{"meta":{"query_hash":"bde45758ee24","filters":{"venue":"Econometrics Journal"},"cohort_total":48,"direct_labels_cover":1,"predictions_cover":48,"exported":48,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/bde45758ee24","api":"https://metacan.xera.ac/api/v1/cohort?venue=Econometrics+Journal"},"results":[{"id":"W1543071511","doi":"10.1111/j.1368-423x.2012.00374.x","title":"Set inference in latent variables models","year":2012,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Latent variable; Inference; Mathematics; Confidence interval; Moment (physics); Test statistic; Statistics; Latent variable model; Statistic; Set (abstract data type); Econometrics; Confidence distribution; Asymptotic distribution; Applied mathematics; Statistical hypothesis testing; Computer science; Artificial intelligence","score_opus":0.3794764509327003,"score_gpt":0.4052846148440892,"score_spread":0.02580816391138885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1543071511","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032689762,0.00010391311,0.9957411,0.00015418955,0.00001574213,0.000025350464,0.00006942495,0.00009358813,0.0005277923],"genre_scores_gemma":[0.33881417,0.0007007232,0.65548134,0.00042430183,0.0003230705,0.0009294307,0.0011824238,0.00026491552,0.0018796982],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.96652716,0.024033295,0.0010798564,0.0027985438,0.0044863783,0.0010747507],"domain_scores_gemma":[0.72431713,0.24753778,0.0094679715,0.012811973,0.004656027,0.0012091548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.034591056,0.0016417917,0.0038221828,0.0058122864,0.0017156418,0.004324805,0.0069135022,0.003069453,0.0076024006],"category_scores_gemma":[0.20306644,0.0019189708,0.004461504,0.0043284614,0.0063718916,0.0074649383,0.009274412,0.008141692,0.0009758003],"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":[0.00013594738,0.00010598564,0.0020862995,0.00022165567,0.0003189295,0.00018442176,0.00045421324,0.12782237,0.0003230415,0.83252907,0.0011320357,0.034686096],"study_design_scores_gemma":[0.0000366345,0.000030513005,0.00023669383,0.000057219087,0.00003417014,0.00003411713,0.000032480395,0.39815578,0.00048435936,0.6001293,0.00074435706,0.0000243823],"about_ca_topic_score_codex":0.0030504644,"about_ca_topic_score_gemma":0.0020504547,"teacher_disagreement_score":0.034591056,"about_ca_system_score_codex":0.0024719753,"about_ca_system_score_gemma":0.0028441886,"threshold_uncertainty_score":0.1829372},"labels":[],"label_agreement":null},{"id":"W1549544496","doi":"10.1111/j.1368-423x.2010.00332.x","title":"Misspecification in moment inequality models: back to moment equalities?","year":2011,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Science Foundation","keywords":"Mathematics; Moment (physics); Applied mathematics; Bivariate analysis; Function (biology); Econometrics; Statistics","score_opus":0.4993481042209085,"score_gpt":0.33195585539792344,"score_spread":0.16739224882298503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1549544496","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032457344,0.0031037799,0.93793654,0.013919452,0.00026652284,0.000033748096,0.0002132616,0.00016769518,0.011901676],"genre_scores_gemma":[0.8981914,0.004337268,0.084869325,0.0034596208,0.0013624685,0.00019295166,0.00030143277,0.00028156993,0.0070041027],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9907479,0.0058246385,0.0003413014,0.0012356399,0.0011464288,0.0007040669],"domain_scores_gemma":[0.92166555,0.062335886,0.008152361,0.005469015,0.0017189779,0.00065835135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015332126,0.0013041557,0.002679442,0.0016864481,0.0010049714,0.0040342114,0.003017776,0.003073388,0.0068969633],"category_scores_gemma":[0.08777918,0.001030623,0.0023402504,0.0022004794,0.006655501,0.012456455,0.0048022172,0.008119434,0.00073754037],"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":[0.000042688956,0.000029562583,0.001967258,0.00014099861,0.00012958073,0.00023887954,0.0005176919,0.036100913,0.00012141934,0.9406896,0.0019015068,0.018119931],"study_design_scores_gemma":[0.00001039688,0.000019855297,0.0004273293,0.00006926261,0.000021002916,0.00006181737,0.0000799999,0.0615291,0.00014093854,0.93584704,0.0017678397,0.000025427347],"about_ca_topic_score_codex":0.0050040935,"about_ca_topic_score_gemma":0.0032579126,"teacher_disagreement_score":0.015332126,"about_ca_system_score_codex":0.002561101,"about_ca_system_score_gemma":0.0011415286,"threshold_uncertainty_score":0.081085026},"labels":[],"label_agreement":null},{"id":"W1607052612","doi":"10.1111/j.1368-423x.2010.00323.x","title":"Fully