ideal demand system; Dominance (genetics); Consumption (sociology); Estimation; Curvature; On demand; Economics; Econometrics; Mathematics; Microeconomics; Sociology; Commerce","score_opus":0.028044387290142254,"score_gpt":0.24263165339477172,"score_spread":0.21458726610462947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053720812","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9819308,0.00021676699,0.012836308,0.00057470636,0.00015563559,0.0005911877,0.00025979732,0.00009572467,0.0033390587],"genre_scores_gemma":[0.9950997,0.00016260834,0.0035092812,0.00059818954,0.00009537572,0.000054462966,0.00037728084,0.00003036756,0.00007271248],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808127,0.000052170486,0.00091338845,0.0006399034,0.000029697745,0.00028355376],"domain_scores_gemma":[0.9985503,0.00008401604,0.0005166879,0.00051027123,0.000057759244,0.00028094556],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006124025,0.00023831356,0.00055421883,0.000302669,0.0001099506,0.00011345477,0.00035182203,0.00027386687,0.000070642614],"category_scores_gemma":[0.000050582817,0.00027215324,0.00010172921,0.00021288784,0.00005833608,0.00067570363,0.00005980411,0.00014229375,0.00056323525],"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":[0.00050288363,0.0017923907,0.05801085,0.00063584314,0.0005325318,0.0000052549044,0.0033790455,0.44920123,0.00024207353,0.4492458,0.00657993,0.029872142],"study_design_scores_gemma":[0.0010998208,0.00071288063,0.05489861,0.00003143841,0.000036803765,0.00001867052,0.00016137597,0.914405,0.0005615332,0.013120044,0.014292802,0.00066101237],"about_ca_topic_score_codex":0.00014062246,"about_ca_topic_score_gemma":0.00012333244,"teacher_disagreement_score":0.4652038,"about_ca_system_score_codex":0.00030060307,"about_ca_system_score_gemma":0.000007861883,"threshold_uncertainty_score":0.99997306},"labels":[],"label_agreement":null},{"id":"W2054161365","doi":"10.1007/s00181-005-0243-y","title":"Rejecting the Hotelling Valuation Principle","year":2005,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Capital Investment and Risk Analysis","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Valuation (finance); Economics; Econometrics; Heteroscedasticity; Mathematical economics; Microeconomics; Finance","score_opus":0.10765941800612734,"score_gpt":0.2972255602093499,"score_spread":0.1895661422032226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054161365","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9682997,0.0037843555,0.001746429,0.010419601,0.00027911167,0.00015646314,0.0000148715535,0.0000511574,0.015248334],"genre_scores_gemma":[0.99142605,0.0014878196,0.0017361997,0.002319992,0.00066461234,0.000015056437,0.00001623247,0.000022879232,0.0023111862],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880326,0.000014925546,0.0005949331,0.00032720322,0.000019918418,0.00023975877],"domain_scores_gemma":[0.99922574,0.000087647415,0.00028046357,0.0003229297,0.00001547029,0.00006776792],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000754785,0.00012285289,0.00024729155,0.000108558146,0.0002278218,0.00012616525,0.00022002989,0.00008091295,0.00033795208],"category_scores_gemma":[0.00009283469,0.00010871373,0.000193919,0.00015668978,0.000044004217,0.0002554625,0.00006310538,0.00016195957,0.0021413893],"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":[0.00001236747,0.00010904208,0.04461397,0.000005806953,0.00013805907,5.590249e-7,0.001579489,0.033386063,0.0000060388143,0.9123677,0.00253993,0.0052409815],"study_design_scores_gemma":[0.00031974376,0.000031444684,0.009157913,0.000003155056,0.000020296622,0.00000333451,0.00015094462,0.42291984,0.00018429213,0.14552037,0.42137927,0.0003093981],"about_ca_topic_score_codex":0.00005666422,"about_ca_topic_score_gemma":0.00008741586,"teacher_disagreement_score":0.7668473,"about_ca_system_score_codex":0.00020089102,"about_ca_system_score_gemma":0.000018351291,"threshold_uncertainty_score":0.99863553},"labels":[],"label_agreement":null},{"id":"W2059853730","doi":"10.1007/s001810000069","title":"Do reductions in black market exchange rate premia cause inflation?","year":2001,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Economics; Black market; Inflation (cosmology); Exchange rate; Real interest rate; Floating exchange rate; Monetary economics; Monetary policy; Unification; Shock (circulatory); Macroeconomics; Market economy","score_opus":0.13001511458648143,"score_gpt":0.2903906727319457,"score_spread":0.16037555814546425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059853730","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89875615,0.0003246526,0.00014767563,0.0041848286,0.0006320642,0.00027651276,0.00014606211,0.00004825213,0.09548381],"genre_scores_gemma":[0.9862829,0.0020292175,0.0003223313,0.00154076,0.00052667747,0.000037922327,0.000038454506,0.000047656387,0.009174083],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975956,0.00004347234,0.0010987773,0.0006552894,0.000013508237,0.00059336994],"domain_scores_gemma":[0.99869823,0.00012908297,0.00035366684,0.0005825617,0.000008397004,0.00022804487],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008914403,0.0002669774,0.0005550902,0.0004621946,0.00010315232,0.00013792247,0.0002837166,0.00023287472,0.006622167],"category_scores_gemma":[0.00014878763,0.0003472841,0.00016056607,0.0002478669,0.000117204065,0.0006994159,0.00008882618,0.0002972145,0.003076885],"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":[0.00017406531,0.0002503334,0.8643313,0.000033881966,0.00012784071,0.000018918847,0.0022378475,0.044272423,0.0000024814567,0.012625432,0.07469269,0.0012327689],"study_design_scores_gemma":[0.0013728074,0.00007324064,0.29657975,0.000013477177,0.0000103323355,0.00003090468,0.00011038502,0.08839394,0.000009644983,0.052962866,0.5597538,0.0006888656],"about_ca_topic_score_codex":0.00044188066,"about_ca_topic_score_gemma":0.0002845699,"teacher_disagreement_score":0.5677516,"about_ca_system_score_codex":0.00049614726,"about_ca_system_score_gemma":0.000035360918,"threshold_uncertainty_score":0.9998979},"labels":[],"label_agreement":null},{"id":"W2060062129","doi":"10.1007/s00181-010-0448-6","title":"Network externalities in consumer spending on lottery games: evidence from Spain","year":2010,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":17,"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":"Lottery; Tobit model; Consumption (sociology); Economics; Externality; Consumer spending; Microeconomics; Consumer Expenditure Survey; Public economics; Advertising; Econometrics; Business; Macroeconomics; Sociology","score_opus":0.08886275030798725,"score_gpt":0.2742377315910977,"score_spread":0.18537498128311047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060062129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9610358,0.00032831903,0.00033093605,0.0014309195,0.0021613862,0.00017971685,0.00007561113,0.0000601932,0.034397107],"genre_scores_gemma":[0.9930476,0.0008508578,0.0019683205,0.0024940365,0.0011172283,0.000023633884,0.000016567921,0.000067155146,0.0004145944],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972783,0.000039991555,0.0011489904,0.00083727774,0.000025364821,0.0006701285],"domain_scores_gemma":[0.99778646,0.0010086818,0.0004209559,0.0005814309,0.000008457207,0.00019401587],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013734262,0.00032254335,0.0007475086,0.00024531197,0.00010650999,0.00027874144,0.0005082133,0.00029009779,0.0021706456],"category_scores_gemma":[0.00038548882,0.00040701983,0.00017723172,0.0001319975,0.0001545696,0.00051814143,0.00014643269,0.00069061393,0.0027689007],"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":[0.000110731846,0.000082578335,0.96899873,0.000011606356,0.000035299625,0.000013582406,0.0005110447,0.0021882472,0.000011671539,0.021333735,0.0026237408,0.0040790197],"study_design_scores_gemma":[0.0015512431,0.0001375369,0.4927518,0.00021784437,0.000014299247,0.000012325834,0.00016313544,0.031392496,0.00008225264,0.28366017,0.18836832,0.0016485977],"about_ca_topic_score_codex":0.00081571366,"about_ca_topic_score_gemma":0.0014336199,"teacher_disagreement_score":0.47624695,"about_ca_system_score_codex":0.00027632603,"about_ca_system_score_gemma":0.00004316804,"threshold_uncertainty_score":0.9998382},"labels":[],"label_agreement":null},{"id":"W2062121708","doi":"10.1007/s00181-010-0438-8","title":"Deposit insurance scheme and banking crises: a special focus on less-developed countries","year":2010,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thompson Rivers University; Simon Fraser University","funders":"","keywords":"Panel data; Economics; Financial crisis; Monetary economics; Business; Econometrics; Macroeconomics","score_opus":0.04228754481987424,"score_gpt":0.2643801384166022,"score_spread":0.22209259359672795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062121708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9690983,0.00026584804,0.0006218421,0.0020287877,0.0011455792,0.00024793268,0.000103242084,0.00006796275,0.026420498],"genre_scores_gemma":[0.9958157,0.00015114826,0.0023199231,0.0006513465,0.0008781824,0.000019649695,0.000008066467,0.0000423551,0.0001136542],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979142,0.000016220316,0.00083735713,0.00077368756,0.00004177103,0.000416749],"domain_scores_gemma":[0.9987538,0.00022193136,0.00034800952,0.000502487,0.000046942896,0.0001268715],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00060503505,0.0002659811,0.00051738566,0.00020963213,0.00029233747,0.00027153047,0.0003215985,0.00024787453,0.0004305018],"category_scores_gemma":[0.0003015596,0.00031952877,0.00009876372,0.00018801718,0.00028554612,0.0003466369,0.00011748878,0.00039691397,0.00032017418],"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":[0.000034590244,0.00008407716,0.6941157,0.000018545823,0.000018697858,0.0000013015319,0.0005339785,0.000062241255,0.0000053166764,0.30220908,0.0003005841,0.002615866],"study_design_scores_gemma":[0.00070671627,0.000069194386,0.7849318,0.000012444784,0.0000032166402,0.000010742119,0.000027346863,0.002390549,0.00015655669,0.15462403,0.056569766,0.0004976278],"about_ca_topic_score_codex":0.000103714,"about_ca_topic_score_gemma":0.00050455425,"teacher_disagreement_score":0.14758503,"about_ca_system_score_codex":0.00017547673,"about_ca_system_score_gemma":0.00007388024,"threshold_uncertainty_score":0.9999257},"labels":[],"label_agreement":null},{"id":"W2068041678","doi":"10.1007/s001819900012","title":"Using the cost function to generate Marshallian demand systems","year":2000,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"Context (archaeology); Demand curve; Function (biology); Representation (politics); Computer science; Observable; On demand; Mathematical optimization; Economics; Mathematical economics; Microeconomics; Mathematics","score_opus":0.0947344320285674,"score_gpt":0.2623496898565987,"score_spread":0.16761525782803127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068041678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9171777,0.0016125728,0.0024536154,0.0032268919,0.001218756,0.00070529326,0.00016477332,0.00006041606,0.07338002],"genre_scores_gemma":[0.9861534,0.0006404297,0.0006602207,0.0058108876,0.0010692741,0.00007943212,0.0000350529,0.000054488497,0.005496764],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980547,0.000030650193,0.0008230325,0.00060706836,0.000019731928,0.00046483555],"domain_scores_gemma":[0.9989529,0.000067693196,0.00022195581,0.00049139967,0.000024416131,0.00024159768],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00063967134,0.0002563317,0.00047356478,0.0001033177,0.00028321234,0.00035389155,0.00039398173,0.00018066158,0.0010351911],"category_scores_gemma":[0.000021583019,0.00022696867,0.00017058414,0.00017553089,0.000049075985,0.0003142903,0.00006790534,0.00020255479,0.002790754],"study_design_candidate":"not_applicable","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":[0.00070804945,0.0005259913,0.06805055,0.000088496774,0.0010485973,0.00001471598,0.0015280198,0.46132845,0.000090592905,0.29214334,0.15585102,0.018622175],"study_design_scores_gemma":[0.00047499125,0.000110504225,0.013882068,0.00001007764,0.000021386015,0.000023106233,0.00008054132,0.031468153,0.000018785555,0.007833177,0.9455374,0.00053981977],"about_ca_topic_score_codex":0.00014371969,"about_ca_topic_score_gemma":0.00006874418,"teacher_disagreement_score":0.7896864,"about_ca_system_score_codex":0.00026743888,"about_ca_system_score_gemma":0.000027939632,"threshold_uncertainty_score":0.999878},"labels":[],"label_agreement":null},{"id":"W2073091282","doi":"10.1007/s00181-012-0597-x","title":"Inventories and antidumping: the case of orange juice trade","year":2012,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":4,"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":"Orange juice; Economics; Victory; International economics; International trade; Chemistry; Food science","score_opus":0.1569400163123663,"score_gpt":0.27050947835523537,"score_spread":0.11356946204286908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073091282","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9781711,0.0032327925,0.00006614018,0.0029410087,0.00057776185,0.00014278232,0.00015147513,0.0000202067,0.014696725],"genre_scores_gemma":[0.99753946,0.00057335955,0.00032748855,0.0011725698,0.00027057345,0.000008894756,0.0000058239725,0.000022554084,0.00007926788],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.998634,0.000017191433,0.0006784576,0.00026742404,0.0000086500695,0.00039430687],"domain_scores_gemma":[0.9990254,0.00012953723,0.000319374,0.0003404082,0.0000062934746,0.00017899403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059111876,0.00017131494,0.00043564587,0.00007879833,0.00012916928,0.000058434147,0.00019499744,0.00012734458,0.0001294797],"category_scores_gemma":[0.00007172989,0.00016431672,0.00012212733,0.000107400185,0.00020631017,0.00043709393,0.00009434997,0.00015640652,0.00011696168],"study_design_candidate":"not_applicable","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":[0.000021543075,0.00014362583,0.40313512,0.000047956095,0.00011222586,0.000009049423,0.0024018348,0.000054992914,0.0000031603486,0.5891642,0.003694338,0.0012119751],"study_design_scores_gemma":[0.0014814413,0.00016574832,0.15065725,0.000014694069,0.000056655404,0.0010875298,0.0019524274,0.0046019256,0.0003330698,0.099210024,0.73948675,0.00095249026],"about_ca_topic_score_codex":0.00023281694,"about_ca_topic_score_gemma":0.00008357876,"teacher_disagreement_score":0.7357924,"about_ca_system_score_codex":0.00007416055,"about_ca_system_score_gemma":0.000014877934,"threshold_uncertainty_score":0.67006415},"labels":[],"label_agreement":null},{"id":"W2078574451","doi":"10.1007/s001810100111","title":"The symmetry of the wage-change distribution: Survey and contract data","year":2002,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":8,"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 Guelph","funders":"","keywords":"Wage; Survey data collection; Parametric statistics; Distribution (mathematics); Symmetry (geometry); Economics; Econometrics; Private sector; Labour economics; Mathematics; Statistics; Economic growth","score_opus":0.18179445850134768,"score_gpt":0.2847899693316491,"score_spread":0.1029955108303014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078574451","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97819805,0.002871053,0.00015153989,0.007287652,0.000667857,0.0002421647,0.008301178,0.0000118991875,0.0022686205],"genre_scores_gemma":[0.99645066,0.0023395391,0.000025675547,0.0007027521,0.0001172828,0.000008184271,0.00011598472,0.00001441728,0.00022548463],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856687,0.00007991236,0.00068551925,0.00038922927,0.000025359106,0.00025309212],"domain_scores_gemma":[0.99758285,0.00073577836,0.0004217468,0.0011498982,0.00003225897,0.00007747585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00196441,0.00013594575,0.00033553902,0.000019909114,0.00022937238,0.00011310572,0.0007728345,0.00010573398,0.00009819744],"category_scores_gemma":[0.00083270343,0.00009767643,0.00007542863,0.00016144982,0.00022461165,0.00022318256,0.00047253747,0.00019110719,0.00003536894],"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":[0.000016593849,0.00007777093,0.7562362,0.000009631467,0.00006140455,4.6834464e-7,0.00008281867,0.0000030710548,1.3049812e-7,0.23505989,0.0025342135,0.005917828],"study_design_scores_gemma":[0.00032726506,0.000020454625,0.8363826,0.0000038928956,0.000005747928,0.0000025827128,0.000012477008,0.027485974,0.0000015721026,0.027961621,0.10762647,0.00016933215],"about_ca_topic_score_codex":0.00059482607,"about_ca_topic_score_gemma":0.00066121767,"teacher_disagreement_score":0.20709826,"about_ca_system_score_codex":0.0000706591,"about_ca_system_score_gemma":0.000011557412,"threshold_uncertainty_score":0.39831293},"labels":[],"label_agreement":null},{"id":"W2079059798","doi":"10.1007/s00181-003-0189-x","title":"Simulation-based inference in dynamic panel probit models: An application to health","year":2004,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Global Health Care Issues","field":"Health Professions","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; McMaster University Medical Centre","funders":"","keywords":"Probit model; Econometrics; Inference; Probit; British Household Panel Survey; Panel data; Economics; Statistics; Mathematics; Computer science","score_opus":0.17903833927140028,"score_gpt":0.5058441467391297,"score_spread":0.3268058074677294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079059798","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8264392,0.000048779544,0.14820804,0.021723542,0.0002287621,0.0025823074,0.00006497324,0.00019090412,0.0005134855],"genre_scores_gemma":[0.97017676,0.000014115684,0.0067422944,0.022490285,0.000076414486,0.00032481592,0.00011565563,0.000033021814,0.000026648631],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99756086,0.00021596356,0.0009354419,0.0005293468,0.0000935008,0.00066491234],"domain_scores_gemma":[0.9977945,0.00084264536,0.00024321798,0.0005074586,0.00011621702,0.0004959278],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00064523355,0.00018405131,0.00037636468,0.00017491402,0.00027307935,0.000012678404,0.00025841637,0.00022944406,0.000028905237],"category_scores_gemma":[0.00029459829,0.0002011989,0.00003558748,0.00028325466,0.000028689243,0.00024298056,0.00006494477,0.0004387732,0.0008067949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049243205,0.00012196451,0.0064845346,0.00008653244,0.0000013796453,3.6541786e-7,0.0023943991,0.9858913,0.0000010395108,0.0029814024,0.00004239181,0.0019454932],"study_design_scores_gemma":[0.0009333352,0.00020759527,0.021344494,0.00011274973,0.0000018043544,6.5374124e-8,0.0004497141,0.9479588,0.0000011449397,0.024933703,0.003845116,0.00021145256],"about_ca_topic_score_codex":0.0028072582,"about_ca_topic_score_gemma":0.018410215,"teacher_disagreement_score":0.14373754,"about_ca_system_score_codex":0.0031134812,"about_ca_system_score_gemma":0.0020964656,"threshold_uncertainty_score":0.9999712},"labels":[],"label_agreement":null},{"id":"W2088173867","doi":"10.1007/s00181-015-0939-6","title":"Biases in consumer elasticities based on micro and aggregate data: an integrated framework and empirical evaluation","year":2015,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economics of Agriculture and Food Markets","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Econometrics; Economics; Elasticity (physics); Aggregate (composite); Inequality; Income elasticity of demand; Price elasticity of demand; Range (aeronautics); Aggregate