modified narrow‐band least squares estimation of weak fractional cointegration","year":2011,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Cointegration; Economics; Estimation; Econometrics; Management","score_opus":0.1643770830449845,"score_gpt":0.23792909408988944,"score_spread":0.07355201104490494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1607052612","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0862999,0.00029152102,0.9121196,0.00010766084,0.000021371654,0.000021633725,0.00006269055,0.00013099931,0.00094456045],"genre_scores_gemma":[0.7331537,0.00041991455,0.26370272,0.00006538849,0.00004302899,0.000069405774,0.00019340779,0.00004698353,0.0023055417],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995147,0.00023052577,0.00002386217,0.00009403747,0.00010388837,0.000032985303],"domain_scores_gemma":[0.9985663,0.0009086483,0.00022701017,0.00014442227,0.00013322869,0.00002040776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011343765,0.00059021544,0.0007352196,0.00048623455,0.00021955548,0.0006614724,0.00069638726,0.0007807446,0.0009936686],"category_scores_gemma":[0.006611433,0.00023000572,0.00049129786,0.0006403872,0.00044668396,0.00079988874,0.0006899363,0.00054451317,0.0002420479],"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":[0.00008265654,0.000060638038,0.0039909794,0.00012347518,0.00010187961,0.00019002022,0.00013865327,0.87443876,0.0078492295,0.028253604,0.00036639496,0.08440376],"study_design_scores_gemma":[0.0000037480493,0.000017293145,0.00051498716,0.0000047807252,0.00000671674,0.000010155166,0.000007737986,0.9939418,0.0007765776,0.004463242,0.00024623433,0.0000067731653],"about_ca_topic_score_codex":0.0040845787,"about_ca_topic_score_gemma":0.003976704,"teacher_disagreement_score":0.0040845787,"about_ca_system_score_codex":0.00027626535,"about_ca_system_score_gemma":0.0005663659,"threshold_uncertainty_score":0.00812161},"labels":[],"label_agreement":null},{"id":"W172253734","doi":"10.1111/ectj.12093","title":"Multiple fixed effects in binary response panel data models","year":2017,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Panel data; Binary number; Binary data; Computer science; Econometrics; Mathematics; Arithmetic","score_opus":0.31446421274860087,"score_gpt":0.27264252972494285,"score_spread":0.04182168302365802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W172253734","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009990836,0.0017549334,0.9825125,0.0016100251,0.00028145756,0.00016939917,0.0009660477,0.0002601074,0.0024546976],"genre_scores_gemma":[0.52365756,0.0052307355,0.44849417,0.0018404401,0.0014264158,0.0017703966,0.0031947868,0.00022174585,0.014163736],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9709815,0.022647563,0.0008285912,0.00312572,0.0016118939,0.00080479326],"domain_scores_gemma":[0.9048793,0.08076102,0.0059321355,0.006024898,0.0018793272,0.00052343996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0329359,0.0012996087,0.002766151,0.0024190696,0.0010453351,0.004294086,0.0041585634,0.0035124111,0.010367814],"category_scores_gemma":[0.0897757,0.0014924527,0.0024819663,0.0045690276,0.0019344931,0.0039067804,0.0031187418,0.0050484193,0.0018509033],"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":[0.0002007969,0.00019175073,0.018318634,0.0009009424,0.0010994284,0.0008324071,0.00077412964,0.21464343,0.0003174888,0.6532496,0.0073429174,0.10212862],"study_design_scores_gemma":[0.00013735765,0.00012891294,0.0040434003,0.0002885074,0.0003563284,0.00023964947,0.00023230734,0.4128741,0.00041544295,0.5629326,0.018234653,0.00011671977],"about_ca_topic_score_codex":0.0063486546,"about_ca_topic_score_gemma":0.0055862395,"teacher_disagreement_score":0.0329359,"about_ca_system_score_codex":0.0013397684,"about_ca_system_score_gemma":0.0012769185,"threshold_uncertainty_score":0.17418379},"labels":[],"label_agreement":null},{"id":"W1852960361","doi":"10.1111/j.1368-423x.2011.00352.x","title":"Rank estimation of partially linear index models","year":2011,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Simon Fraser University","keywords":"Component (thermodynamics); Mathematics; Rank (graph theory); Parametric statistics; Linear model; Linear regression; Index (typography); Derivative (finance); Applied mathematics; Log-linear model; General linear model; Proper linear model; Statistics; Monotone polygon; Econometrics; Bayesian multivariate linear regression; Computer science; Combinatorics; Economics","score_opus":0.32177777382840117,"score_gpt":0.3739421771381093,"score_spread":0.05216440330970812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1852960361","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022000272,0.0002649432,0.97644037,0.00021744077,0.000015776403,0.00003023212,0.00017781457,0.00019725444,0.0006557895],"genre_scores_gemma":[0.64989805,0.0011019269,0.33974355,0.00025429516,0.0002442703,0.00038907235,0.0017931538,0.00018590601,0.0063897097],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9910579,0.006781411,0.0002163703,0.0007109362,0.000842501,0.00039105353],"domain_scores_gemma":[0.9688297,0.022868564,0.003468587,0.0028683783,0.001615258,0.0003494165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009912541,0.0013790374,0.0021204795,0.0018032076,0.00052436115,0.0021737218,0.0021706345,0.0015112486,0.0024805842],"category_scores_gemma":[0.041444764,0.00077374943,0.001490011,0.002357346,0.001693143,0.0033771032,0.002050725,0.0018652598,0.00068034424],"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":[0.0002256286,0.000112114794,0.0064354734,0.00026204143,0.00034363905,0.00022720205,0.00021464714,0.6567787,0.0012744796,0.22365616,0.0023281835,0.10814171],"study_design_scores_gemma":[0.000014891696,0.00007126955,0.00064031413,0.000013632028,0.000022397999,0.000031496722,0.000018146413,0.9253626,0.0003717262,0.07275949,0.0006715614,0.00002245063],"about_ca_topic_score_codex":0.0031905822,"about_ca_topic_score_gemma":0.0035782892,"teacher_disagreement_score":0.009912541,"about_ca_system_score_codex":0.00093287334,"about_ca_system_score_gemma":0.0013258702,"threshold_uncertainty_score":0.05242312},"labels":[],"label_agreement":null},{"id":"W1899180799","doi":"10.1111/ectj.12030","title":"Point-optimal panel unit root tests with serially correlated errors","year":2014,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Center for Interuniversity Research and Analysis on Organizations","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Unit root; Statistic; Statistics; Variance (accounting); Centring; Mathematics; Point (geometry); Econometrics; Engineering; Economics","score_opus":0.050886664013331306,"score_gpt":0.20681740312239974,"score_spread":0.15593073910906843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1899180799","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22354877,0.0006301507,0.76152873,0.00080847234,0.00021731076,0.00028765784,0.001916186,0.0007801541,0.010282563],"genre_scores_gemma":[0.92488134,0.0004054704,0.0695383,0.0002740429,0.0002983,0.00039602423,0.0017582128,0.00017902224,0.0022692461],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.96782345,0.022076651,0.0018951942,0.0031779297,0.0037712622,0.0012554453],"domain_scores_gemma":[0.762541,0.2001524,0.014110048,0.015967302,0.005846052,0.0013831377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024588889,0.0007899921,0.002492505,0.0027473792,0.000574087,0.0021171968,0.0027624443,0.0018813673,0.009050221],"category_scores_gemma":[0.18596135,0.00083204097,0.0016557769,0.0040831105,0.0017740958,0.0044507687,0.0032364356,0.0028572513,0.0014373001],"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":[0.0020478056,0.00053741276,0.086917244,0.0005967643,0.0026415237,0.0021148196,0.0010172372,0.21169387,0.0032099287,0.36448756,0.014451174,0.31028464],"study_design_scores_gemma":[0.0004486495,0.00070317823,0.038670734,0.00009813035,0.00027751955,0.0003486786,0.0004885614,0.480455,0.0030225313,0.47071168,0.0046177898,0.00015754833],"about_ca_topic_score_codex":0.0009755958,"about_ca_topic_score_gemma":0.00074855675,"teacher_disagreement_score":0.024588889,"about_ca_system_score_codex":0.0006382521,"about_ca_system_score_gemma":0.001866266,"threshold_uncertainty_score":0.13003999},"labels":[],"label_agreement":null},{"id":"W1937520435","doi":"10.1111/j.1368-423x.2010.00328.x","title":"Short‐term