data; Microeconomics; Statistics; Mathematics","score_opus":0.231838833554093,"score_gpt":0.3407213109226676,"score_spread":0.10888247736857462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088173867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99090123,0.0020118915,0.00026748012,0.0027139662,0.0003579814,0.00032951028,0.0004687089,0.000037207916,0.0029120368],"genre_scores_gemma":[0.9913948,0.0005302658,0.004150436,0.003246836,0.00015983237,0.000030791874,0.00039936817,0.00003573888,0.000051930634],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977458,0.0000869452,0.0007836982,0.00096678495,0.000037723974,0.00037904148],"domain_scores_gemma":[0.9980444,0.00063458696,0.00029277467,0.000614228,0.000054883807,0.00035913405],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017192716,0.00029867634,0.00061147683,0.00031394392,0.000074514515,0.00024956386,0.0003190104,0.0003063709,0.00008632729],"category_scores_gemma":[0.0014691078,0.00030348945,0.00004246256,0.00015343417,0.00019655752,0.000661815,0.00016699426,0.00036268317,0.00009006354],"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":[0.0009755042,0.0010739238,0.93672967,0.00006091464,0.00019667661,0.000018726825,0.0021971655,0.010052086,0.0000049792943,0.013087113,0.020781303,0.014821961],"study_design_scores_gemma":[0.0044302624,0.00092493667,0.17784224,0.00014492465,0.000059200043,0.000024130204,0.00092125003,0.6438675,0.000044749693,0.07112168,0.09926104,0.0013581217],"about_ca_topic_score_codex":0.00012375087,"about_ca_topic_score_gemma":0.00037670365,"teacher_disagreement_score":0.7588874,"about_ca_system_score_codex":0.0002460621,"about_ca_system_score_gemma":0.00015464339,"threshold_uncertainty_score":0.9999417},"labels":[],"label_agreement":null},{"id":"W2089089349","doi":"10.1007/s00181-006-0060-y","title":"Does Trade Openness Affect the Speed of Output Convergence? Some Empirical Evidence","year":2006,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":17,"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 Victoria","funders":"","keywords":"Openness to experience; Convergence (economics); Econometrics; Economics; Nonparametric statistics; Regression; Kernel (algebra); Rate of convergence; Mathematics; Statistics; Computer science; Macroeconomics; Psychology","score_opus":0.10461661260711752,"score_gpt":0.28298284045604283,"score_spread":0.1783662278489253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089089349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96888965,0.0016604062,0.0003274115,0.021608066,0.001923425,0.00049107196,0.00020633181,0.000052297208,0.004841353],"genre_scores_gemma":[0.995812,0.00038990975,0.0002208827,0.0014175212,0.00092209183,0.000023085484,0.000015911535,0.000044750952,0.0011538311],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969287,0.00008735734,0.0014086295,0.0009382263,0.00004145637,0.0005956458],"domain_scores_gemma":[0.99743646,0.0007043943,0.00075339625,0.00092167006,0.00002273737,0.00016131214],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015734924,0.00035420206,0.00095862296,0.00016673144,0.00018868293,0.00012062354,0.00087645964,0.00023009584,0.00044749968],"category_scores_gemma":[0.00033126195,0.00025822708,0.00040189663,0.00022080152,0.00042803772,0.00084821926,0.00020008747,0.00035812912,0.0005753607],"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":[0.00011829895,0.00028959813,0.89143574,0.00008589456,0.000105351486,0.0000047562844,0.00041547735,0.0011801382,0.000039294388,0.08963408,0.016084194,0.00060718955],"study_design_scores_gemma":[0.0010627753,0.0002139482,0.64402336,0.00003666449,0.000037399834,0.000019247958,0.000111443296,0.008382302,0.0023041386,0.23921676,0.10360449,0.0009874924],"about_ca_topic_score_codex":0.00049797114,"about_ca_topic_score_gemma":0.00012823108,"teacher_disagreement_score":0.2474124,"about_ca_system_score_codex":0.0002085106,"about_ca_system_score_gemma":0.00010470902,"threshold_uncertainty_score":0.999987},"labels":[],"label_agreement":null},{"id":"W2093821076","doi":"10.1007/s00181-006-0063-8","title":"An Eclectic Approach to Estimating U.S. Potential GDP","year":2006,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Potential output; Econometrics; Economics; Productivity; Vector autoregression; Multivariate statistics; Monte Carlo method; Output gap; Unemployment rate; Real gross domestic product; Unemployment; Structural vector autoregression; Mathematics; Statistics; Interest rate; Macroeconomics; Monetary policy","score_opus":0.07635855174901422,"score_gpt":0.2615861795227997,"score_spread":0.18522762777378549,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093821076","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9071215,0.00010367134,0.054583922,0.0010375576,0.00064439385,0.0002605081,0.00018092766,0.00010437146,0.035963144],"genre_scores_gemma":[0.95232666,0.0000049307264,0.04351563,0.0019556955,0.0012768854,0.000029150908,0.00008586894,0.000059500588,0.0007456593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974867,0.000021424785,0.0009851828,0.00081466616,0.000018926723,0.00067308143],"domain_scores_gemma":[0.998734,0.000036828715,0.00028548247,0.0006029427,0.000008264938,0.00033247872],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005087571,0.0002875427,0.0005844011,0.0002908331,0.00021132194,0.00026101127,0.00043349597,0.00017736897,0.00038043875],"category_scores_gemma":[0.000047128204,0.00036612325,0.00018583702,0.00013798702,0.000058121714,0.0005664395,0.00007319782,0.00020733017,0.002532041],"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":[0.000036914764,0.00039622653,0.030773245,0.000018192473,0.000037850292,0.0000017627062,0.00029111604,0.9254789,0.000012080665,0.02960963,0.012654176,0.000689911],"study_design_scores_gemma":[0.00050366746,0.00012553105,0.033401776,0.0000026003179,0.000008063891,0.000027921164,0.00002580989,0.88982743,0.000028323213,0.057519652,0.017955404,0.0005738325],"about_ca_topic_score_codex":0.0014474342,"about_ca_topic_score_gemma":0.000036566413,"teacher_disagreement_score":0.045205176,"about_ca_system_score_codex":0.0002736233,"about_ca_system_score_gemma":0.000025903162,"threshold_uncertainty_score":0.99987906},"labels":[],"label_agreement":null},{"id":"W2094955313","doi":"10.1007/s001810100115","title":"New directions in business cycle research and financial analysis","year":2002,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":71,"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","funders":"","keywords":"Variety (cybernetics); State space; Econometrics; Inference; Computer science; Business cycle; Markov chain; Autoregressive conditional heteroskedasticity; Section (typography); Mathematical economics; Economics; Mathematics; Artificial intelligence; Statistics; Machine learning; Macroeconomics; Volatility (finance)","score_opus":0.21221541889077286,"score_gpt":0.3160288153524136,"score_spread":0.10381339646164076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094955313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9630392,0.0013842594,0.0005743642,0.006213384,0.00022149306,0.00013939841,0.00008637237,0.000027594264,0.028313886],"genre_scores_gemma":[0.99273336,0.0019449048,0.0006752733,0.00056170416,0.00029089279,0.000013223984,0.0000112566195,0.000020443018,0.003748942],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99815917,0.000023587678,0.00068656384,0.00058228587,0.000017438042,0.00053096906],"domain_scores_gemma":[0.9990933,0.00015785154,0.00012529582,0.0003670317,0.000011991314,0.00024454217],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00061060773,0.00016129685,0.0005675367,0.0011189998,0.00015832769,0.00012965634,0.00020443952,0.00017326481,0.002351404],"category_scores_gemma":[0.00021197922,0.0002065919,0.00011135604,0.0011316687,0.00010025371,0.0003716041,0.00009426698,0.0002893017,0.0011339589],"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":[0.000058251615,0.00043191866,0.86302495,0.000024001993,0.00025625477,0.000011399554,0.0025881396,0.03268252,0.0000010243903,0.054229207,0.034011003,0.012681355],"study_design_scores_gemma":[0.0008252702,0.00006941452,0.55395895,0.0000046194427,0.00001725166,0.000006936588,0.000032578755,0.14463295,0.0000043985488,0.075280696,0.22474416,0.00042277135],"about_ca_topic_score_codex":0.0036208043,"about_ca_topic_score_gemma":0.0014979182,"teacher_disagreement_score":0.30906597,"about_ca_system_score_codex":0.00022907034,"about_ca_system_score_gemma":0.000020671057,"threshold_uncertainty_score":0.9996438},"labels":[],"label_agreement":null},{"id":"W2111695214","doi":"10.1007/s00181-014-0873-z","title":"The stock market and the consumer confidence channel: evidence from Canada","year":2014,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Consumer confidence index; Economics; Stock (firearms); Stock market; Volatility (finance); Unemployment; Monetary economics; Pessimism; Financial economics; Macroeconomics","score_opus":0.03489492195918552,"score_gpt":0.2345959021466685,"score_spread":0.199700980187483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111695214","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93295425,0.007016126,0.0033951069,0.033029675,0.0013791044,0.00054209196,0.00030557008,0.000029270352,0.021348823],"genre_scores_gemma":[0.9935382,0.0024272408,0.000077950936,0.0027652327,0.00013974533,0.000034801546,0.000004493585,0.00001869883,0.0009936608],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833095,0.00011522256,0.0006805777,0.00049750856,0.00003481034,0.000340916],"domain_scores_gemma":[0.99472904,0.0040475684,0.00035353246,0.0006938457,0.000031919415,0.00014411198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021835973,0.00019171771,0.00043871556,0.000023342962,0.00040701078,0.00023668708,0.0005173439,0.00008933927,0.00027393427],"category_scores_gemma":[0.0013855038,0.0001383088,0.00008648316,0.00006772069,0.00042879095,0.00014223017,0.0001943559,0.0002593416,0.00002171801],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000575748,0.000038102793,0.78245074,0.00003176743,0.00025031995,0.0000018247277,0.00049565145,0.00008295728,3.474248e-7,0.14898975,0.058642402,0.008440391],"study_design_scores_gemma":[0.00058324664,0.000017352684,0.11111046,0.000009786021,0.000009107828,0.0000020812213,0.000034639474,0.5611802,0.0000011057823,0.12708162,0.19974501,0.0002254118],"about_ca_topic_score_codex":0.24029975,"about_ca_topic_score_gemma":0.33017942,"teacher_disagreement_score":0.6713403,"about_ca_system_score_codex":0.00014877695,"about_ca_system_score_gemma":0.0001261745,"threshold_uncertainty_score":0.7647592},"labels":[],"label_agreement":null},{"id":"W2119382189","doi":"10.1007/s00181-011-0488-6","title":"Channels of risk-sharing among Canadian provinces: 1961–2006","year":2011,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Vancouver Island University","funders":"","keywords":"Pairwise comparison; Rest (music); Economics; Product (mathematics); Smoothing; Capital market; Capital (architecture); Financial economics; Econometrics; Geography; Finance; Computer science","score_opus":0.0553950461570046,"score_gpt":0.27623026505906445,"score_spread":0.22083521890205984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119382189","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8778723,0.000028603841,0.0000075237117,0.0008440409,0.00026641713,0.00012895964,0.0002729048,0.000014516841,0.12056474],"genre_scores_gemma":[0.99643564,0.00007228463,0.00009568459,0.0009984683,0.00028601137,0.0000071240497,0.0000019288748,0.000010704794,0.0020921594],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990747,0.000033548775,0.00022111145,0.000207698,0.00005162335,0.00041129993],"domain_scores_gemma":[0.999086,0.000057752368,0.00017268906,0.00018421948,0.000025485284,0.0004738592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031856415,0.00008299663,0.00016079907,0.00008451449,0.00022496097,0.0000329223,0.00035584447,0.00011737193,0.00040019274],"category_scores_gemma":[0.00023446322,0.000095384195,0.00007233509,0.00011643628,0.00029451304,0.00020547856,0.00002758236,0.00011969679,0.000060141418],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016306949,0.000045843688,0.8078929,0.0000128725715,0.000040973016,0.000010006291,0.061890543,0.0001178401,4.0345233e-7,0.096589096,0.027632644,0.00575056],"study_design_scores_gemma":[0.00026235843,0.00004044999,0.36620286,0.000023978446,0.00001987263,7.9168615e-7,0.0011312458,0.0005377306,0.0001081467,0.027413728,0.60385674,0.00040206252],"about_ca_topic_score_codex":0.98630464,"about_ca_topic_score_gemma":0.9943625,"teacher_disagreement_score":0.57622415,"about_ca_system_score_codex":0.00044396202,"about_ca_system_score_gemma":0.00097216544,"threshold_uncertainty_score":0.438183},"labels":[],"label_agreement":null},{"id":"W2121246556","doi":"10.1007/s00181-012-0656-3","title":"Import price dynamics in major advanced economies and heterogeneity in exchange rate pass-through","year":2012,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Exchange-rate pass-through; Economics; Exchange rate; Monetary economics; Degree (music); International economics","score_opus":0.08370633205391886,"score_gpt":0.282914500437291,"score_spread":0.19920816838337213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121246556","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.982794,0.0020004439,0.00013324013,0.00202989,0.0005297338,0.00037849162,0.00028561207,0.000032095675,0.011816478],"genre_scores_gemma":[0.9938212,0.0020040858,0.0011555407,0.0023114434,0.00021229683,0.000071368944,0.00005952245,0.00005600984,0.00030851082],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968221,0.000046946512,0.0013734619,0.00069981825,0.00001272833,0.0010449446],"domain_scores_gemma":[0.99860275,0.00017641242,0.00046238277,0.00047459238,0.0000043393557,0.00027952777],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012261075,0.0003805109,0.0009431472,0.000355595,0.00007751639,0.000084006606,0.0002624495,0.0002783398,0.0003454012],"category_scores_gemma":[0.00010156517,0.00048800078,0.0001366685,0.00014284294,0.00012057312,0.0016270753,0.00018963682,0.0003369351,0.00046797754],"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":[0.00007748868,0.00016716373,0.9815773,0.000046159807,0.000034530254,0.0000033334845,0.00090134103,0.0016624301,0.0000013990485,0.014498546,0.00024949427,0.0007808312],"study_design_scores_gemma":[0.0029329278,0.00011220314,0.83005184,0.000018323484,0.000007832658,0.000029524668,0.0002879285,0.084952176,0.00006212464,0.02567205,0.054786,0.0010870455],"about_ca_topic_score_codex":0.0010891097,"about_ca_topic_score_gemma":0.0026308626,"teacher_disagreement_score":0.15152542,"about_ca_system_score_codex":0.0012059836,"about_ca_system_score_gemma":0.000027178328,"threshold_uncertainty_score":0.9997572},"labels":[],"label_agreement":null},{"id":"W2139552401","doi":"10.1007/s00181-006-0095-0","title":"Evaluating multi-treatment programs: theory and evidence from the U.S. Job Training Partnership Act experiment","year":2007,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Benchmark (surveying); General partnership; Computer science; Sample (material); Training (meteorology); Work (physics); Operations research; Business; Finance; Mathematics; Engineering","score_opus":0.6798412018231792,"score_gpt":0.5532420723404441,"score_spread":0.1265991294827351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139552401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9667088,0.0007449009,0.030843372,0.00045353884,0.000051839328,0.0006469123,0.0000024361532,0.00021649418,0.00033173396],"genre_scores_gemma":[0.84053785,0.00012345154,0.15849592,0.00043205055,0.00015098942,0.00013004948,0.0000032737732,0.00003457182,0.00009184958],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99840564,0.0002176302,0.00047551145,0.00040983091,0.00009711922,0.00039426298],"domain_scores_gemma":[0.9926596,0.00651166,0.00020634547,0.00044765524,0.000034915673,0.00013980034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026105687,0.00024915332,0.0003149821,0.000027151294,0.00015758006,0.000091473856,0.0002239529,0.00011467409,0.00004869015],"category_scores_gemma":[0.0014676052,0.00017148379,0.00008551718,0.00005399438,0.0001979112,0.00021010576,0.00011014252,0.00018207743,0.000011402188],"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":[0.0004784749,0.00048230565,0.050523687,0.000033313925,0.00027752694,0.000017963814,0.074283406,0.000078866426,0.0017817068,0.05935199,0.00018100155,0.8125098],"study_design_scores_gemma":[0.0024309286,0.0023250475,0.019615492,0.0007893245,0.000309419,0.000033746113,0.024205606,0.0110810185,0.043745786,0.88943285,0.004461857,0.0015689327],"about_ca_topic_score_codex":0.000038153838,"about_ca_topic_score_gemma":0.00019360856,"teacher_disagreement_score":0.83008087,"about_ca_system_score_codex":0.00036671097,"about_ca_system_score_gemma":0.0001001582,"threshold_uncertainty_score":0.6992906},"labels":[],"label_agreement":null},{"id":"W2140111038","doi":"10.1007/s00181-011-0502-z","title":"Dynamic price dependence of Canadian and international art markets: an empirical analysis","year":2011,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Art History and Market Analysis","field":"Arts and Humanities","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Economics; Index (typography); Mainstream; Art market; Painting; Price index; Granger causality; Financial economics; Linkage (software); Econometrics; History; Art history; Political science; Law","score_opus":0.057912329014562745,"score_gpt":0.2591180722311181,"score_spread":0.20120574321655535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140111038","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6943059,0.000041266667,0.00014266322,0.0006334333,0.0002224773,0.000056553024,0.00008339715,0.000021525784,0.3044928],"genre_scores_gemma":[0.9881666,0.000115353796,0.00083435257,0.00077651214,0.000061817256,0.000005291887,0.00006118251,0.0000117709105,0.009967129],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990684,0.000052494383,0.0003407518,0.0002927648,0.00005322821,0.00019237769],"domain_scores_gemma":[0.99925697,0.000054803004,0.0001252939,0.00023088286,0.00007091249,0.0002611205],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002741938,0.00012688048,0.00027931103,0.00083892205,0.00016146405,0.00004655232,0.0002446517,0.000063713116,0.010033759],"category_scores_gemma":[0.0000340114,0.00012640108,0.00014684701,0.00012139975,0.00026493563,0.00037220016,0.000050527724,0.00010463359,0.000057619927],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007554621,0.0010858716,0.6849197,0.000068329704,0.0076801805,0.00006517738,0.15831184,0.00023011862,0.0000100056695,0.07264897,0.052211102,0.022013221],"study_design_scores_gemma":[0.00022848528,0.00010514708,0.08163014,0.0000044372314,0.0005854435,0.000004991898,0.0021159216,0.033975195,0.000003752582,0.0029871764,0.87798,0.00037934433],"about_ca_topic_score_codex":0.007601169,"about_ca_topic_score_gemma":0.5332102,"teacher_disagreement_score":0.8257689,"about_ca_system_score_codex":0.00012862938,"about_ca_system_score_gemma":0.0001088137,"threshold_uncertainty_score":0.9990073},"labels":[],"label_agreement":null},{"id":"W2144471233","doi":"10.1007/s00181-013-0792-4","title":"Macroeconomic news surprises and volatility spillover in foreign exchange markets","year":2014,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Volatility (finance); Economics; Spillover effect; Volatility swap; Foreign exchange; Monetary economics; Volatility smile; Forward volatility; Implied volatility; Volatility risk premium; Impulse response; Econometrics; Financial economics; Macroeconomics; Mathematics","score_opus":0.03029730378234962,"score_gpt":0.24120345273939192,"score_spread":0.2109061489570423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144471233","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8912575,0.00036821657,0.0010422071,0.00077474676,0.0002706418,0.00028124874,0.00013116303,0.00003356489,0.10584069],"genre_scores_gemma":[0.99671507,0.0005143471,0.00066108897,0.0012000471,0.00013838311,0.00002715421,0.000025336814,0.0000410251,0.00067752745],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974245,0.00006193824,0.0010862468,0.0008909643,0.00001922119,0.0005171577],"domain_scores_gemma":[0.9985103,0.00030009134,0.00034621803,0.0006021524,0.000015732707,0.00022552411],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0015912335,0.00030199526,0.000782698,0.00024937137,0.00008331753,0.00012996729,0.00028001165,0.0002374851,0.0011629976],"category_scores_gemma":[0.0002825197,0.00036965928,0.00014935309,0.00012213072,0.0001380747,0.00036516177,0.00021637244,0.00026427902,0.00009472804],"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":[0.00006727206,0.00006834581,0.97843814,0.000042978132,0.000017938459,8.716257e-7,0.000097616256,0.000008272744,2.7132285e-7,0.015183022,0.0008215256,0.005253771],"study_design_scores_gemma":[0.00069961086,0.000037738046,0.49240378,0.000005135794,0.0000026566313,0.0000025808245,0.000018007195,0.30938172,0.0000016206359,0.11076158,0.086376324,0.00030923996],"about_ca_topic_score_codex":0.0006254922,"about_ca_topic_score_gemma":0.0014139339,"teacher_disagreement_score":0.48603433,"about_ca_system_score_codex":0.00026518252,"about_ca_system_score_gemma":0.00002641281,"threshold_uncertainty_score":0.99987555},"labels":[],"label_agreement":null},{"id":"W2147071066","doi":"10.1007/s00181-010-0429-9","title":"Nowcasting norwegian GDP: the role of asset prices in a small open economy","year":2010,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":81,"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":"Universitetet i Oslo; World Bank Group","keywords":"Nowcasting; Economics; Small open economy; Asset (computer security); Econometrics; Dynamic factor; Stock (firearms); Stock exchange; Panel data; Real gross domestic product; Monetary economics; Norwegian; Quarter (Canadian coin); Financial economics; Exchange rate; Finance; Geography; Computer science","score_opus":0.10263704626622956,"score_gpt":0.27308843792809734,"score_spread":0.1704513916618678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147071066","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8729738,0.00013460343,0.00007084076,0.0023511301,0.0003097204,0.00039242944,0.0001737535,0.000013557367,0.12358018],"genre_scores_gemma":[0.9958075,0.000050049883,0.0020673699,0.001434445,0.00025663507,0.00004684274,0.000020585785,0.00003816015,0.00027836952],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975515,0.00001888851,0.0013005562,0.0005822382,0.0000069066236,0.0005399017],"domain_scores_gemma":[0.99799496,0.00031581274,0.00076413044,0.00074761047,0.000010914036,0.00016654817],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013820333,0.0002588639,0.00073867105,0.00024147981,0.00012430512,0.0002533424,0.0013646865,0.00021398727,0.0009491907],"category_scores_gemma":[0.0001891819,0.0002578922,0.00017802944,0.0001507784,0.00015746625,0.0006086045,0.00041317916,0.00054583506,0.00063502596],"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":[0.00007666385,0.00028016887,0.6764664,0.000030189172,0.00010623492,0.0000022734832,0.0020257353,0.004437705,0.000039961422,0.30954868,0.0011487053,0.0058373087],"study_design_scores_gemma":[0.0013509571,0.0001218639,0.09198774,0.00001341981,0.00001083308,0.000023799952,0.00036547956,0.0911513,0.00033458153,0.38853583,0.42538038,0.00072382577],"about_ca_topic_score_codex":0.003055678,"about_ca_topic_score_gemma":0.004632871,"teacher_disagreement_score":0.5844786,"about_ca_system_score_codex":0.000107677784,"about_ca_system_score_gemma":0.00007231233,"threshold_uncertainty_score":0.9999873},"labels":[],"label_agreement":null},{"id":"W2149657862","doi":"10.1007/s001810200140","title":"Employer-supported training in Canada and its impact on mobility and wages","year":2003,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Receipt; Wage; Training (meteorology); Demographic economics; Psychology; Hazard; Wage growth; Affect (linguistics); Economics; Labour economics; Accounting; Geography","score_opus":0.04917882070245145,"score_gpt":0.27389053118768636,"score_spread":0.22471171048523492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149657862","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939332,0.0003175245,0.000015412015,0.0005313387,0.00016966519,0.00016744487,0.0003354863,0.000010701373,0.0045192055],"genre_scores_gemma":[0.99874854,0.0003008455,0.00006327721,0.0007529622,0.000021052016,0.00001118489,0.000009633119,0.000021372804,0.00007115737],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983744,0.00004334545,0.00065727637,0.00052933453,0.000019459862,0.00037620284],"domain_scores_gemma":[0.99912506,0.00023722925,0.00018085155,0.0002324846,0.000012939395,0.00021142345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008626767,0.00020837889,0.0005337847,0.00010279076,0.00005756122,0.000057950354,0.00009559084,0.00009668268,0.00017778749],"category_scores_gemma":[0.000293425,0.00021863688,0.000052675365,0.000116644456,0.00003461886,0.00014393288,0.000037352285,0.00021604073,0.00000858513],"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":[0.000029936566,0.000050071994,0.896815,0.000017713235,0.00003279569,0.000009126328,0.0003510103,0.00044866593,0.0000010254403,0.10116217,0.000048297414,0.0010341859],"study_design_scores_gemma":[0.0008131042,0.00008105304,0.86585325,0.000007938475,0.0000034709226,0.000008899726,0.00016021711,0.009926055,0.00001629854,0.1184048,0.0042899665,0.00043494484],"about_ca_topic_score_codex":0.15255694,"about_ca_topic_score_gemma":0.42837003,"teacher_disagreement_score":0.27581307,"about_ca_system_score_codex":0.00062521594,"about_ca_system_score_gemma":0.00037421196,"threshold_uncertainty_score":0.89157534},"labels":[],"label_agreement":null},{"id":"W2154776903","doi":"10.1007/s00181-006-0092-3","title":"The impact of unionization on the incidence of and sources of payment for training in Canada","year":2006,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Seniority; Payment; Nonunion; Training (meteorology); Variety (cybernetics); Human capital; Labour economics; Business; Control (management); Demographic economics; Capital (architecture); Incidence (geometry); Economics; Economic growth; Finance; Political science; Medicine; Management; Geography","score_opus":0.038339361987861774,"score_gpt":0.25817301955738414,"score_spread":0.21983365756952236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154776903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997876,0.00014105579,0.00021049545,0.00070604385,0.000039613406,0.00014230901,0.00024051078,8.309251e-7,0.0006431255],"genre_scores_gemma":[0.99975336,0.00010851117,0.000044905522,0.00004786427,0.000014666045,0.0000066135117,0.0000049442506,0.0000058569585,0.000013280444],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991334,0.000017944254,0.0006076519,0.0001147523,0.000014694803,0.0001115256],"domain_scores_gemma":[0.99867785,0.0006739254,0.00045858556,0.00014816436,0.000024842448,0.000016637148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007488795,0.00006445271,0.00023864402,0.000036934693,0.00003713511,0.000010460992,0.00012422583,0.000028245748,0.0000067334845],"category_scores_gemma":[0.00016028424,0.0000445626,0.00005287726,0.00008492761,0.00006210717,0.00003389249,0.000024250641,0.00004501994,9.5430785e-8],"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":[0.000035539273,0.00002229376,0.6425208,0.000011681525,0.000018815628,6.923558e-8,0.00023446309,0.019398276,0.000002255094,0.33666152,0.000041556086,0.0010527527],"study_design_scores_gemma":[0.0003222789,0.00009529794,0.690774,0.0000128339825,0.0000022931977,3.1998766e-7,0.00026177004,0.079497315,0.00008736692,0.22845258,0.00040337807,0.00009056567],"about_ca_topic_score_codex":0.3532419,"about_ca_topic_score_gemma":0.30218324,"teacher_disagreement_score":0.10820895,"about_ca_system_score_codex":0.00020182623,"about_ca_system_score_gemma":0.00021671611,"threshold_uncertainty_score":0.71055007},"labels":[],"label_agreement":null},{"id":"W2159978532","doi":"10.1007/s00181-009-0315-5","title":"Are sports teams multiproduct firms?","year":2009,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":7,"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 Victoria","funders":"","keywords":"Economics; Production (economics); Econometrics; Context (archaeology); Aggregate (composite); Estimation; Scope (computer science); Function (biology); Microeconomics; Economies of scope; Economies of scale; Substitution (logic); Computer science","score_opus":0.04443008229496645,"score_gpt":0.2565287068317177,"score_spread":0.21209862453675124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159978532","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9607149,0.000692613,0.0002498818,0.0057959235,0.00064791203,0.00014751541,0.00006461282,0.00007264186,0.031613994],"genre_scores_gemma":[0.990395,0.000452511,0.00041988638,0.005548622,0.00052559195,0.0000044912153,0.000018950175,0.00002552859,0.0026093896],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981254,0.000003284539,0.0007980407,0.00062437,0.000028040085,0.00042086703],"domain_scores_gemma":[0.9985471,0.000018208832,0.00064117,0.000584021,0.000024817884,0.00018473441],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003912527,0.00022708542,0.0005446099,0.00017261921,0.00012084926,0.00009984917,0.0002784642,0.00014228874,0.0011105133],"category_scores_gemma":[0.00007130598,0.00025330592,0.00019439848,0.0001613658,0.000051820753,0.00028360751,0.00003772124,0.00021479686,0.00090272364],"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":[0.000031046446,0.00029623156,0.9259667,0.000012243513,0.00003839623,0.000023769271,0.00024430396,0.004471723,0.0000013182628,0.038395602,0.022615131,0.0079035815],"study_design_scores_gemma":[0.000319462,0.000049660383,0.5274967,0.0000074685895,0.0000044060343,0.000008598207,0.00003178803,0.015446457,0.000022791673,0.024959374,0.43127468,0.0003786487],"about_ca_topic_score_codex":0.00003058016,"about_ca_topic_score_gemma":0.000015042242,"teacher_disagreement_score":0.40865955,"about_ca_system_score_codex":0.00014505016,"about_ca_system_score_gemma":0.000024392031,"threshold_uncertainty_score":0.9999919},"labels":[],"label_agreement":null},{"id":"W2167609577","doi":"10.1007/s00181-011-0508-6","title":"The ‘trendiness’ of sleep: an empirical investigation into the cyclical nature of sleep time","year":2011,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":40,"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 Ottawa","funders":"","keywords":"Sleep (system call); Affect (linguistics); Economics; Recession; Unemployment; Sleep deprivation; Great recession; Unemployment rate; Work (physics); Demographic economics; Cognition; Psychology; Monetary economics; Labour economics; Macroeconomics; Psychiatry","score_opus":0.07682359002095165,"score_gpt":0.3935609361102902,"score_spread":0.31673734608933857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167609577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97126305,0.00021155489,0.000014789029,0.019278986,0.0005098491,0.0003752935,0.000014772034,0.000044421227,0.008287254],"genre_scores_gemma":[0.99547255,0.00011355087,0.0002735396,0.0028885633,0.00037156555,0.00006574717,0.000027306816,0.000030261024,0.0007569336],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99793434,0.00041069672,0.00087741314,0.00028950823,0.0001252313,0.0003627852],"domain_scores_gemma":[0.9976649,0.0010610658,0.00044126846,0.00055242714,0.00014211563,0.00013816611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089994277,0.00019526703,0.0004040491,0.000058415164,0.00073519716,0.000007280145,0.0005145255,0.00038572305,0.00024784156],"category_scores_gemma":[0.0003097548,0.00010991625,0.00013604396,0.0001804151,0.0005892844,0.0001488326,0.0002969291,0.00077437295,0.00011090373],"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":[0.0002111706,0.00014081417,0.9326171,0.000047027002,0.00015160853,6.0872395e-7,0.03038437,0.000012174841,0.00005515175,0.0100784935,0.02257859,0.003722883],"study_design_scores_gemma":[0.00073072675,0.00032454263,0.89216405,0.000039317012,0.00009135929,9.399316e-7,0.002873098,0.0019333225,0.00045369743,0.04186816,0.05924663,0.00027413553],"about_ca_topic_score_codex":0.00021828144,"about_ca_topic_score_gemma":0.00057660206,"teacher_disagreement_score":0.04045304,"about_ca_system_score_codex":0.000088208755,"about_ca_system_score_gemma":0.000116755305,"threshold_uncertainty_score":0.56546164},"labels":[],"label_agreement":null},{"id":"W2171692556","doi":"10.1007/s00181-008-0240-z","title":"Screen wars, star wars, and sequels","year":2008,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Cinema and Media Studies","field":"Economics, Econometrics and Finance","cited_by":32,"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 Calgary","funders":"","keywords":"Nonparametric statistics; Profit (economics); Econometrics; Conditional probability distribution; Specification; Marginal distribution; Conditional expectation; Economics; Marginal profit; Computer science; Mathematics; Statistics; Microeconomics; Random variable","score_opus":0.09088501114558718,"score_gpt":0.2538209006183152,"score_spread":0.16293588947272802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171692556","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9660999,0.004153257,0.00015575431,0.0046040043,0.00037786513,0.00016881316,0.00019702034,0.000059879283,0.02418352],"genre_scores_gemma":[0.9801553,0.010594638,0.0021454864,0.0029744229,0.00041455775,0.00002247827,0.000033061344,0.00004623536,0.003613811],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99856216,0.000008560046,0.00056251424,0.00048321066,0.00001761838,0.0003659417],"domain_scores_gemma":[0.99922717,0.000100157755,0.00016876943,0.00028833825,0.000016386119,0.00019916138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021458056,0.00019660521,0.0005516624,0.0001356508,0.00020839214,0.000029330073,0.00015368249,0.0001196312,0.00024939634],"category_scores_gemma":[0.00010815046,0.00022189207,0.000106483094,0.00009197265,0.00021855466,0.0002048724,0.00014249678,0.00016445135,0.00062880554],"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":[0.00006658122,0.00019875403,0.79104584,0.000044204415,0.00026501663,0.000048378206,0.0035312714,0.00006368243,0.00000889216,0.08868558,0.112561464,0.0034803061],"study_design_scores_gemma":[0.0010992311,0.00012944869,0.15540439,0.000007215113,0.000009455278,0.00005697791,0.00011414803,0.0012451896,0.000051052826,0.029409569,0.8119504,0.00052294065],"about_ca_topic_score_codex":0.00015006163,"about_ca_topic_score_gemma":0.00006246534,"teacher_disagreement_score":0.6993889,"about_ca_system_score_codex":0.00010284868,"about_ca_system_score_gemma":0.00003496275,"threshold_uncertainty_score":0.9048496},"labels":[],"label_agreement":null},{"id":"W2323793152","doi":"10.1007/s00181-016-1079-3","title":"Patent thickets, defensive patenting, and induced R&amp;D: an empirical analysis of the costs and potential benefits of fragmentation in patent ownership","year":2016,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Intellectual property; Industrial organization; Fragmentation (computing); Business; Value (mathematics); Market value; Economics","score_opus":0.24227223376939935,"score_gpt":0.2755955922384261,"score_spread":0.03332335846902676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2323793152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99821556,0.00004354286,0.000055401186,0.0010819319,0.00015052232,0.00022633694,0.000017278458,0.000011221681,0.00019823325],"genre_scores_gemma":[0.99850994,0.00008567098,0.000037159512,0.0012104525,0.00007796475,0.0000059699937,0.000027155487,0.00001594311,0.000029741197],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986269,0.00006531151,0.00057168177,0.0003646802,0.00013181914,0.00023964311],"domain_scores_gemma":[0.999091,0.000107122156,0.0003916611,0.00022832646,0.00015093492,0.00003093071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042107262,0.000182435,0.00039571855,0.00034214716,0.00008773582,0.000063918815,0.00017705893,0.00014828607,0.000089192166],"category_scores_gemma":[0.00018490118,0.000107155036,0.00012087434,0.00040660036,0.00013007339,0.00044573637,0.00023357784,0.00012588922,0.000009832643],"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":[0.00027672094,0.00019437491,0.98004544,0.00005253084,0.00024236126,9.949437e-7,0.00078593945,0.0007590418,0.0013088789,0.00040236412,0.00009568398,0.015835661],"study_design_scores_gemma":[0.0010766926,0.000053705553,0.9874935,0.00007690291,0.0003562251,0.0000013705209,0.0003883015,0.008714599,0.00072490884,0.0006737942,0.00020501303,0.00023496327],"about_ca_topic_score_codex":0.00067527423,"about_ca_topic_score_gemma":0.0011864718,"teacher_disagreement_score":0.015600697,"about_ca_system_score_codex":0.000057349,"about_ca_system_score_gemma":0.000023186185,"threshold_uncertainty_score":0.43696555},"labels":[],"label_agreement":null},{"id":"W2606388273","doi":"10.1007/s00181-017-1254-1","title":"A dynamic factor model for nowcasting Canadian GDP growth","year":2017,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada; Wilfrid Laurier University","funders":"","keywords":"Nowcasting; Dynamic factor; Univariate; Econometrics; Gross domestic product; Design for manufacturability; Economics; Real gross domestic product; Computer science; Macroeconomics; Multivariate statistics; Geography; Engineering; Meteorology","score_opus":0.22306227462406603,"score_gpt":0.30153439126717974,"score_spread":0.07847211664311371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606388273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95294803,0.00011884772,0.012057757,0.008628291,0.0007662148,0.00044051875,0.004175973,0.000042621057,0.020821718],"genre_scores_gemma":[0.9896943,0.00011187156,0.0043413313,0.002352669,0.00020061557,0.000043918102,0.000050303788,0.000065311586,0.0031396882],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99770665,0.0000051444026,0.00075910275,0.0006726835,0.000010868348,0.00084555324],"domain_scores_gemma":[0.9979528,0.00008425668,0.00056263193,0.00083657756,0.000016101763,0.0005476186],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003751644,0.00028477467,0.0006105226,0.00025163926,0.000829157,0.0004252782,0.0007545251,0.00023593807,0.0002991981],"category_scores_gemma":[0.0003610676,0.00036460356,0.00028968632,0.00002212925,0.000109162334,0.0006995397,0.0000711128,0.0001964799,0.00090490514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027765086,0.0003201457,0.56295663,0.0002819374,0.0007702353,0.000016288925,0.0066053187,0.15584557,0.000013526784,0.22076172,0.04356232,0.008588661],"study_design_scores_gemma":[0.0006107055,0.000037599882,0.01739504,0.000004840504,0.0000057792413,0.0000044695394,0.0000101776295,0.89392,0.0000054969673,0.07102412,0.016552428,0.00042935307],"about_ca_topic_score_codex":0.024986895,"about_ca_topic_score_gemma":0.055684775,"teacher_disagreement_score":0.7380744,"about_ca_system_score_codex":0.00062948285,"about_ca_system_score_gemma":0.00012751439,"threshold_uncertainty_score":0.9998806},"labels":[],"label_agreement":null},{"id":"W2612017567","doi":"10.1007/s00181-017-1305-7","title":"The role of the exchange rate in Canadian monetary policy: evidence from a TVP-BVAR model","year":2017,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; Monetary policy; Exchange rate; Interest rate; Bayesian vector autoregression; Credibility; Monetary economics; Econometrics; Lucas critique; Inflation targeting; Explanatory power; Volatility (finance); Inflation (cosmology); Taylor rule; Fisher hypothesis; Macroeconomics; Central bank; Bayesian probability; Real interest