forecasts of euro area GDP growth","year":2011,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":245,"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":"Banca d'Italia","keywords":"Bridging (networking); Exploit; Econometrics; Quarter (Canadian coin); Regression; Term (time); Real gross domestic product; Computer science; Economics; Statistics; Mathematics; Geography","score_opus":0.2624821405732601,"score_gpt":0.22848466598637132,"score_spread":0.03399747458688876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1937520435","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94644576,0.001540785,0.034499317,0.0009973409,0.00041303932,0.000026102945,0.007773279,0.0011040253,0.0072002504],"genre_scores_gemma":[0.989546,0.0004897976,0.0035917894,0.00003491677,0.000118784905,0.000014012543,0.005199459,0.00005191843,0.000953336],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996747,0.00009964487,0.000022530105,0.00008874693,0.00008668019,0.000027825505],"domain_scores_gemma":[0.99587125,0.0021467991,0.00074829895,0.00036301455,0.0007069664,0.00016371057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021108838,0.00053417607,0.00043726753,0.00089364656,0.00013248125,0.0009714595,0.00047482303,0.0007102191,0.0020839164],"category_scores_gemma":[0.009089052,0.00029018408,0.0002915212,0.00093641883,0.00016481146,0.0013787374,0.00035188667,0.00071324356,0.0008191453],"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":[0.0004030716,0.000105429164,0.12483715,0.0001187738,0.0002175242,0.00010568746,0.000119263466,0.79672945,0.0011794092,0.0047843186,0.010427185,0.060972787],"study_design_scores_gemma":[0.0000376931,0.00009379983,0.042568333,0.000043690412,0.000038191865,0.00003562702,0.00006270359,0.94840926,0.001683701,0.003430772,0.0035661578,0.000030077475],"about_ca_topic_score_codex":0.006550327,"about_ca_topic_score_gemma":0.005396443,"teacher_disagreement_score":0.006550327,"about_ca_system_score_codex":0.00031278454,"about_ca_system_score_gemma":0.0003593548,"threshold_uncertainty_score":0.01302439},"labels":[],"label_agreement":null},{"id":"W1973158386","doi":"10.1111/j.1368-423x.2008.00250.x","title":"Estimation of the stochastic conditional duration model via alternative methods","year":2008,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Western University","funders":"","keywords":"Generalized method of moments; Mathematics; Method of moments (probability theory); Maximum likelihood; Empirical likelihood; Applied mathematics; Conditional expectation; Likelihood function; Monte Carlo method; Function (biology); Statistics; Econometrics; Confidence interval; Estimator","score_opus":0.10655790093856843,"score_gpt":0.2954683027195382,"score_spread":0.1889104017809698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973158386","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013324221,0.00017520896,0.9859136,0.00008259688,0.000010984334,0.000018084975,0.00004919331,0.000118432195,0.0003077061],"genre_scores_gemma":[0.42852256,0.0007149629,0.56820136,0.00009848499,0.00009848132,0.00021078938,0.0004546,0.00017026305,0.001528588],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99598014,0.0027381652,0.00015171753,0.0003696317,0.0006283649,0.00013199827],"domain_scores_gemma":[0.97862875,0.016744694,0.0017505856,0.0016716603,0.00096405146,0.0002402141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007124966,0.0005324523,0.0011914342,0.0015971032,0.00030673662,0.0014664633,0.0018229003,0.0010524488,0.0023484174],"category_scores_gemma":[0.03603985,0.00052835926,0.00090035185,0.0014663823,0.0009788801,0.0032460222,0.0016652913,0.0014017673,0.0003939703],"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":[0.0002082025,0.000060816914,0.0046633217,0.00014111123,0.00013020175,0.00011212943,0.00027699102,0.67344916,0.0011998151,0.20929043,0.0007751699,0.10969263],"study_design_scores_gemma":[0.00001902006,0.000017687978,0.0006679402,0.000015195688,0.000009755866,0.000050042992,0.000013975993,0.96599966,0.0003196485,0.03205958,0.0008049604,0.000022613003],"about_ca_topic_score_codex":0.0044717113,"about_ca_topic_score_gemma":0.0024039047,"teacher_disagreement_score":0.007124966,"about_ca_system_score_codex":0.0010018861,"about_ca_system_score_gemma":0.0017580497,"threshold_uncertainty_score":0.037680864},"labels":[],"label_agreement":null},{"id":"W1995775717","doi":"10.1111/j.1368-423x.2008.00246.x","title":"Moment