rate","score_opus":0.11917901600540179,"score_gpt":0.27649177818281023,"score_spread":0.15731276217740844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612017567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9649209,0.0022814665,0.000019434505,0.017616661,0.00029215295,0.00025683249,0.00069844484,0.000007667018,0.013906436],"genre_scores_gemma":[0.9953841,0.001925248,0.00008908589,0.0017035152,0.0002697228,0.000023368228,0.0000061096875,0.000028781698,0.00057004875],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979563,0.000040376573,0.00082140625,0.00045629186,0.000018265837,0.00070741004],"domain_scores_gemma":[0.99724877,0.00025473814,0.000663854,0.0015398001,0.000008326067,0.00028450004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010349477,0.00022275759,0.00049199554,0.00016978027,0.00058217783,0.00022125407,0.0015500278,0.00017981998,0.00012266693],"category_scores_gemma":[0.00066957535,0.00018865005,0.0002167497,0.00006660654,0.00027337827,0.0005625232,0.00026377424,0.00028840447,0.00029653325],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006515808,0.00004020111,0.9007406,0.000010772685,0.00009139891,0.0000017170147,0.0018258793,0.06409704,0.00001009291,0.028249128,0.0020253982,0.002842585],"study_design_scores_gemma":[0.0002553778,0.000015380441,0.30327544,0.00001745387,0.0000046446185,7.716567e-7,0.000030025889,0.51754045,0.00006062443,0.14506052,0.033528052,0.00021125351],"about_ca_topic_score_codex":0.6925105,"about_ca_topic_score_gemma":0.4449554,"teacher_disagreement_score":0.5974652,"about_ca_system_score_codex":0.00056831044,"about_ca_system_score_gemma":0.0003110432,"threshold_uncertainty_score":0.7692926},"labels":[],"label_agreement":null},{"id":"W2762150821","doi":"10.1007/s00181-017-1343-1","title":"Quantile forecast combination using stochastic dominance","year":2017,"lang":"en","type":"article","venue":"Empirical Economics","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":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; Edge Hill University","keywords":"Quantile; Forecast error; Econometrics; Stochastic dominance; Forecast verification; Mathematics; Statistics; Selection (genetic algorithm); Computer science","score_opus":0.23844048642004323,"score_gpt":0.3189729033769603,"score_spread":0.0805324169569171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762150821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97058755,0.00019822773,0.014098656,0.0016231375,0.0011011757,0.00022783686,0.00020368617,0.00003504544,0.011924687],"genre_scores_gemma":[0.9971811,0.00005306282,0.0009657165,0.0006161903,0.00032886432,0.000012190531,0.000017928574,0.00004376369,0.0007811933],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980894,0.000011042915,0.00079685607,0.00056942564,0.000016082955,0.0005172126],"domain_scores_gemma":[0.9978347,0.00006885558,0.0009387892,0.00096110505,0.000011221794,0.00018536959],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00050685124,0.0002484811,0.00060772826,0.00016184339,0.00067022047,0.0003801939,0.000611765,0.00017610396,0.0004930586],"category_scores_gemma":[0.0002448165,0.00031705742,0.0002049223,0.00003166141,0.00019339981,0.00097461557,0.0001622359,0.00019328935,0.0014686257],"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":[0.00037792147,0.00085358985,0.3093204,0.00011418715,0.0003998819,0.000019430445,0.0020309456,0.19391245,0.00003404524,0.46978432,0.012357739,0.010795122],"study_design_scores_gemma":[0.0015429556,0.00010096401,0.050023124,0.000016818502,0.000012777938,0.000024468036,0.000022142327,0.79535025,0.000048214613,0.13457572,0.017651167,0.00063141435],"about_ca_topic_score_codex":0.00067965954,"about_ca_topic_score_gemma":0.00006141218,"teacher_disagreement_score":0.6014378,"about_ca_system_score_codex":0.0002818393,"about_ca_system_score_gemma":0.000031118336,"threshold_uncertainty_score":0.9999282},"labels":[],"label_agreement":null},{"id":"W2778036599","doi":"10.1007/s00181-018-1580-y","title":"A time–frequency analysis of the Canadian macroeconomy and the yield curve","year":2018,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":6,"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":"Fundação para a Ciência e a Tecnologia","keywords":"Yield curve; Economics; Monetary policy; Econometrics; Yield (engineering); Interest rate; Inflation (cosmology); Unemployment; Monetary economics; Curvature; Short rate; Hodrick–Prescott filter; Macroeconomics; Mathematics; Business cycle","score_opus":0.03470068916645692,"score_gpt":0.22613714555835956,"score_spread":0.19143645639190265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2778036599","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8697657,0.0008713611,0.000110136025,0.012082346,0.00040146662,0.00033612686,0.00036930715,0.000020492893,0.11604308],"genre_scores_gemma":[0.9964048,0.000041427,0.00008333835,0.0013582099,0.00013068554,0.000013403342,0.0000064569067,0.000017879194,0.0019437604],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984935,0.000032586908,0.0007947006,0.00037288005,0.00001945668,0.00028685902],"domain_scores_gemma":[0.9984961,0.00017264058,0.0004559838,0.0006894948,0.000048850645,0.00013692712],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007538658,0.00015382872,0.00073639286,0.00031692494,0.00036791258,0.00011409113,0.00044712937,0.00010202529,0.0022054804],"category_scores_gemma":[0.00013417927,0.00011233931,0.0004468809,0.00067478715,0.0008157983,0.000106934625,0.00012674712,0.00012681297,0.00034311664],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003081692,0.000028886541,0.5059825,0.000008850212,0.003009376,5.69647e-7,0.0015975203,0.0003211769,9.0483917e-7,0.48411563,0.004409525,0.0004942142],"study_design_scores_gemma":[0.0012528083,0.000099021156,0.31394318,0.000013180364,0.000789482,0.00000886036,0.00026027593,0.17587206,0.000018365457,0.086214185,0.42081073,0.0007178482],"about_ca_topic_score_codex":0.1553499,"about_ca_topic_score_gemma":0.48263937,"teacher_disagreement_score":0.4164012,"about_ca_system_score_codex":0.000167786,"about_ca_system_score_gemma":0.00009389836,"threshold_uncertainty_score":0.99870664},"labels":[],"label_agreement":null},{"id":"W2786143286","doi":"10.1007/s00181-019-01694-5","title":"Does business confidence matter for investment?","year":2019,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":62,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Carleton University","funders":"","keywords":"Investment (military); Quarter (Canadian coin); Business cycle; Confidence interval; Economics; Predictive power; Sign (mathematics); Investment strategy; Return on investment; Econometrics; Monetary economics; Macroeconomics; Statistics; Geography","score_opus":0.03450199352066178,"score_gpt":0.24195356099718449,"score_spread":0.2074515674765227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2786143286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.789192,0.00026756577,0.0011316694,0.008647237,0.0027033018,0.00083106244,0.0002935572,0.000057222223,0.19687636],"genre_scores_gemma":[0.9565048,0.0002635988,0.0022673286,0.024507394,0.00041535907,0.00016615851,0.00006875641,0.00007200875,0.015734594],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983952,0.0000073811934,0.0006361185,0.00056442135,0.000015640755,0.0003812046],"domain_scores_gemma":[0.9990701,0.0001042357,0.00028661106,0.00040595015,0.00003779071,0.000095299656],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00027129948,0.00021039306,0.0004870504,0.000115995696,0.000079883815,0.00016116258,0.0002842238,0.00013843468,0.0023005332],"category_scores_gemma":[0.00005994646,0.00017473214,0.0001384889,0.00011208989,0.00007414946,0.00047354263,0.000069041256,0.00009207529,0.0043017943],"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":[0.000036283407,0.000053695196,0.207242,0.000063207866,0.000028742577,3.3318778e-7,0.000081748534,0.00006840764,0.000005789279,0.7763933,0.015958875,0.000067638895],"study_design_scores_gemma":[0.0005705094,0.00005213869,0.14531662,0.000010763297,0.0000037118002,9.840544e-7,0.00003486385,0.0010026637,0.00004319314,0.35882252,0.4938175,0.00032452407],"about_ca_topic_score_codex":0.00007909719,"about_ca_topic_score_gemma":0.00001520175,"teacher_disagreement_score":0.47785863,"about_ca_system_score_codex":0.00011304131,"about_ca_system_score_gemma":0.000053346153,"threshold_uncertainty_score":0.9986115},"labels":[],"label_agreement":null},{"id":"W2787219109","doi":"10.1007/s00181-019-01753-x","title":"Black swan models for the entertainment industry with an application to the movie business","year":2019,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":6,"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 Calgary","funders":"","keywords":"Econometrics; Black swan theory; Skewness; Ordinary least squares; Outlier; Revenue; Film industry; Statistical inference; Regression analysis; Profitability index; Skew; Statistical model; Regression; Sample (material); Black box; Economics; Computer science; Statistics; Mathematics; Artificial intelligence","score_opus":0.04513576501089041,"score_gpt":0.2543489799891817,"score_spread":0.20921321497829132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787219109","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90999275,0.00009088101,0.068748064,0.016022848,0.00023438132,0.0010700809,0.00011919383,0.00001725176,0.0037045467],"genre_scores_gemma":[0.9929198,0.00008735305,0.0002764122,0.005148987,0.00024727517,0.00013849071,0.00002880912,0.000029097851,0.0011237564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989447,0.0000033740173,0.00038770278,0.00039059375,0.000023366238,0.00025026154],"domain_scores_gemma":[0.99893,0.000056907098,0.00020789403,0.0006740999,0.00004062269,0.000090494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042390486,0.0001447597,0.00024055841,0.000053946387,0.00013234465,0.00013024629,0.00043058943,0.00011060582,0.00012885555],"category_scores_gemma":[0.0000072662187,0.00009516605,0.0000621327,0.00015179733,0.00004581239,0.0002133105,0.000057073757,0.00017033941,0.00030982672],"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":[0.0000934845,0.000086528154,0.06396018,0.000015472544,0.00006346994,1.1567666e-7,0.0006097133,0.8348599,4.0465304e-7,0.09619883,0.001996147,0.0021157442],"study_design_scores_gemma":[0.00027802796,0.00009076049,0.02305973,0.000003496574,0.000007547047,9.828461e-7,0.00015337698,0.6892343,0.000004395529,0.005395828,0.28160548,0.00016607584],"about_ca_topic_score_codex":0.00013796198,"about_ca_topic_score_gemma":0.00016157332,"teacher_disagreement_score":0.27960932,"about_ca_system_score_codex":0.000111571084,"about_ca_system_score_gemma":0.00003808218,"threshold_uncertainty_score":0.3982299},"labels":[],"label_agreement":null},{"id":"W2889667962","doi":"10.1007/s00181-018-1566-9","title":"The dynamics among domestic saving, investment, and the current account balance in the USA: a long-run perspective","year":2018,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Royal University; The King's University; Western University","funders":"","keywords":"Ricardian equivalence; Economics; Current account; Investment (military); Balance (ability); Econometrics; Monetary economics; Business cycle; Sample (material); Balance of trade; Government (linguistics); Perspective (graphical); Macroeconomics; Fiscal policy; Politics; Exchange rate; Mathematics","score_opus":0.05794707571122712,"score_gpt":0.2959473884170122,"score_spread":0.23800031270578506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889667962","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9664064,0.0026278354,0.0002574866,0.011906917,0.00070745166,0.0005916366,0.00009470328,0.000014954275,0.017392596],"genre_scores_gemma":[0.9928359,0.0017984912,0.00003488363,0.0043807663,0.0005051976,0.00008120291,0.0000074150853,0.000025746085,0.00033040068],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.997924,0.000099347984,0.0008106829,0.0005598228,0.00003073836,0.0005754192],"domain_scores_gemma":[0.9978723,0.00080966373,0.0004626391,0.00072550395,0.000018084404,0.0001118422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019673347,0.0002860149,0.00048960926,0.00011161929,0.0005586043,0.00043408963,0.00077787583,0.000100107434,0.00007150993],"category_scores_gemma":[0.0004129164,0.00018089099,0.00015817025,0.00017277001,0.0014956145,0.00035590868,0.0001866742,0.00052890816,0.00044276216],"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":[0.00010240909,0.00007033204,0.4852493,0.0000081932585,0.00006790319,0.0000018808889,0.0034894543,0.0004767061,1.7683911e-8,0.5069689,0.0024814394,0.0010834553],"study_design_scores_gemma":[0.0013757878,0.0000832486,0.57809126,0.000011310836,0.000015122638,0.000020346517,0.00043462063,0.20478866,3.1132498e-7,0.19130601,0.023560612,0.00031271658],"about_ca_topic_score_codex":0.002128813,"about_ca_topic_score_gemma":0.011143832,"teacher_disagreement_score":0.3156629,"about_ca_system_score_codex":0.00061543536,"about_ca_system_score_gemma":0.00005126817,"threshold_uncertainty_score":0.73765206},"labels":[],"label_agreement":null},{"id":"W2903575327","doi":"10.1007/s00181-018-01618-9","title":"Why fully efficient banks matter? A nonparametric stochastic frontier approach in the presence of fully efficient banks","year":2018,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":7,"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 Lethbridge","funders":"","keywords":"Nonparametric statistics; Frontier; Economics; Econometrics; Stochastic frontier analysis; Financial economics; Microeconomics","score_opus":0.0642081765377193,"score_gpt":0.34214012284840284,"score_spread":0.2779319463106835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903575327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80085677,0.00015869176,0.18918402,0.002393056,0.0005312316,0.0005067935,0.00002683179,0.000022391525,0.0063202064],"genre_scores_gemma":[0.99289244,0.0000019090826,0.003277765,0.0033847957,0.00017061466,0.00003531592,0.0000047517387,0.000027350343,0.00020503253],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9938599,0.000707105,0.001956725,0.0014016491,0.0012611131,0.0008135202],"domain_scores_gemma":[0.9929459,0.0036530683,0.00077579904,0.0020249677,0.00040490794,0.0001953374],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006878084,0.00039761522,0.0009204858,0.0013677732,0.00026728155,0.0004423178,0.0031082332,0.00024933057,0.0005206011],"category_scores_gemma":[0.003005569,0.00027067575,0.00041299852,0.003980262,0.0010962994,0.00014865777,0.0004981075,0.000512767,0.0010609457],"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":[0.00015737914,0.0013500142,0.010725248,0.000013027069,0.000043703258,0.00000483919,0.0043564006,0.94811934,0.000023331399,0.0007192489,0.029605355,0.004882107],"study_design_scores_gemma":[0.00053461926,0.0002206767,0.030357497,0.000018860612,0.000050879975,0.00001943648,0.00076571363,0.9614616,0.000051810475,0.0012049443,0.004940477,0.00037348506],"about_ca_topic_score_codex":0.00011937878,"about_ca_topic_score_gemma":0.00005636609,"teacher_disagreement_score":0.19203569,"about_ca_system_score_codex":0.00022762109,"about_ca_system_score_gemma":0.00025325702,"threshold_uncertainty_score":0.99997455},"labels":[],"label_agreement":null},{"id":"W2915003395","doi":"10.1007/s00181-019-01641-4","title":"The sunk-cost fallacy in the National Basketball Association: evidence using player salary and playing time","year":2019,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Sunk costs; Salary; Basketball; Economics; Normative; Association (psychology); Panel data; Microeconomics; Precommitment; Econometrics; Psychology","score_opus":0.10679064713556229,"score_gpt":0.2957480460506456,"score_spread":0.18895739891508329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2915003395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98313135,0.0009924524,0.000028245024,0.0051074564,0.0002418156,0.0002285987,0.00003582111,0.000007656927,0.010226592],"genre_scores_gemma":[0.9946701,0.0008635553,0.00008787271,0.0030262037,0.00019281819,0.000009379276,0.0000063962184,0.000014567866,0.001129085],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987837,0.000019986837,0.0005498442,0.00030819437,0.000056174307,0.00028210066],"domain_scores_gemma":[0.9986349,0.0007570865,0.0003367361,0.00019466065,0.000032450953,0.00004419391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022168695,0.0001267249,0.0002473217,0.00008502681,0.00021205287,0.00028223926,0.00029302546,0.0001040311,0.00027171825],"category_scores_gemma":[0.00021045067,0.00010180725,0.00007401585,0.00014226734,0.000035156754,0.000380377,0.00007579156,0.00023774726,0.0005367382],"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":[0.000013832851,0.000018981737,0.98342985,0.0000058655623,0.000025783014,6.405321e-7,0.00028238853,0.0040274872,0.0000019787003,0.009908737,0.002113985,0.00017046559],"study_design_scores_gemma":[0.00032643476,0.000022799975,0.47610113,0.000017808505,0.0000039712554,0.000006904906,0.000047604364,0.39762196,0.0000015946423,0.0060789487,0.11954762,0.00022323987],"about_ca_topic_score_codex":0.00007969599,"about_ca_topic_score_gemma":0.0000636494,"teacher_disagreement_score":0.50732875,"about_ca_system_score_codex":0.00040081888,"about_ca_system_score_gemma":0.00006325287,"threshold_uncertainty_score":0.6898863},"labels":[],"label_agreement":null},{"id":"W2916789885","doi":"10.1007/s00181-021-02119-y","title":"Fiscal reaction functions for the advanced economies revisited","year":2021,"lang":"en","type":"preprint","venue":"Empirical Economics","topic":"Fiscal Policies and Political Economy","field":"Economics, Econometrics and Finance","cited_by":26,"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":"Sapienza Università di Roma","keywords":"Economics; Monetary economics; Sovereignty; Debt; Function (biology); Sovereign debt; Fiscal policy; Macroeconomics","score_opus":0.06786829660760837,"score_gpt":0.2866791569601017,"score_spread":0.21881086035249334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916789885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57510394,0.01482778,0.033691116,0.16038202,0.018282948,0.0051702047,0.012386753,0.0005475649,0.17960766],"genre_scores_gemma":[0.9297454,0.0058705686,0.0057215076,0.025684282,0.006871147,0.002542687,0.003098234,0.00042702255,0.020039152],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9961685,0.000031533382,0.0017324557,0.0012619211,0.000023420283,0.0007821516],"domain_scores_gemma":[0.99648696,0.0009625072,0.000849628,0.0013466312,0.00007260446,0.00028166646],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006027823,0.0005490019,0.0013137467,0.00019123516,0.00042057448,0.00057279295,0.0006800857,0.00069465215,0.000740602],"category_scores_gemma":[0.0004526487,0.00056011765,0.0010864338,0.00011634416,0.00024830535,0.00031815618,0.0006380534,0.00093957275,0.0006458596],"study_design_candidate":"not_applicable","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":[0.00030192724,0.0005692938,0.010765244,0.00076568173,0.0019535434,0.0000039001243,0.001173887,0.026953656,0.0000064255173,0.7367716,0.20746332,0.01327155],"study_design_scores_gemma":[0.00066064525,0.00007983513,0.008487065,0.00003523579,0.00006980831,0.000007334317,0.00029782564,0.03271187,0.00001383107,0.09260799,0.864264,0.00076455064],"about_ca_topic_score_codex":0.00032469508,"about_ca_topic_score_gemma":0.0001675849,"teacher_disagreement_score":0.6568007,"about_ca_system_score_codex":0.00069820706,"about_ca_system_score_gemma":0.00015138977,"threshold_uncertainty_score":0.99968505},"labels":[],"label_agreement":null},{"id":"W2981381721","doi":"10.1007/s00181-019-01787-1","title":"Tourism, economic growth, and tourism-induced EKC hypothesis: evidence from the Mediterranean region","year":2019,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":129,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Tourism; Kuznets curve; Cointegration; Mediterranean climate; Economics; Causality (physics); Panel data; Granger causality; Economic geography; Sustainable development; Distributed lag; Economy; Consumption (sociology); Econometrics; Macroeconomics; Geography; Ecology; Biology","score_opus":0.07831923444863566,"score_gpt":0.23729522370787962,"score_spread":0.15897598925924394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981381721","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97296625,0.0015431956,0.00014049532,0.014588143,0.0014756274,0.0004784928,0.00012145507,0.00007562075,0.008610699],"genre_scores_gemma":[0.99040496,0.0031056511,0.00056091987,0.003962974,0.0011038119,0.00006152432,0.000020124982,0.000114018236,0.00066601514],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963842,0.00008172479,0.0013603735,0.0014730078,0.000038988903,0.0006617056],"domain_scores_gemma":[0.99619126,0.0013327495,0.0008666367,0.0012997562,0.000008473112,0.00030110724],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007227607,0.00050225534,0.0009601353,0.0001733927,0.00019420119,0.00027431923,0.0009741367,0.0003747142,0.0009806429],"category_scores_gemma":[0.00024453056,0.00051419274,0.00028435476,0.000081926366,0.00019448755,0.00093093753,0.0003792963,0.00045430692,0.0039887014],"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":[0.00024108436,0.00019929119,0.92032367,0.00006618672,0.0006463325,0.000029596082,0.0024760703,0.0015565876,0.00017497505,0.043025162,0.025524702,0.005736316],"study_design_scores_gemma":[0.004280525,0.00059982843,0.64800406,0.00018282322,0.00011619204,0.00007887796,0.0007760338,0.026596399,0.0020151364,0.2137898,0.100233965,0.0033263573],"about_ca_topic_score_codex":0.00115521,"about_ca_topic_score_gemma":0.00016236106,"teacher_disagreement_score":0.27231964,"about_ca_system_score_codex":0.0005469461,"about_ca_system_score_gemma":0.000061878774,"threshold_uncertainty_score":0.9999326},"labels":[],"label_agreement":null},{"id":"W2982251873","doi":"10.1007/s00181-019-01786-2","title":"Structural breaks, debt limits and the tax smoothing hypothesis: theory and evidence from the OECD countries","year":2019,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Economics; Monetary economics; Debt; Tax rate; Smoothing; Econometrics; Optimal tax; Sample (material); Tax policy; Macroeconomics; Tax reform; Public economics; Mathematics","score_opus":0.04736497447619915,"score_gpt":0.2373433078851643,"score_spread":0.18997833340896517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982251873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9656446,0.0088543175,0.000036342863,0.017690945,0.00041048552,0.00033261642,0.00017668758,0.000026514794,0.0068275104],"genre_scores_gemma":[0.98774135,0.0010480098,0.000126419,0.010354713,0.0003521324,0.00001948005,0.0000033563992,0.000032477892,0.0003220337],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99824226,0.00010578962,0.0006657025,0.00059008814,0.000022504599,0.00037363515],"domain_scores_gemma":[0.9942445,0.004723062,0.0003733346,0.0005395132,0.000010273719,0.00010931287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015677476,0.0002609385,0.00058746623,0.00005260188,0.00031309575,0.00040345095,0.00047539023,0.00016258864,0.00023953838],"category_scores_gemma":[0.00048774172,0.00018239502,0.00012403795,0.000041274398,0.0005943808,0.00056402973,0.00020569233,0.0003150053,0.00066598447],"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":[0.0003860594,0.000007902786,0.2770982,0.000026708847,0.00015910329,6.282825e-7,0.0036846441,0.00006586108,0.0000016355986,0.71516556,0.0015174149,0.0018862422],"study_design_scores_gemma":[0.0010604922,0.000032186257,0.2379203,0.00002596215,0.000021941107,0.0000110692035,0.00029541386,0.006177002,0.000020721849,0.7432931,0.010828536,0.00031330393],"about_ca_topic_score_codex":0.0005038896,"about_ca_topic_score_gemma":0.00012314729,"teacher_disagreement_score":0.039177924,"about_ca_system_score_codex":0.000085637446,"about_ca_system_score_gemma":0.00003325337,"threshold_uncertainty_score":0.8560105},"labels":[],"label_agreement":null},{"id":"W3026338022","doi":"10.1007/s00181-020-01878-4","title":"Revisiting the link between output growth and volatility: panel GARCH analysis","year":2020,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":8,"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 Guelph","funders":"","keywords":"Volatility (finance); Economics; Openness to experience; Econometrics; Autoregressive conditional heteroskedasticity; Panel data; Panel analysis; Forward volatility; Monetary economics; Stochastic volatility","score_opus":0.10521601426183196,"score_gpt":0.25415538053049325,"score_spread":0.14893936626866128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026338022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89921784,0.00094853307,0.006429077,0.08070976,0.00009519744,0.00023208924,0.00026408007,0.00007065897,0.0120327445],"genre_scores_gemma":[0.99251074,0.0005331439,0.00083645753,0.0040700654,0.00174843,0.000018910097,0.00005718968,0.000052055966,0.00017303695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971317,0.000058883372,0.0012530726,0.0010388296,0.00003074859,0.0004867398],"domain_scores_gemma":[0.9980356,0.00044068237,0.0005835026,0.0005762851,0.000010492166,0.00035340383],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008244874,0.00031330422,0.0009941162,0.00018583311,0.00022827197,0.00020614864,0.00053798786,0.00019662027,0.0002586473],"category_scores_gemma":[0.00035464118,0.00032385474,0.00034430358,0.00037299676,0.00021086835,0.0002852785,0.00038608248,0.00042712202,0.0003493153],"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":[0.00000993466,0.0000059284944,0.97587,0.000026189491,0.000561415,0.0000013372776,0.00054055196,0.00041583384,0.0000010982186,0.015708543,0.00013876069,0.0067203706],"study_design_scores_gemma":[0.00069338735,0.00007130684,0.7077551,0.000005184998,0.00023721403,0.0000020602486,0.00014547004,0.1182008,0.000036278176,0.024026701,0.1480929,0.00073363347],"about_ca_topic_score_codex":0.00011303337,"about_ca_topic_score_gemma":0.00000808388,"teacher_disagreement_score":0.26811495,"about_ca_system_score_codex":0.0001468906,"about_ca_system_score_gemma":0.000022036504,"threshold_uncertainty_score":0.9999213},"labels":[],"label_agreement":null},{"id":"W3026774961","doi":"10.1007/s00181-020-01886-4","title":"Bank stability and economic growth: trade-offs or opportunities?","year":2020,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Banking stability, regulation, efficiency","field":"Economics, Econometrics and Finance","cited_by":27,"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 New Brunswick","funders":"","keywords":"Economics; Capital (architecture); Monetary economics; Capital requirement; Quality (philosophy); Stability (learning theory); Regulatory reform; Capital deepening; Panel data; International economics; Capital formation; Financial capital; Macroeconomics; Human capital; Market economy; Econometrics","score_opus":0.1359404994420192,"score_gpt":0.2701022656334244,"score_spread":0.13416176619140519,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026774961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95490324,0.0005297007,0.00090072793,0.029063875,0.00043222128,0.00039074483,0.0005067296,0.00014674457,0.013125997],"genre_scores_gemma":[0.9946487,0.0004959282,0.0007698099,0.0035570636,0.00031949845,0.000023222983,0.0000337632,0.00005708267,0.000094909454],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970628,0.000047600846,0.0013001626,0.0010724069,0.000028769875,0.00048827776],"domain_scores_gemma":[0.9983328,0.0003091568,0.00042704106,0.00049354316,0.000018108582,0.00041936076],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00073051755,0.0003326152,0.0007825133,0.00012256614,0.00018485778,0.0001886303,0.00040232792,0.00022810599,0.0026397435],"category_scores_gemma":[0.00034955845,0.00037980283,0.00017793613,0.00013720001,0.00035401856,0.0005343691,0.00018176279,0.00026059203,0.0003277437],"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":[0.0002601966,0.00030634706,0.5739872,0.00023843268,0.00013697002,0.000008737304,0.0042519583,0.00048170952,0.000006230342,0.40874815,0.0065511265,0.0050229407],"study_design_scores_gemma":[0.003400301,0.00091397157,0.37543002,0.000018173017,0.000047520338,0.000041014042,0.00081645866,0.11733939,0.00035915416,0.13810773,0.36107567,0.002450602],"about_ca_topic_score_codex":0.000098875054,"about_ca_topic_score_gemma":0.000080489146,"teacher_disagreement_score":0.35452452,"about_ca_system_score_codex":0.00040167515,"about_ca_system_score_gemma":0.00017396783,"threshold_uncertainty_score":0.9998654},"labels":[],"label_agreement":null},{"id":"W3088641008","doi":"10.1007/s00181-020-01938-9","title":"Gravity models of interprovincial migration flows in Canada with hierarchical multifactor structure","year":2020,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":11,"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":"Economic and Social Research Council; University of York","keywords":"Economics; Unemployment; Econometrics; Gravity model of trade; Panel data; Destinations; Internal migration; Economic geography; Estimator; Demographic economics; Geography; International economics; Macroeconomics; Mathematics; Developing country; Statistics; Tourism","score_opus":0.03120132792784113,"score_gpt":0.2052091114614628,"score_spread":0.17400778353362167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088641008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98787946,0.000058000067,0.0032564986,0.007453492,0.00008736319,0.00014851817,0.00057093916,0.0000068805084,0.00053887605],"genre_scores_gemma":[0.99721843,0.00005134533,0.001178072,0.0013574811,0.00009816305,0.000006341135,0.00005882977,0.000021212807,0.000010123101],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833786,0.000016038583,0.0008867446,0.00049074285,0.000030156942,0.00023846889],"domain_scores_gemma":[0.9991518,0.00006282844,0.0003643381,0.00020090352,0.00002370639,0.00019637049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008909872,0.0001915791,0.0007038973,0.00011004187,0.000032814954,0.000031052346,0.0002689648,0.000095964584,0.00015534137],"category_scores_gemma":[0.000041553547,0.0001961216,0.00011866569,0.00016446745,0.00004942536,0.00022033647,0.0000654614,0.00024324862,0.000011018136],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044837914,0.00009357555,0.56487757,0.000049198305,0.00016718438,0.00000976144,0.001213949,0.37668687,0.000026004629,0.054073077,0.0003937503,0.0019606985],"study_design_scores_gemma":[0.00064204243,0.00009599629,0.027200378,0.0000054971965,0.000006801398,0.0000012983506,0.000065430366,0.9444147,0.000061581864,0.024144141,0.0030598873,0.00030224957],"about_ca_topic_score_codex":0.6403075,"about_ca_topic_score_gemma":0.9557411,"teacher_disagreement_score":0.5677278,"about_ca_system_score_codex":0.00051290134,"about_ca_system_score_gemma":0.0004878019,"threshold_uncertainty_score":0.7997607},"labels":[],"label_agreement":null},{"id":"W3121203693","doi":"10.1007/s001810100116","title":"Fads or bubbles?","year":2002,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Econometrics; Economics; Dividend; Regression; Mathematics; Statistics","score_opus":0.12498861367387687,"score_gpt":0.2551614189228695,"score_spread":0.1301728052489926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121203693","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37934098,0.0003535083,0.00079564,0.0038897942,0.001158019,0.00018104176,0.00007980778,0.00016335577,0.6140379],"genre_scores_gemma":[0.97572696,0.0024715748,0.0022481158,0.0038466237,0.00064669066,0.000029199142,0.000016601887,0.0001004992,0.014913742],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997765,0.000013998882,0.0009661838,0.0006584788,0.000015553196,0.000580794],"domain_scores_gemma":[0.99869674,0.00012590694,0.00032702897,0.0005842163,0.0000146299935,0.00025148844],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00041036055,0.00027215513,0.0006326636,0.00021782155,0.00016413402,0.00019691195,0.0004257751,0.00023126563,0.012453679],"category_scores_gemma":[0.00015480054,0.00030320726,0.00021848765,0.00017962312,0.0001079868,0.00041231007,0.00012241532,0.00023386895,0.013821036],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026838595,0.0012146991,0.27416772,0.000115809,0.0004016189,0.00006254069,0.0029124464,0.002466582,0.0000046496625,0.31047863,0.32431957,0.08358735],"study_design_scores_gemma":[0.0008197654,0.00010224211,0.0025602963,0.000005508366,0.0000062805634,0.000024418607,0.0000452592,0.04832752,0.000014268358,0.030509701,0.91697097,0.00061374094],"about_ca_topic_score_codex":0.000041425945,"about_ca_topic_score_gemma":0.00006400333,"teacher_disagreement_score":0.59912413,"about_ca_system_score_codex":0.0002926459,"about_ca_system_score_gemma":0.000020324918,"threshold_uncertainty_score":0.999942},"labels":[],"label_agreement":null},{"id":"W3122118186","doi":"10.1007/s001810000031","title":"Invariance, price indices and estimation in almost ideal demand systems","year":2000,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":32,"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":"Estimator; Almost ideal demand system; Econometrics; Ideal (ethics); Invariant (physics); Price index; Mathematics; Index (typography); TRACE (psycholinguistics); Estimation; Economics; Statistics; Computer science; Microeconomics","score_opus":0.030224241797243027,"score_gpt":0.23862617306023254,"score_spread":0.2084019312629895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122118186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9352253,0.0016700571,0.0011896681,0.00071982347,0.00026628267,0.00026283128,0.00009213712,0.00003218531,0.060541723],"genre_scores_gemma":[0.9958832,0.0013543556,0.0008067251,0.0005908571,0.00010297568,0.00003710026,0.000021525957,0.00002809077,0.0011751539],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819404,0.000020189762,0.00089578,0.0005302651,0.000012261274,0.0003474605],"domain_scores_gemma":[0.99921054,0.0001176466,0.0002590486,0.00026704927,0.0000070231154,0.00013872277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006700129,0.0001901726,0.0005240563,0.00017372737,0.00009162714,0.00018387192,0.00019132807,0.00017662227,0.0005217993],"category_scores_gemma":[0.000038341725,0.00023452567,0.000052476615,0.00011360882,0.0000866133,0.0005573989,0.000051631087,0.0001692355,0.00055761106],"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":[0.00010457222,0.00013119263,0.13437444,0.000079179845,0.00007288263,0.0000070738083,0.0017561101,0.08088609,8.298357e-7,0.77482474,0.001258624,0.006504288],"study_design_scores_gemma":[0.0020827772,0.00012977015,0.075377434,0.00004250105,0.000008945383,0.000043379274,0.00018721656,0.4976664,0.000007154031,0.24017845,0.18342598,0.0008500037],"about_ca_topic_score_codex":0.00044259612,"about_ca_topic_score_gemma":0.00007596545,"teacher_disagreement_score":0.5346463,"about_ca_system_score_codex":0.00017475602,"about_ca_system_score_gemma":0.000031690342,"threshold_uncertainty_score":0.9563679},"labels":[],"label_agreement":null},{"id":"W3125099639","doi":"10.1007/s00181-021-02154-9","title":"Electoral systems and income inequality: a tale of political equality","year":2021,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":10,"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":"Agencia Estatal de Investigación; Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España; Ministerio de Economía y Competitividad; European Regional Development Fund; Euskal Herriko Unibertsitatea; York University","keywords":"Economic inequality; Income inequality metrics; Economics; Inequality; Income distribution; Politics; Democracy; Demographic economics; Political science; Mathematics; Law","score_opus":0.08219831850549639,"score_gpt":0.366908488213402,"score_spread":0.28471016970790564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125099639","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97116137,0.00021142673,0.0001959502,0.0026270752,0.00047431057,0.00011714352,0.00008207711,0.000038378636,0.025092293],"genre_scores_gemma":[0.997846,0.000053595337,0.00014299461,0.0010086439,0.0004060213,0.0000060218426,0.000012672671,0.000010934487,0.0005130996],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99770474,0.00067653094,0.0006342104,0.0003218555,0.00016467937,0.0004979797],"domain_scores_gemma":[0.9985959,0.00048712257,0.00015054444,0.00028901876,0.0001528742,0.0003245284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015092094,0.00012928635,0.00047761737,0.000042888085,0.00019595442,0.000102789665,0.00017166749,0.0002049032,0.00012911683],"category_scores_gemma":[0.00080815563,0.00013432051,0.00010772944,0.00016829105,0.00042938982,0.00021861227,0.00014161199,0.00017493055,0.000019184137],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018289405,0.000118170785,0.29472935,0.000079979414,0.000028623313,0.0000030328158,0.0014620541,0.000005225599,0.000024556355,0.70300937,0.00029163386,0.0002297436],"study_design_scores_gemma":[0.003102506,0.0004802874,0.4765322,0.00014145636,0.00014439382,0.000034651028,0.0200661,0.0036794124,0.002244356,0.15911269,0.3324563,0.0020056644],"about_ca_topic_score_codex":0.0077335923,"about_ca_topic_score_gemma":0.002505352,"teacher_disagreement_score":0.5438967,"about_ca_system_score_codex":0.00028883122,"about_ca_system_score_gemma":0.0006076146,"threshold_uncertainty_score":0.998874},"labels":[],"label_agreement":null},{"id":"W3125388086","doi":"10.1007/s00181-011-0516-6","title":"The dynamics of entrepreneurship: hysteresis, business cycles and government policy","year":2011,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Entrepreneurship Studies and Influences","field":"Business, Management and Accounting","cited_by":108,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Entrepreneurship; Hysteresis; Business cycle; Economics; Government (linguistics); Affect (linguistics); Dynamics (music); Econometrics; Economic geography; Macroeconomics; Sociology; Physics","score_opus":0.03357377801412295,"score_gpt":0.23755416438238558,"score_spread":0.20398038636826263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125388086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9746741,0.00023563544,0.000015324205,0.0056632,0.00019962843,0.00010886211,0.0000089649975,0.00002497768,0.01906933],"genre_scores_gemma":[0.99739236,0.0007025371,0.000043967542,0.001373113,0.00032204183,0.000008147616,0.0000028497616,0.000014259295,0.00014069842],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991275,0.000008546804,0.00031909999,0.00022955232,0.000084169966,0.00023110442],"domain_scores_gemma":[0.9993251,0.000104424966,0.00025256557,0.00024841394,0.000053444248,0.000016072809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015878247,0.00014272693,0.00019374042,0.000036819354,0.00018160674,0.000110387875,0.00026089637,0.000044114757,0.000029766037],"category_scores_gemma":[0.00015492253,0.00010239052,0.00005499182,0.0001423927,0.00021502383,0.0003244249,0.00034359464,0.000059838443,0.000021601545],"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":[0.00005076804,0.000051303396,0.8850561,0.00004598113,0.00004060006,8.4492166e-7,0.00011800562,0.00002074892,0.0000027618971,0.098200455,0.00049768266,0.01591475],"study_design_scores_gemma":[0.00031243116,0.000015027986,0.95782524,0.000024184743,0.00004301585,0.0000016544261,0.0008965588,0.00091978407,0.000060077393,0.0176221,0.022053786,0.00022611399],"about_ca_topic_score_codex":0.000857839,"about_ca_topic_score_gemma":0.0011785566,"teacher_disagreement_score":0.08057836,"about_ca_system_score_codex":0.000051031875,"about_ca_system_score_gemma":0.000020006379,"threshold_uncertainty_score":0.41753644},"labels":[],"label_agreement":null},{"id":"W3145840744","doi":"","title":"The role of the exchange rate in Canadian monetary policy: Evidence from a TVP-BVAR model","year":2018,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; Monetary policy; Exchange rate; Monetary economics; Central bank; Macroeconomics; Econometrics","score_opus":0.09439665319249303,"score_gpt":0.2633209965447842,"score_spread":0.16892434335229117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3145840744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9741316,0.0021733495,0.000041697345,0.010384971,0.00029697796,0.0002549525,0.000587525,0.0000106920015,0.012118276],"genre_scores_gemma":[0.99457693,0.0010973804,0.0001322978,0.0032048407,0.00047817873,0.00002063474,0.0000071207714,0.00003023996,0.0004523589],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978335,0.000053113476,0.0008853113,0.00046447525,0.000018500357,0.00074508996],"domain_scores_gemma":[0.9981678,0.000294375,0.00038002577,0.0008632083,0.000012424468,0.0002821485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009847371,0.00022169392,0.00045281605,0.00022958544,0.00026078333,0.00008501534,0.00088839314,0.0001776647,0.0002469178],"category_scores_gemma":[0.00037051731,0.00018689429,0.00018580655,0.00021200831,0.00031537673,0.0003539924,0.00016713873,0.00024764825,0.0005917689],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017209041,0.00008915376,0.86456186,0.000017438382,0.00018005726,0.0000017721993,0.0067483475,0.06336856,0.00003425248,0.052592747,0.0077146096,0.004519144],"study_design_scores_gemma":[0.00025585073,0.00004001694,0.114293985,0.000017247374,0.0000051334605,0.0000010900859,0.00005288646,0.6617938,0.00014866891,0.156971,0.06617272,0.00024758757],"about_ca_topic_score_codex":0.5532268,"about_ca_topic_score_gemma":0.41716337,"teacher_disagreement_score":0.75026786,"about_ca_system_score_codex":0.00063427555,"about_ca_system_score_gemma":0.00032924453,"threshold_uncertainty_score":0.7621328},"labels":[],"label_agreement":null},{"id":"W3147651526","doi":"10.1007/s00181-021-02192-3","title":"Exchange Rate Parities and Taylor Rule Deviations","year":2021,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"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":"Taylor rule; Economics; Credibility; Inflation (cosmology); Exchange rate; Inflation targeting; Econometrics; Benchmark (surveying); Monetary policy; Macroeconomics; Monetary economics; Central bank; Geography","score_opus":0.1339710531153634,"score_gpt":0.26399287532486193,"score_spread":0.13002182220949854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3147651526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9548965,0.003394413,0.0010067365,0.009120758,0.00047885688,0.00010758264,0.00047919314,0.000048283408,0.03046769],"genre_scores_gemma":[0.9851406,0.0018972968,0.0010548135,0.0070561217,0.00037161243,0.0000255784,0.00008613062,0.000035703535,0.004332105],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984703,0.000025299927,0.0006194965,0.000489934,0.00000810356,0.0003868807],"domain_scores_gemma":[0.99911124,0.0001373107,0.00019733369,0.00034211425,0.000010596208,0.00020140066],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00037096214,0.0001852356,0.0004705644,0.00011880851,0.00017027716,0.00017767688,0.0001257784,0.00013560127,0.0021559424],"category_scores_gemma":[0.00014809496,0.00024099942,0.000119793134,0.000080130485,0.000087053035,0.00039531421,0.00011664468,0.00015106531,0.0012841006],"study_design_candidate":"not_applicable","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":[0.00007884484,0.00046087182,0.45719647,0.000245753,0.00053865387,0.00004711166,0.004511761,0.0050036963,0.000028060193,0.4632074,0.058732297,0.00994906],"study_design_scores_gemma":[0.0010982979,0.00005695252,0.0904789,0.000007950495,0.000017076867,0.00004957335,0.00019687618,0.03873615,0.00021365422,0.19111943,0.67729604,0.000729084],"about_ca_topic_score_codex":0.00014455947,"about_ca_topic_score_gemma":0.00009341307,"teacher_disagreement_score":0.6185638,"about_ca_system_score_codex":0.0001142582,"about_ca_system_score_gemma":0.000027917104,"threshold_uncertainty_score":0.99949354},"labels":[],"label_agreement":null},{"id":"W3177397933","doi":"10.1007/s00181-023-02481-z","title":"Modeling interest rate setting at the European Central Bank with bargaining models and counterfactuals","year":2023,"lang":"en","type":"article","venue":"Empirical Economics","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":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Social Sciences and Humanities Research Council of Canada; Government of Ontario","keywords":"Interest rate; Economics; Counterfactual thinking; Monetary policy; Counterfactual conditional; Forward guidance; Member states; Macroeconomics; Monetary economics; Voting; Central bank; International economics; Inflation targeting; Credit channel; European union; Political science","score_opus":0.19153267347307412,"score_gpt":0.2676563525725295,"score_spread":0.07612367909945539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177397933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9726867,0.00024754458,0.0030171755,0.0031195385,0.00017547379,0.00018372669,0.00020846308,0.00009906532,0.020262301],"genre_scores_gemma":[0.99609315,0.00042326603,0.00015241597,0.0021348665,0.0002542771,0.000008907909,0.000053015945,0.00007297225,0.00080712175],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99783677,0.00007208061,0.0007406958,0.0006130445,0.000014753544,0.0007226697],"domain_scores_gemma":[0.9989262,0.00020445752,0.00023287037,0.0004172522,0.0000070614415,0.00021214751],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016276757,0.0002767942,0.00043901688,0.00014883022,0.0003590505,0.00024263049,0.00029495527,0.000078090496,0.00017903307],"category_scores_gemma":[0.000062529136,0.00024225998,0.00009705262,0.00010188315,0.00011977294,0.0005137746,0.00028932115,0.00025695327,0.0010907233],"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":[0.00005274954,0.000013029678,0.013337221,0.000013044609,0.000096745374,0.0000071991167,0.0024082519,0.97531766,0.0000031546256,0.0058474587,0.002026087,0.0008774212],"study_design_scores_gemma":[0.0005342977,0.000049160175,0.004292005,0.0000152409975,0.000008616118,0.000019716328,0.00023442393,0.9733691,0.000010899973,0.01568727,0.0054350127,0.00034424366],"about_ca_topic_score_codex":0.00022399105,"about_ca_topic_score_gemma":0.00018828233,"teacher_disagreement_score":0.023406444,"about_ca_system_score_codex":0.00020027244,"about_ca_system_score_gemma":0.000019161549,"threshold_uncertainty_score":0.999687},"labels":[],"label_agreement":null},{"id":"W3193970765","doi":"10.1007/s00181-021-02117-0","title":"Economic impact payment, human mobility and COVID-19 mitigation in the USA","year":2021,"lang":"en","type":"article","venue":"Empirical Economics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Payment; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Economics; Business; Natural resource economics; Finance; Virology; Medicine; Outbreak; Infectious disease (medical specialty)","score_opus":0.3213937582631765,"score_gpt":0.4956273056479698,"score_spread":0.1742335473847933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193970765","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9853718,0.00008482909,0.00027538545,0.012675848,0.00004410084,0.00027198784,0.000041522948,0.000027105487,0.0012074013],"genre_scores_gemma":[0.9898854,0.00013630107,0.00044637333,0.0092948275,0.00009556968,0.0000516102,0.000015564,0.0000106290745,0.00006374746],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982497,0.00037539907,0.0005827007,0.00046504446,0.000041105133,0.00028605646],"domain_scores_gemma":[0.99437124,0.004891389,0.00015972595,0.00040907488,0.0000136507915,0.0001549454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016018957,0.00018532446,0.00044813048,0.000033786113,0.00019041485,0.000064964195,0.00018999173,0.000119121454,0.0004378689],"category_scores_gemma":[0.0031885959,0.00013075818,0.00014585219,0.000067058696,0.00019672222,0.00009722235,0.0001982634,0.00021880625,0.000038104405],"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":[0.000017935114,0.00015234492,0.9564428,0.00006126431,0.000052093215,0.000010099883,0.0009480739,0.001259024,0.000014052396,0.029613154,0.011052914,0.0003762577],"study_design_scores_gemma":[0.00053157273,0.00006979796,0.5097813,0.0000045929473,0.00002020215,0.000012444566,0.00027532675,0.001907946,0.00002622584,0.4736345,0.013532836,0.00020325012],"about_ca_topic_score_codex":0.00060762686,"about_ca_topic_score_gemma":0.007718242,"teacher_disagreement_score":0.4466615,"about_ca_system_score_codex":0.0012734892,"about_ca_system_score_gemma":0.00024856083,"threshold_uncertainty_score":0.53321636},"labels":[],"label_agreement":null},{"id":"W3194684478","doi":"10.1007/s00181-021-02115-2","title":"Does economic inequality breed murder? An empirical investigation of the relationship between economic inequality and homicide rates in Canadian provinces and CMAs","year":2021,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Homicide; Inequality; Economic inequality; Demographic economics; Metropolitan area; Census; Economics; Poison control; Geography; Injury prevention; Demography; Sociology; Population; Medicine; Mathematics","score_opus":0.11042044418267469,"score_gpt":0.38954699560028627,"score_spread":0.27912655141761156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194684478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94954383,0.00007138735,0.0000016754178,0.049156,0.00026219216,0.00027206357,0.00015263206,0.000013625154,0.0005266206],"genre_scores_gemma":[0.9971184,0.000095908996,0.00012780454,0.0023093484,0.0002233432,0.000011308207,0.000029949217,0.000011692835,0.00007225364],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975157,0.00081606105,0.0007518283,0.00041116134,0.00005472104,0.0004505495],"domain_scores_gemma":[0.99725026,0.0016853734,0.00023062897,0.0002604134,0.000025996544,0.00054732163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019815366,0.00014972808,0.00041662436,0.000089281384,0.00041717145,0.00014596333,0.00020182205,0.00024032299,0.000049421575],"category_scores_gemma":[0.00080352335,0.00011676197,0.000055163022,0.00009230461,0.00054354215,0.00047489523,0.00009459974,0.00023959276,0.0000047324756],"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":[0.000005912312,0.000006193089,0.9860628,0.00003729286,0.000006214404,3.915219e-7,0.004343108,0.000044270822,2.970836e-7,0.009008756,0.00009085841,0.0003939099],"study_design_scores_gemma":[0.00026904378,0.000014566611,0.9659294,0.000018607081,0.000009943824,4.6792076e-7,0.0026432006,0.00039279746,0.0000377288,0.02724576,0.0032746233,0.00016386092],"about_ca_topic_score_codex":0.5471112,"about_ca_topic_score_gemma":0.9641254,"teacher_disagreement_score":0.41701415,"about_ca_system_score_codex":0.0010323907,"about_ca_system_score_gemma":0.0040313043,"threshold_uncertainty_score":0.71513605},"labels":[],"label_agreement":null},{"id":"W4286383129","doi":"10.1007/s00181-022-02272-y","title":"Noise shocks and business cycle fluctuations in three major European Economies","year":2022,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Bundesamt für Strassen","keywords":"Business cycle; Economics; Demand shock; Noise (video); Autoregressive model; Supply shock; Inflation (cosmology); Quarter (Canadian coin); Structural vector autoregression; Supply and demand; Econometrics; Monetary economics; Macroeconomics; Monetary policy","score_opus":0.06444374093728157,"score_gpt":0.24120635472839594,"score_spread":0.17676261379111435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286383129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9458993,0.00066937367,0.00029285456,0.0052518738,0.0005013552,0.00024020374,0.00047552946,0.00004536364,0.04662415],"genre_scores_gemma":[0.99543744,0.00018602874,0.00044015064,0.0028415665,0.00020254332,0.000054217282,0.00006533652,0.000057156125,0.00071553205],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977966,0.00004669988,0.0009800295,0.00067243626,0.00001565582,0.0004886019],"domain_scores_gemma":[0.99892324,0.00012858752,0.0003143649,0.00045559328,0.0000059041045,0.000172292],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008564564,0.00025174863,0.00055319787,0.00042616157,0.00034132964,0.00013116677,0.0003796472,0.00006344804,0.0022207466],"category_scores_gemma":[0.000088530636,0.00034546384,0.00010752319,0.00018886731,0.00010862482,0.00045590723,0.00040644602,0.00033071465,0.0007240268],"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":[0.000112926435,0.00031564996,0.69952273,0.000035172845,0.00011103632,0.000019275074,0.0018484762,0.2271325,0.0000036699369,0.060473308,0.007047072,0.0033781782],"study_design_scores_gemma":[0.0014966005,0.00007770529,0.6372508,0.0000039328634,0.000008476672,0.000034256187,0.00016082388,0.13439025,0.0000028588327,0.10822506,0.1177074,0.00064181944],"about_ca_topic_score_codex":0.0008406396,"about_ca_topic_score_gemma":0.0004956533,"teacher_disagreement_score":0.11066033,"about_ca_system_score_codex":0.00040301084,"about_ca_system_score_gemma":0.000038212802,"threshold_uncertainty_score":0.99989974},"labels":[],"label_agreement":null},{"id":"W4295300959","doi":"10.1007/s00181-022-02290-w","title":"Complex network analysis of volatility spillovers between global financial indicators and G20 stock markets","year":2022,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":30,"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":"Volatility (finance); Financial crisis; Volatility swap; Spillover effect; Economics; Volatility smile; Financial market; Volatility risk premium; Stock (firearms); Financial economics; Implied volatility; Bivariate analysis; Stock market; Monetary economics; Business; Finance; Geography; Macroeconomics","score_opus":0.04095144399900901,"score_gpt":0.2674912680886032,"score_spread":0.22653982408959417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295300959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.984365,0.0001967001,0.0011402302,0.00042704135,0.00022624282,0.00022262447,0.0043602046,0.00002194249,0.009040054],"genre_scores_gemma":[0.99867076,0.000028427648,0.00045083792,0.00044264173,0.00008497803,0.000015210192,0.0002325878,0.000014706169,0.000059847753],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976061,0.00008562278,0.0011574294,0.00068827986,0.0000527724,0.00040977204],"domain_scores_gemma":[0.9982885,0.00026158735,0.0007357061,0.00049674633,0.000016514956,0.00020094708],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014845601,0.00022556799,0.0010817093,0.0003049849,0.0002708261,0.00004054872,0.0003717437,0.0001287523,0.0016358895],"category_scores_gemma":[0.00013619271,0.00030107997,0.00035508492,0.0012668265,0.00016649897,0.000114188944,0.0005143186,0.00026938345,0.0000035680468],"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":[0.00008268619,0.00006898661,0.984286,0.000013433674,0.00037139296,6.632183e-7,0.000063759384,0.0005886026,2.7088863e-8,0.011671377,0.0013732952,0.0014797657],"study_design_scores_gemma":[0.00031180526,0.00005917277,0.76719487,7.0151856e-7,0.000088256216,4.4500754e-7,0.000011645682,0.18875569,6.903541e-8,0.015021672,0.028342359,0.00021333148],"about_ca_topic_score_codex":0.00026679228,"about_ca_topic_score_gemma":0.00016706454,"teacher_disagreement_score":0.21709116,"about_ca_system_score_codex":0.0004581797,"about_ca_system_score_gemma":0.0000773493,"threshold_uncertainty_score":0.99994415},"labels":[],"label_agreement":null},{"id":"W4296555010","doi":"10.1007/s00181-022-02300-x","title":"Portfolio selection: from under-diversification to concentration","year":2022,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":2,"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 Prince Edward Island; University of Waterloo","funders":"","keywords":"Diversification (marketing strategy); Economics; Efficient frontier; Portfolio; Econometrics; Estimator; Portfolio optimization; Investment strategy; Modern portfolio theory; Microeconomics; Financial economics; Mathematics; Statistics; Business; Profit (economics)","score_opus":0.08318409436880256,"score_gpt":0.2651002144417904,"score_spread":0.18191612007298782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296555010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9566417,0.00015102919,0.031662572,0.0032639434,0.00066869246,0.00021100386,0.0003399332,0.000059657243,0.007001489],"genre_scores_gemma":[0.99508655,0.0000424538,0.0013941402,0.0026549303,0.00020984946,0.000042804713,0.00012334048,0.000017974338,0.0004279779],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99870163,0.000018911112,0.00053305,0.00049360853,0.00002786612,0.00022492072],"domain_scores_gemma":[0.9994027,0.00004517081,0.00020107359,0.00021874394,0.000020431593,0.00011185852],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00030261665,0.00011432189,0.00024871234,0.00009999597,0.0003585297,0.000060966024,0.00020302423,0.00006116054,0.0021950228],"category_scores_gemma":[0.00004228803,0.00017095011,0.0000924547,0.00023474645,0.000017897402,0.00019376118,0.00011041321,0.00018707322,0.0005702138],"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":[0.00021236716,0.00034420527,0.42090333,0.0000057677366,0.00008669769,0.00000232604,0.0022872905,0.22045818,0.00006259959,0.32440153,0.026131092,0.005104604],"study_design_scores_gemma":[0.00071016775,0.00019357141,0.123237655,0.0000020363912,0.000009890479,0.0000035702071,0.00038403602,0.2257219,0.00011359484,0.16770598,0.4813809,0.0005366824],"about_ca_topic_score_codex":0.0006323836,"about_ca_topic_score_gemma":0.000055359684,"teacher_disagreement_score":0.45524985,"about_ca_system_score_codex":0.00059878145,"about_ca_system_score_gemma":0.00006204171,"threshold_uncertainty_score":0.9987171},"labels":[],"label_agreement":null},{"id":"W4317880803","doi":"10.1007/s00181-023-02358-1","title":"Hedging strategies among financial markets: the case of green and brown assets","year":2023,"lang":"en","type":"article","venue":"Empirical Economics","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":"York University","funders":"","keywords":"Bond; Hedge; Financial economics; Portfolio; Business; Bond market; Economics; Finance","score_opus":0.03798316216914741,"score_gpt":0.2627557936278721,"score_spread":0.2247726314587247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317880803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9870099,0.00021207074,0.00022933462,0.0014685473,0.0002304835,0.00016672442,0.00022856974,0.000037125697,0.010417265],"genre_scores_gemma":[0.9988853,0.00024370021,0.00009793339,0.00013918438,0.000089332854,0.000014051177,0.000013814544,0.000019826039,0.00049686356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986018,0.000031861236,0.0006686565,0.00038816972,0.000013936325,0.00029559238],"domain_scores_gemma":[0.9989046,0.00031216574,0.00030085215,0.0003728336,0.000019903679,0.000089663605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011966585,0.00015928035,0.00039906113,0.00014563401,0.00016925677,0.000112396854,0.00020483739,0.00013276801,0.00015443093],"category_scores_gemma":[0.00018751739,0.00015280195,0.000117007585,0.00023517958,0.00021937053,0.0002735156,0.0001881771,0.0001945954,0.0000237817],"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":[0.000042038002,0.00005254649,0.8984511,0.00009509855,0.000060089613,0.000071961615,0.00063552184,0.00011332293,8.3584047e-7,0.08968998,0.002396226,0.008391302],"study_design_scores_gemma":[0.00030889874,0.00003707786,0.54649967,0.0000074129593,0.0000056815834,0.000036588946,0.00025029125,0.29308698,0.0000016638683,0.15026303,0.009280732,0.00022195937],"about_ca_topic_score_codex":0.001054465,"about_ca_topic_score_gemma":0.0013545834,"teacher_disagreement_score":0.3519514,"about_ca_system_score_codex":0.000051875304,"about_ca_system_score_gemma":0.00004967047,"threshold_uncertainty_score":0.62310827},"labels":[],"label_agreement":null},{"id":"W4321071958","doi":"10.1007/s00181-023-02381-2","title":"The short-term impact of the 2020 pandemic lockdown on employment in Greece","year":2023,"lang":"en","type":"article","venue":"Empirical Economics","topic":"COVID-19 Pandemic Impacts","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":"University of Ottawa","funders":"University of Patras","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Tourism; Demographic economics; Term (time); Economics; Intervention (counseling); Government (linguistics); Geography; Medicine","score_opus":0.0994257992279475,"score_gpt":0.33918646857178103,"score_spread":0.23976066934383353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321071958","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99113,0.0001941769,0.0000144697015,0.0051699937,0.00054219237,0.00036681344,0.00014707891,0.000046292844,0.0023889763],"genre_scores_gemma":[0.9971451,0.00079124887,0.000005397725,0.0011175018,0.00013607388,0.000029884395,0.000008630931,0.00003763089,0.00072849344],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99788994,0.000040719147,0.0009895732,0.00046299712,0.00004512082,0.00057166576],"domain_scores_gemma":[0.9979832,0.00072899036,0.0003156275,0.0008308861,0.000014169051,0.0001271334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010885021,0.0002360706,0.00048940966,0.00017944396,0.0001407476,0.000066279266,0.00074889284,0.00016461538,0.00011210626],"category_scores_gemma":[0.00050248386,0.00016887246,0.0003781524,0.0005624117,0.00015231012,0.00011541284,0.00027470515,0.00038712609,0.00060661894],"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":[0.000054454234,0.000053009688,0.97917455,0.000007174739,0.000058982456,0.000002035453,0.00049660716,0.008229459,0.000009166291,0.0017788449,0.007551016,0.0025846912],"study_design_scores_gemma":[0.0005159877,0.00012997874,0.9538413,0.000018500197,0.0000042956153,0.00000366187,0.00002608596,0.009769528,0.000027836535,0.010409693,0.025018632,0.0002344875],"about_ca_topic_score_codex":0.0003597261,"about_ca_topic_score_gemma":0.0003677942,"teacher_disagreement_score":0.025333248,"about_ca_system_score_codex":0.0010407391,"about_ca_system_score_gemma":0.00017385658,"threshold_uncertainty_score":0.7797062},"labels":[],"label_agreement":null},{"id":"W4362638454","doi":"10.1007/s00181-023-02406-w","title":"DS-HECK: double-lasso estimation of Heckman selection model","year":2023,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","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":"Université de Montréal","funders":"Japan Society for the Promotion of Science; Australian Research Council; Russian Science Foundation","keywords":"Estimator; Lasso (programming language); Econometrics; Selection (genetic algorithm); Model selection; Consistency (knowledge bases); Feature selection; Selection bias; Statistics; Mathematics; Computer science; Artificial intelligence","score_opus":0.1914133336604218,"score_gpt":0.3040603734150777,"score_spread":0.1126470397546559,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362638454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9754998,0.000058277146,0.0074867094,0.0016596386,0.0003275343,0.00021271393,0.00018832448,0.0001383849,0.014428606],"genre_scores_gemma":[0.9951754,0.00017526337,0.0017510118,0.00047073636,0.00013835318,0.0000234233,0.00009823532,0.000043279273,0.0021243053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979761,0.000010381362,0.0010479704,0.0004840468,0.000020431147,0.0004610483],"domain_scores_gemma":[0.99893314,0.00006916685,0.00048449764,0.0003478937,0.000011076929,0.00015424205],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006190895,0.00021389822,0.00057289854,0.00045190015,0.000114748094,0.00005866747,0.000245372,0.00020184478,0.00032875247],"category_scores_gemma":[0.00005941385,0.00027431684,0.00021199904,0.0002857775,0.00006815233,0.00049870746,0.00007718675,0.00017499193,0.0026246551],"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":[0.000061945575,0.000053300304,0.013028373,0.000027237367,0.000051766343,3.4947925e-7,0.0003623163,0.94278485,0.000007822647,0.03446078,0.008451695,0.00070955575],"study_design_scores_gemma":[0.00081422576,0.00006277882,0.006115306,0.000004810479,0.00000694848,0.0000035800142,0.000016463562,0.92530537,0.00021459178,0.062001757,0.005188626,0.000265553],"about_ca_topic_score_codex":0.00024840137,"about_ca_topic_score_gemma":0.00003803038,"teacher_disagreement_score":0.027540976,"about_ca_system_score_codex":0.00023574154,"about_ca_system_score_gemma":0.000043984106,"threshold_uncertainty_score":0.9999709},"labels":[],"label_agreement":null},{"id":"W4378672602","doi":"10.1007/s00181-023-02432-8","title":"The oil price-macroeconomy dependence","year":2023,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; University of Calgary","funders":"","keywords":"Economics; Copula (linguistics); Oil price; Econometrics; Markov chain; Tail dependence; Context (archaeology); Monetary economics; Mathematics; Statistics; Multivariate statistics","score_opus":0.046916240226972036,"score_gpt":0.2680525956786183,"score_spread":0.22113635545164623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378672602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73783,0.00052251085,0.00058798824,0.010027974,0.0013744013,0.00014607445,0.00017058461,0.0002085933,0.2491319],"genre_scores_gemma":[0.97433513,0.0027175983,0.00030661438,0.0012895851,0.00030104173,0.00009113348,0.000037767215,0.000056946938,0.020864172],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99786156,0.000024339828,0.0008642333,0.0006062828,0.000024597832,0.0006190002],"domain_scores_gemma":[0.99825937,0.0004893913,0.00032253336,0.0007227427,0.000024848854,0.00018112938],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016497247,0.0002057591,0.00037481717,0.00012883317,0.00044342337,0.00026080236,0.0006452605,0.00014471635,0.0004559349],"category_scores_gemma":[0.00028410341,0.00019781383,0.00020780961,0.0003194302,0.00014661564,0.00023291518,0.00025842935,0.0002682763,0.0029485312],"study_design_candidate":"not_applicable","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":[0.00005718689,0.00007987005,0.62447697,0.000037170466,0.00013959955,0.0000083145205,0.00032212806,0.00031310972,0.0000011880403,0.32145533,0.024355637,0.02875347],"study_design_scores_gemma":[0.0002304977,0.00001871002,0.033328824,0.0000023153523,0.0000020030961,0.0000030729395,0.00004094629,0.19440944,0.0000024480903,0.11503391,0.6566787,0.000249141],"about_ca_topic_score_codex":0.00006488652,"about_ca_topic_score_gemma":0.00013874371,"teacher_disagreement_score":0.632323,"about_ca_system_score_codex":0.00020242347,"about_ca_system_score_gemma":0.000060922877,"threshold_uncertainty_score":0.99782777},"labels":[],"label_agreement":null},{"id":"W4380051600","doi":"10.1007/s00181-023-02441-7","title":"When to use matching and weighting or regression in instrumental variable estimation? Evidence from college proximity and returns to college","year":2023,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"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":"Institut für Arbeitsmarkt- und Berufsforschung","keywords":"Instrumental variable; Covariate; Econometrics; Propensity score matching; Weighting; Estimator; Matching (statistics); Average treatment effect; Statistics; Variance (accounting); Regression; Economics; Estimation; Variance inflation factor; Linear regression; Mathematics; Multicollinearity","score_opus":0.21134094600946787,"score_gpt":0.41446308657484643,"score_spread":0.20312214056537856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380051600","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898372,0.0000060974526,0.0067514363,0.002117014,0.000055383254,0.00075080665,0.0002163603,0.0001931448,0.00007255582],"genre_scores_gemma":[0.49147955,0.00003945756,0.5075683,0.00051222177,0.00002658365,0.000088490546,0.000009202404,0.00002922099,0.00024696614],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99867505,0.000065098546,0.00046145025,0.00044571748,0.00008159736,0.00027111318],"domain_scores_gemma":[0.99746543,0.0019361285,0.00011583217,0.0002628838,0.00002634606,0.00019337394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004753864,0.00018860558,0.00035931187,0.00016520552,0.000112935966,0.00009201275,0.00014484342,0.00012304899,0.000045978846],"category_scores_gemma":[0.0018041825,0.00016466092,0.000016700982,0.00027177995,0.000035034067,0.0008754426,0.0004725269,0.00019112244,0.000014706145],"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":[0.0038416432,0.0008290724,0.4908371,0.0013067545,0.00023407582,0.00041096075,0.06603041,0.0038934692,0.013439933,0.32628098,0.07066706,0.022228524],"study_design_scores_gemma":[0.00050227996,0.00021172599,0.011580606,0.0012875925,0.000017791122,0.000017357686,0.0011477654,0.03999366,0.0023658,0.94154507,0.00084784266,0.00048250108],"about_ca_topic_score_codex":0.00020327826,"about_ca_topic_score_gemma":0.000901335,"teacher_disagreement_score":0.6152641,"about_ca_system_score_codex":0.0002921111,"about_ca_system_score_gemma":0.00008268634,"threshold_uncertainty_score":0.6714677},"labels":[],"label_agreement":null},{"id":"W4381805392","doi":"10.1007/s00181-023-02456-0","title":"Bribery, regulation and firm performance: evidence from a threshold model","year":2023,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":17,"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 Guelph","funders":"","keywords":"Limiting; Business; Monetary economics; Language change; Industrial organization; Microeconomics; Economics","score_opus":0.14830766257426803,"score_gpt":0.3471237904297185,"score_spread":0.1988161278554505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381805392","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983791,0.00003303413,0.000080362224,0.0054252823,0.00030168527,0.000118615244,0.0000053449444,0.00008508989,0.010159585],"genre_scores_gemma":[0.9900404,0.0016335754,0.00032150635,0.0007031788,0.00012048769,0.000010597323,0.0000122465335,0.000007879564,0.007150078],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992897,0.000014926788,0.00019652022,0.00024692764,0.000052930183,0.0001989747],"domain_scores_gemma":[0.9995748,0.0001333529,0.000052791762,0.0001225303,0.000014480478,0.00010203799],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00041373784,0.00007021819,0.000121976496,0.00005440008,0.00020284187,0.000093078976,0.00011347171,0.00007950282,0.0003305246],"category_scores_gemma":[0.000047084908,0.00007967538,0.00003065332,0.00009038053,0.000071550516,0.00036586926,0.000084065876,0.00006520031,0.0009190274],"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":[0.00008829138,0.000033008815,0.69067407,0.000021987335,0.000038934162,0.000001147238,0.042401005,0.084685095,0.000035152774,0.0043023615,0.021386452,0.15633252],"study_design_scores_gemma":[0.00015540897,0.000009183694,0.25372013,0.000019950945,0.000004167379,2.1818099e-7,0.0005756458,0.7045363,0.000006884603,0.0027103468,0.038105413,0.00015634288],"about_ca_topic_score_codex":0.00016262868,"about_ca_topic_score_gemma":0.0003806689,"teacher_disagreement_score":0.61985123,"about_ca_system_score_codex":0.00020581235,"about_ca_system_score_gemma":0.00020253433,"threshold_uncertainty_score":0.99985886},"labels":[],"label_agreement":null},{"id":"W4388290569","doi":"10.1007/s00181-023-02512-9","title":"Inflation uncertainty","year":2023,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; University of Calgary","funders":"","keywords":"Economics; Inflation (cosmology); Output gap; Econometrics; Inflation rate; Markov chain; Monetary policy; Real interest rate; Economic stability; Autoregressive conditional heteroskedasticity; Monetary economics; Keynesian economics; Mathematics; Statistics; Volatility (finance); Physics","score_opus":0.06292192192997251,"score_gpt":0.2763543023509014,"score_spread":0.2134323804209289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388290569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9151299,0.00004214122,0.0006105697,0.002592404,0.0004986964,0.00012871783,0.00014043557,0.00015538203,0.08070172],"genre_scores_gemma":[0.9964329,0.00013943111,0.00020558976,0.0006852256,0.00014997883,0.00001795945,0.00010793027,0.000023535045,0.002237464],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986903,0.0000124043845,0.00057932513,0.0004005461,0.000014732751,0.000302701],"domain_scores_gemma":[0.9992257,0.00011350371,0.00018370184,0.00035166604,0.000015983822,0.00010947252],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007413251,0.00012728634,0.000292517,0.00019170072,0.00009811842,0.000070209535,0.00018769357,0.00012496258,0.00083051494],"category_scores_gemma":[0.00016605167,0.00015643932,0.00012699474,0.00030441384,0.000045472178,0.00017180262,0.00009327251,0.00013294224,0.0019583362],"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":[0.000023776625,0.000041060914,0.8454645,0.00001718673,0.000038550686,0.000002014058,0.0002697534,0.0023957007,0.0000015870856,0.13737506,0.011444374,0.002926427],"study_design_scores_gemma":[0.00019132237,0.00001507497,0.13166761,0.000001303295,0.0000011415775,5.684571e-7,0.000015416088,0.50750214,9.4875344e-7,0.18075007,0.17970152,0.0001529035],"about_ca_topic_score_codex":0.000077217344,"about_ca_topic_score_gemma":0.000057669076,"teacher_disagreement_score":0.7137969,"about_ca_system_score_codex":0.00014899595,"about_ca_system_score_gemma":0.000023188997,"threshold_uncertainty_score":0.99881876},"labels":[],"label_agreement":null},{"id":"W4391749957","doi":"10.1007/s00181-024-02556-5","title":"Business cycles in the USA: the role of monetary policy and oil shocks","year":2024,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":3,"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 Calgary","funders":"","keywords":"Economics; Monetary policy; Variance decomposition of forecast errors; Monetary economics; Demand shock; Dominance (genetics); Supply shock; Inflation (cosmology); Business cycle; Variance (accounting); Inflation targeting; Macroeconomics; Econometrics","score_opus":0.028386939661674875,"score_gpt":0.25951766473493154,"score_spread":0.23113072507325666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391749957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9506823,0.0034506498,0.00005177176,0.0064370227,0.00012737779,0.00007161347,0.00012500165,0.000008692113,0.039045587],"genre_scores_gemma":[0.9972723,0.0016352164,0.000059755508,0.00062056165,0.00015061053,0.0000127192125,0.0000075004023,0.0000133846415,0.000227953],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989455,0.000027592907,0.00050932704,0.0003038001,0.000017147468,0.00019664259],"domain_scores_gemma":[0.9991684,0.00035728555,0.00009365385,0.00033527377,0.00001002805,0.00003538753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00086574827,0.00012242916,0.00027173967,0.0001475368,0.000058980786,0.00011628681,0.00029217324,0.00008819608,0.00008492362],"category_scores_gemma":[0.00011487181,0.00008899844,0.000077963006,0.00030268123,0.00013628522,0.00013497486,0.0000998861,0.00019419278,0.000022198941],"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":[0.00001490306,0.000049569702,0.8039118,0.000046993508,0.00003093872,0.0000014658701,0.0008106562,0.000162845,0.0000010890202,0.17678519,0.0001594719,0.018025085],"study_design_scores_gemma":[0.000104146646,0.00001212066,0.5025035,0.000008843226,0.0000039732463,0.000005713795,0.00009319349,0.2511235,0.0000013805641,0.17084923,0.07517547,0.00011891759],"about_ca_topic_score_codex":0.0023249937,"about_ca_topic_score_gemma":0.0012067216,"teacher_disagreement_score":0.3014083,"about_ca_system_score_codex":0.00006649695,"about_ca_system_score_gemma":0.00005570535,"threshold_uncertainty_score":0.36292508},"labels":[],"label_agreement":null},{"id":"W4393377682","doi":"10.1007/s00181-024-02581-4","title":"Hybrid measures of multidimensional poverty","year":2024,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"","keywords":"Poverty; Econometrics; Economics; Economic growth","score_opus":0.08824305316845067,"score_gpt":0.3475125269490928,"score_spread":0.25926947378064213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393377682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89025295,0.00049585645,0.00043256665,0.007031273,0.0018700409,0.00013563874,0.00008984973,0.00011226697,0.09957958],"genre_scores_gemma":[0.9957243,0.00020191738,0.00040067028,0.0018828592,0.00043471105,0.0000028915229,0.000006934385,0.00001087676,0.0013348099],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99901956,0.000109470086,0.00029441473,0.00021734838,0.00013934344,0.00021988385],"domain_scores_gemma":[0.9993572,0.0002965894,0.00004537189,0.00013744114,0.000051366344,0.000111985166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082001503,0.00008567289,0.00018883136,0.000049452003,0.00013480666,0.000040829396,0.00014864022,0.000073479154,0.00047481878],"category_scores_gemma":[0.00023468374,0.0000766301,0.00014298745,0.0000680553,0.00018410242,0.00019381195,0.000047714064,0.000121659796,0.00017844491],"study_design_candidate":"not_applicable","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":[0.00009659053,0.0003190323,0.023468848,0.000093058305,0.00017952344,0.000017518752,0.0106162345,0.00030026573,0.00018219442,0.65106124,0.28044045,0.033225007],"study_design_scores_gemma":[0.00012551427,0.000030412906,0.0030799522,0.000014661907,0.000011580395,0.0000012443654,0.00024158749,0.0024420635,0.00052934507,0.017721912,0.97564805,0.00015370548],"about_ca_topic_score_codex":0.0008354793,"about_ca_topic_score_gemma":0.0003316683,"teacher_disagreement_score":0.69520754,"about_ca_system_score_codex":0.00017801825,"about_ca_system_score_gemma":0.00038290344,"threshold_uncertainty_score":0.5198933},"labels":[],"label_agreement":null},{"id":"W4396895548","doi":"10.1007/s00181-024-02606-y","title":"Do consumer price indices in oil-producing economies respond differently to oil market shocks? Evidence from Canada","year":2024,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Oil price; Economics; Monetary economics","score_opus":0.04606397649412276,"score_gpt":0.2676274982384592,"score_spread":0.22156352174433647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396895548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9674919,0.005152264,0.00007036903,0.005887938,0.001568379,0.00011987894,0.0011037264,0.00005192815,0.018553564],"genre_scores_gemma":[0.99111307,0.0020943154,0.000542448,0.0012723398,0.0002616989,0.000063287334,0.00003304804,0.000060974176,0.004558802],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962624,0.00007395672,0.0014140866,0.0015429474,0.000051956045,0.0006546976],"domain_scores_gemma":[0.99708706,0.0014516129,0.00025694395,0.0008404553,0.000026159747,0.00033774856],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014658598,0.00039930028,0.0008616606,0.00045013533,0.00010991779,0.00056657253,0.0006355128,0.00020889938,0.003091613],"category_scores_gemma":[0.000791328,0.00046913067,0.0001510881,0.00037785698,0.0000702996,0.0005714009,0.00032671596,0.000484053,0.00019333459],"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":[0.00023134924,0.000063332416,0.9702258,0.00017619756,0.0001402532,0.000029764898,0.0013466912,0.00024373205,0.0000042253832,0.0015826928,0.011806291,0.0141496835],"study_design_scores_gemma":[0.00047983608,0.000054474778,0.61550826,0.00034024968,0.000015886848,0.0000045198603,0.00020243962,0.13295662,0.00002062948,0.013188955,0.23612002,0.001108111],"about_ca_topic_score_codex":0.20653602,"about_ca_topic_score_gemma":0.37540856,"teacher_disagreement_score":0.35471755,"about_ca_system_score_codex":0.0016339202,"about_ca_system_score_gemma":0.00054579234,"threshold_uncertainty_score":0.99977607},"labels":[],"label_agreement":null},{"id":"W4400000585","doi":"10.1007/s00181-024-02607-x","title":"Intergenerational earnings mobility in Chile: the tale of the upper tail","year":2024,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Intergenerational and Educational Inequality Studies","field":"Social Sciences","cited_by":7,"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 British Columbia","funders":"","keywords":"Earnings; Economics; Demographic economics; Econometrics; Finance","score_opus":0.057223242867022635,"score_gpt":0.3590025293127824,"score_spread":0.3017792864457598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400000585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91059965,0.00015867557,0.000018404036,0.07869882,0.0011006756,0.000095810356,0.00001790769,0.000008555327,0.009301485],"genre_scores_gemma":[0.99411935,0.000047976246,0.00004154255,0.0012283099,0.00055080786,0.000029178505,0.0000057576726,0.0000036019176,0.003973456],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99925005,0.00016205174,0.0002482685,0.00013745262,0.00009132015,0.00011083848],"domain_scores_gemma":[0.9994555,0.00034490242,0.00003591522,0.00009042883,0.000051726183,0.000021514532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008030101,0.000054434888,0.000079764606,0.000023461946,0.0002887396,0.000049459195,0.00019448386,0.000040287232,0.0004892069],"category_scores_gemma":[0.0003421617,0.0000327041,0.000092617825,0.00014042643,0.0003072382,0.00010059304,0.00006443837,0.00015444391,0.000038141166],"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":[0.000010852921,0.00015848955,0.18924238,0.0000151150325,0.000054387343,1.5341078e-7,0.03780534,0.0030363738,0.00003715592,0.70231986,0.066465184,0.00085468567],"study_design_scores_gemma":[0.00006132667,0.000014735297,0.30288202,0.000021516993,0.000007896399,7.9315123e-7,0.0040979763,0.0033071425,0.00019986638,0.038308453,0.6509754,0.00012283059],"about_ca_topic_score_codex":0.00074026233,"about_ca_topic_score_gemma":0.00439627,"teacher_disagreement_score":0.6640114,"about_ca_system_score_codex":0.0001415296,"about_ca_system_score_gemma":0.00034124227,"threshold_uncertainty_score":0.5356473},"labels":[],"label_agreement":null},{"id":"W4400945228","doi":"10.1007/s00181-024-02643-7","title":"How do climate policy uncertainty and renewable energy and clean technology stock prices co-move? evidence from Canada","year":2024,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":32,"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; Climate policy; Stock (firearms); Renewable energy; Clean technology; Clean energy; Natural resource economics; Climate change; Climate change mitigation; Financial economics; Monetary economics; Macroeconomics; Geography; Engineering; Ecology","score_opus":0.0279139182077371,"score_gpt":0.25719789827222284,"score_spread":0.22928398006448575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400945228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9725333,0.008684664,0.0006852609,0.012455577,0.00029903773,0.00012438073,0.0010462564,0.000065924214,0.004105624],"genre_scores_gemma":[0.9916278,0.006548035,0.00041155054,0.0006502786,0.00017209386,0.00001760398,0.000028359605,0.00003062449,0.00051365775],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982065,0.000016484813,0.0004922742,0.0008298988,0.00002562513,0.00042923368],"domain_scores_gemma":[0.9988633,0.0003496228,0.00018104723,0.00039761182,0.000018336621,0.00019007748],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036386063,0.00023772159,0.0004998551,0.00025030677,0.00014452625,0.0004921505,0.00023526279,0.00021195211,0.00008279119],"category_scores_gemma":[0.00020908294,0.00026342552,0.000055532237,0.00023962781,0.00015294262,0.00033553792,0.0002230494,0.00017978057,0.0000029984253],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007502368,0.000038972954,0.8644078,0.0001371927,0.00018757634,0.000020087451,0.00022711603,0.00027697976,0.00001015426,0.08332548,0.0070103966,0.044283226],"study_design_scores_gemma":[0.00030602157,0.00008156996,0.04170272,0.0000668135,0.000014032584,0.000011326826,0.00016481313,0.44323918,0.0000314442,0.15333797,0.36045504,0.00058905425],"about_ca_topic_score_codex":0.4355831,"about_ca_topic_score_gemma":0.43796116,"teacher_disagreement_score":0.8227051,"about_ca_system_score_codex":0.00046359704,"about_ca_system_score_gemma":0.00026753487,"threshold_uncertainty_score":0.9999818},"labels":[],"label_agreement":null},{"id":"W4405128396","doi":"10.1007/s00181-024-02693-x","title":"A decomposition of the variance of international trade flows","year":2024,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Economics; Variance decomposition of forecast errors; Variance (accounting); Decomposition; International economics; Econometrics; International trade; Chemistry","score_opus":0.0591822794528445,"score_gpt":0.268603979898127,"score_spread":0.20942170044528252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405128396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93354285,0.0016028116,0.0016006458,0.012722771,0.0035035787,0.00018645255,0.0007602901,0.00003507341,0.046045527],"genre_scores_gemma":[0.9980073,0.0003546442,0.00093094184,0.00041630017,0.00014882251,0.0000060336097,0.000011871216,0.000016413136,0.00010765127],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987833,0.000008630809,0.0007615935,0.00028010635,0.000016473756,0.00014991108],"domain_scores_gemma":[0.9993928,0.000067592744,0.00022203998,0.00026811997,0.0000050703616,0.000044360324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023892385,0.000109455694,0.00030235638,0.00009732659,0.00002818903,0.000043146592,0.0003979206,0.00009896223,0.000250729],"category_scores_gemma":[0.000029264307,0.000107853,0.0002609978,0.00013070024,0.00007153952,0.00021413945,0.00007384275,0.00012795435,0.000099840305],"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":[0.00003303645,0.00016447576,0.04326923,0.000090730624,0.00026574047,0.000001461052,0.0005316096,0.00616628,0.0001364269,0.94256216,0.0050695105,0.0017093297],"study_design_scores_gemma":[0.00061002275,0.00008353931,0.09922072,0.000078540674,0.000023617711,0.000025768417,0.000053757256,0.15854679,0.0011908412,0.16267544,0.5771123,0.00037866595],"about_ca_topic_score_codex":0.00003713117,"about_ca_topic_score_gemma":0.00001545613,"teacher_disagreement_score":0.7798867,"about_ca_system_score_codex":0.00013422377,"about_ca_system_score_gemma":0.000038616294,"threshold_uncertainty_score":0.43981177},"labels":[],"label_agreement":null},{"id":"W4407124772","doi":"10.1007/s00181-025-02715-2","title":"Clan culture and private insurance take-up","year":2025,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Islamic Finance and Banking Studies","field":"Business, Management and Accounting","cited_by":1,"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 Windsor","funders":"National Natural Science Foundation of China","keywords":"Clan; Business; Economics; Actuarial science; Political science; Law","score_opus":0.01658197002650406,"score_gpt":0.24524484080207554,"score_spread":0.2286628707755715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407124772","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9609943,0.0002614288,0.0000646368,0.0038682087,0.00053713913,0.00008569668,0.0000025827903,0.000060041286,0.034125984],"genre_scores_gemma":[0.9842329,0.00022646248,0.000110091896,0.011584212,0.0004094277,0.000008604317,0.0000075000235,0.00000846579,0.0034123312],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99941766,0.0000021431408,0.00016611407,0.00022000681,0.00002346523,0.0001706053],"domain_scores_gemma":[0.9997599,0.000016843322,0.00007132624,0.00012352574,0.000026424144,0.0000019545787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000080264464,0.000116479365,0.00018161852,0.000064843945,0.00016211497,0.00014060055,0.000119442775,0.00006414876,0.000012433669],"category_scores_gemma":[0.000041995114,0.0001013617,0.000038097896,0.00013545773,0.00006941228,0.0003148691,0.00016000724,0.00010339086,0.00008471441],"study_design_candidate":"not_applicable","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":[0.000037226506,0.000038666138,0.4470713,0.00015844547,0.00005638258,0.000002891136,0.00016944291,0.000032030686,0.000019533807,0.42825922,0.08008627,0.04406858],"study_design_scores_gemma":[0.00034421872,0.000003691784,0.27869546,0.00003122207,0.000013360972,4.019433e-7,0.000026540349,0.00045364542,0.00001320631,0.04696599,0.67331356,0.00013873864],"about_ca_topic_score_codex":0.000020594565,"about_ca_topic_score_gemma":0.00003910519,"teacher_disagreement_score":0.59322727,"about_ca_system_score_codex":0.00002092877,"about_ca_system_score_gemma":0.000010069358,"threshold_uncertainty_score":0.41334102},"labels":[],"label_agreement":null},{"id":"W4408961219","doi":"10.1007/s00181-025-02727-y","title":"Estimating flexible functional forms using macroeconomic data","year":2025,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","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":"University of British Columbia","funders":"Japan Society for the Promotion of Science","keywords":"Econometrics; Economics; Computer science; Mathematical economics","score_opus":0.3031392964367511,"score_gpt":0.3392580865883129,"score_spread":0.03611879015156183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408961219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8744524,0.0006801534,0.05990441,0.0027581286,0.0023557944,0.000296723,0.00088668,0.00013281667,0.058532905],"genre_scores_gemma":[0.9747867,0.00006471717,0.015900621,0.0051477137,0.0006353266,0.000015486747,0.0003382587,0.000054533746,0.0030566202],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99699056,0.000014141697,0.0013159439,0.0010194401,0.000014385169,0.00064551306],"domain_scores_gemma":[0.99789643,0.0001371656,0.00045252597,0.0013285151,0.000008968678,0.00017638398],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00084077055,0.00031658995,0.0007120731,0.00040466263,0.0003119048,0.00023236024,0.000844541,0.00021036708,0.0014674228],"category_scores_gemma":[0.00014846094,0.0003948023,0.00017759875,0.00015960139,0.00012350122,0.0011542562,0.0004233594,0.0002843353,0.001675009],"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":[0.00016027234,0.00026533112,0.19014692,0.00012780166,0.00059754873,0.0000040072255,0.0002187977,0.5535908,0.000015218791,0.19136344,0.056381434,0.0071284696],"study_design_scores_gemma":[0.00068180135,0.00001974356,0.0067373673,0.000012722599,0.000015577423,0.000013028676,0.000023244771,0.8008774,0.00003207511,0.10343364,0.08777483,0.00037857544],"about_ca_topic_score_codex":0.00035987154,"about_ca_topic_score_gemma":0.000035054854,"teacher_disagreement_score":0.24728663,"about_ca_system_score_codex":0.00052775786,"about_ca_system_score_gemma":0.00012690974,"threshold_uncertainty_score":0.9998504},"labels":[],"label_agreement":null},{"id":"W4411258466","doi":"10.1007/s00181-025-02775-4","title":"Spatial Nexus: Natural Resources and Economic Growth","year":2025,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Natural Resources and Economic Development","field":"Economics, Econometrics and Finance","cited_by":2,"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 Guelph","funders":"","keywords":"Nexus (standard); Natural resource; Economic geography; Spatial econometrics; Natural (archaeology); Economics; Natural resource economics; Regional science; Geography; Econometrics; Computer science; Political science","score_opus":0.018433528915106658,"score_gpt":0.23449128367164132,"score_spread":0.21605775475653466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411258466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8967396,0.0034315952,0.00027416204,0.0068613733,0.0017474466,0.0002338844,0.00007632522,0.00007809293,0.090557516],"genre_scores_gemma":[0.9892052,0.0006679763,0.00060007966,0.0034057163,0.0002566967,0.000024736108,0.000019441333,0.000031246942,0.005788913],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976473,0.000015262594,0.0009921049,0.00082983833,0.000015042702,0.00050046446],"domain_scores_gemma":[0.99902177,0.00015328013,0.00029953156,0.00033973574,0.000014382169,0.00017128744],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000427292,0.0003095406,0.00067486597,0.0003618142,0.00020865869,0.000270627,0.00039334156,0.00020021692,0.00039024765],"category_scores_gemma":[0.000101974816,0.00035555073,0.00016660261,0.00009581859,0.00015619675,0.000291199,0.00031820883,0.00030926926,0.00075195625],"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":[0.00017851409,0.000092791466,0.5665472,0.00008441576,0.00039826593,0.0000056955623,0.0011353373,0.00021169566,0.0000030752917,0.39067572,0.02486256,0.015804695],"study_design_scores_gemma":[0.0012755204,0.000049860966,0.15039906,0.000019944824,0.00001221491,0.000009698709,0.00014931076,0.019191666,0.00005233402,0.14537577,0.68281037,0.00065423636],"about_ca_topic_score_codex":0.00076925225,"about_ca_topic_score_gemma":0.00028678178,"teacher_disagreement_score":0.6579478,"about_ca_system_score_codex":0.00047946526,"about_ca_system_score_gemma":0.00006294602,"threshold_uncertainty_score":0.9998897},"labels":[],"label_agreement":null},{"id":"W4413738919","doi":"10.1007/s00181-025-02811-3","title":"Monetary policy spillovers from the USA to advanced and emerging economies","year":2025,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":2,"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 Calgary","funders":"","keywords":"Economics; Monetary policy; Emerging markets; Monetary economics; Macroeconomics; Economy; International economics","score_opus":0.049579629881893815,"score_gpt":0.27957283012985906,"score_spread":0.22999320024796524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413738919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9261507,0.0010015348,0.00043018375,0.048280396,0.000592594,0.00029882794,0.00045364664,0.00003537574,0.022756744],"genre_scores_gemma":[0.95703155,0.0009386468,0.0011428703,0.03818516,0.00041789093,0.000031440683,0.000027106456,0.000030069916,0.0021952612],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99781054,0.000021010394,0.00086568366,0.00074148615,0.000012214179,0.0005490745],"domain_scores_gemma":[0.9985396,0.00033931367,0.00023115461,0.00065328623,0.000006206049,0.00023042243],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00035452514,0.00030696663,0.0006351229,0.00030463035,0.00026753932,0.00018921234,0.00047123473,0.0001415239,0.0005121118],"category_scores_gemma":[0.00022709374,0.00031476197,0.0001701137,0.00019019123,0.00013409708,0.0004167624,0.00027894825,0.00022651235,0.0013284103],"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":[0.00020391138,0.000082704064,0.7363376,0.000022809536,0.00044306662,0.0000024916683,0.0022130955,0.055066235,0.0000108689355,0.13625307,0.046758942,0.022605216],"study_design_scores_gemma":[0.00070320535,0.000057728343,0.25930074,0.000014421569,0.000014022303,0.0000021868123,0.00017592305,0.018026106,0.00005560406,0.085279405,0.63589,0.00048063966],"about_ca_topic_score_codex":0.005881278,"about_ca_topic_score_gemma":0.0010870091,"teacher_disagreement_score":0.58913106,"about_ca_system_score_codex":0.00031758565,"about_ca_system_score_gemma":0.000059353693,"threshold_uncertainty_score":0.99993044},"labels":[],"label_agreement":null},{"id":"W4414291109","doi":"10.1007/s00181-025-02820-2","title":"Econometric analysis of the long-run relationship between preventive care spending and mortality: evidence from OECD countries, 1970–2019","year":2025,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Global Health Care Issues","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Canadian Institutes of Health Research","keywords":"Econometric analysis; Preventive care; Econometric model; Statistical analysis; Trend analysis","score_opus":0.15662036301257012,"score_gpt":0.4830922498914829,"score_spread":0.3264718868789128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414291109","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900243,0.0041229147,0.00009488942,0.0016888409,0.0006139247,0.0007485152,0.0008944837,0.000028625112,0.0017834664],"genre_scores_gemma":[0.9980652,0.00036181227,0.00013587541,0.00066631363,0.00012237934,0.000025104475,0.00011493756,0.000012354892,0.00049605634],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99737614,0.0005583278,0.0010872553,0.00049024617,0.00011243039,0.00037557687],"domain_scores_gemma":[0.9910037,0.0074808113,0.0005847809,0.00066450523,0.00012390551,0.00014231037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008036898,0.00018398579,0.00074051286,0.00048389865,0.0005198614,0.000024809511,0.00038421722,0.00030099726,0.0002709774],"category_scores_gemma":[0.0010529377,0.00016121751,0.00019033789,0.0010362793,0.00014968116,0.0002281296,0.00040813527,0.0005125893,0.0001239264],"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":[0.000016835224,0.000007988582,0.9949183,0.00013820035,0.00039696478,3.090118e-7,0.0019934585,0.00017249868,4.526094e-8,0.0012035862,0.0010097554,0.00014206115],"study_design_scores_gemma":[0.00028069425,0.000018786945,0.99146444,0.00023886336,0.0011377425,3.6640216e-8,0.0011852594,0.00028190445,0.000007081553,0.0024835472,0.0027761585,0.00012547235],"about_ca_topic_score_codex":0.003477252,"about_ca_topic_score_gemma":0.0062372964,"teacher_disagreement_score":0.008040827,"about_ca_system_score_codex":0.0010397715,"about_ca_system_score_gemma":0.00063736585,"threshold_uncertainty_score":0.65742594},"labels":[],"label_agreement":null},{"id":"W4414890093","doi":"10.1007/s00181-025-02834-w","title":"Oil-macroeconomy relationship over time: Does oil still matter?","year":2025,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":1,"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 Saskatchewan; Queen's University","funders":"","keywords":"Oil price; Shock (circulatory); Developing country; Geopolitics; Relevance (law); Panel data; Crude oil; Empirical evidence","score_opus":0.020854523553240082,"score_gpt":0.25714827772573273,"score_spread":0.23629375417249265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414890093","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64978856,0.00022799119,0.00036401715,0.0049914997,0.0007150338,0.000044894907,0.0003337259,0.00006050233,0.34347376],"genre_scores_gemma":[0.86084384,0.0001856723,0.0011845576,0.004419069,0.00016874407,0.00005277251,0.00008988725,0.000047526468,0.13300796],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974802,0.00003585686,0.0011808807,0.0008180407,0.000019576564,0.00046542948],"domain_scores_gemma":[0.9982512,0.00041001893,0.00037348844,0.00077592325,0.00002914605,0.00016022997],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00075002643,0.0002988383,0.00065496005,0.00031885365,0.00016992837,0.00021316053,0.00043365642,0.00028184964,0.006113393],"category_scores_gemma":[0.00018912388,0.0003221294,0.00027158856,0.00022847837,0.00012878305,0.0003615734,0.00021011103,0.00034748396,0.0023580007],"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":[0.00003342036,0.00009166319,0.9134259,0.000059564085,0.00007327237,9.475958e-7,0.00007063174,0.000048767,6.604604e-7,0.07422739,0.008952151,0.003015614],"study_design_scores_gemma":[0.0006694017,0.000014163323,0.25792608,0.000017517192,0.000012795502,0.0000012880723,0.000010366488,0.10778754,0.000003933829,0.1312979,0.5018112,0.00044778176],"about_ca_topic_score_codex":0.00011274715,"about_ca_topic_score_gemma":0.00007236913,"teacher_disagreement_score":0.6554998,"about_ca_system_score_codex":0.00041882932,"about_ca_system_score_gemma":0.00008213835,"threshold_uncertainty_score":0.99992305},"labels":[],"label_agreement":null},{"id":"W858425222","doi":"10.1007/s00181-018-1486-8","title":"Demographics and the demand for currency","year":2018,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Islamic Finance and Banking Studies","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Liberian dollar; Demographics; Economics; Currency; Value (mathematics); Monetary economics; Business; Finance; Demography","score_opus":0.026167587345848172,"score_gpt":0.25904372287073035,"score_spread":0.23287613552488218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W858425222","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9828312,0.00023817088,0.00091381796,0.009304807,0.00049383414,0.0002121947,0.0000020425373,0.000032500084,0.00597144],"genre_scores_gemma":[0.99030644,0.0001451821,0.00018332375,0.007196298,0.0020119718,0.000026562688,0.0000032794105,0.000010162374,0.00011680681],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995069,0.0000027975175,0.00014728402,0.00015932703,0.000021363963,0.00016230725],"domain_scores_gemma":[0.9996464,0.000108051914,0.000082832514,0.00010648719,0.000054458927,0.0000017209593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030467022,0.00008740959,0.00014798247,0.000044963195,0.0003409444,0.00011817466,0.000112408154,0.0000369846,0.0000098665],"category_scores_gemma":[0.000092764334,0.00005774154,0.000059375903,0.00008158388,0.00038289974,0.00020941833,0.00010007288,0.000049687962,0.000039775266],"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":[0.0001281062,0.000027232074,0.061513666,0.00005873405,0.00004918765,2.060832e-7,0.00019372048,0.0000039467736,7.681006e-7,0.8498101,0.04853048,0.039683837],"study_design_scores_gemma":[0.0016313205,0.000019325818,0.039079703,0.0000142171275,0.000063706175,9.906009e-7,0.00004317521,0.0105949715,0.0000037861794,0.34515044,0.6032077,0.00019063425],"about_ca_topic_score_codex":0.000013676653,"about_ca_topic_score_gemma":0.000072787574,"teacher_disagreement_score":0.55467725,"about_ca_system_score_codex":0.000005460877,"about_ca_system_score_gemma":0.000007257116,"threshold_uncertainty_score":0.2622303},"labels":[],"label_agreement":null}]}