based regression algorithms for drift and volatility estimation in continuous-time Markov switching models","year":2008,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":17,"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 British Columbia; University of Calgary","funders":"Social Sciences and Humanities Research Council of Canada; Austrian Science Fund","keywords":"Sass; Volatility (finance); Econometrics; Moment (physics); Algorithm; Library science; Computer science; Operations research; Economics; Mathematics; World Wide Web","score_opus":0.14282520831656836,"score_gpt":0.35669033011019596,"score_spread":0.2138651217936276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995775717","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025472192,0.00039249245,0.99650383,0.00008903794,0.000019583586,0.000008838435,0.00002430907,0.0001693016,0.00024535725],"genre_scores_gemma":[0.27545497,0.0021028232,0.717619,0.00016211011,0.00024827765,0.00025114822,0.00040824967,0.00028459541,0.003468802],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987392,0.00074944866,0.00005933228,0.00016733707,0.00021609187,0.00006862145],"domain_scores_gemma":[0.99129945,0.0073177735,0.00054569734,0.000323763,0.00040865972,0.00010463579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033186106,0.0008505272,0.0016181661,0.0014966277,0.00041998204,0.0011675428,0.0018431585,0.0015096492,0.002690433],"category_scores_gemma":[0.01908472,0.0006970529,0.0009481817,0.0015981308,0.0009253858,0.0020999168,0.0012243873,0.0024009552,0.00073435204],"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":[0.000100167235,0.000042290772,0.00059906126,0.00010947538,0.00008919107,0.00007161477,0.000060526298,0.8234758,0.0011273222,0.104623765,0.0010121232,0.06868863],"study_design_scores_gemma":[0.00000534735,0.00000769547,0.000067563866,0.000006869879,0.0000046799078,0.000013346076,0.000002519101,0.982166,0.0001799797,0.017213332,0.0003244665,0.000008075758],"about_ca_topic_score_codex":0.0029814467,"about_ca_topic_score_gemma":0.0019143588,"teacher_disagreement_score":0.0033186106,"about_ca_system_score_codex":0.0009681835,"about_ca_system_score_gemma":0.00097646145,"threshold_uncertainty_score":0.017550707},"labels":[],"label_agreement":null},{"id":"W2000956261","doi":"10.1111/j.1368-423x.2009.00285.x","title":"Finite-sample distribution-free inference in linear median regressions under heteroscedasticity and non-linear dependence of unknown form","year":2009,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":39,"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":"","keywords":"Heteroscedasticity; Mathematics; Statistics; Nuisance parameter; Inference; Linear regression; Monte Carlo method; Parametric statistics; Asymptotic distribution; Linear model; Applied mathematics; Econometrics; Estimator; Computer science","score_opus":0.13034522669683446,"score_gpt":0.38191276767703763,"score_spread":0.2515675409802032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000956261","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013458369,0.00008227368,0.9858278,0.000079186735,0.000009480063,0.00002423762,0.000039686194,0.00015143935,0.00032741175],"genre_scores_gemma":[0.6475885,0.0003284801,0.34983754,0.0001428431,0.00008147124,0.0004136721,0.00032093984,0.00011501323,0.0011715954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9893169,0.0074614864,0.0003809032,0.0012477441,0.001288724,0.00030420572],"domain_scores_gemma":[0.7533515,0.22429658,0.010064491,0.008512704,0.0030029756,0.0007718034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0321456,0.0010754024,0.0024792205,0.0022487435,0.00068880693,0.0023939882,0.0033230104,0.0016004224,0.0032886332],"category_scores_gemma":[0.17758818,0.0011775739,0.0019726276,0.0017633899,0.004848991,0.003648704,0.0031808591,0.0034556903,0.0004506763],"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":[0.00036290425,0.00023453227,0.007247112,0.00033073343,0.0005955581,0.0004269055,0.0003906,0.4610457,0.0017913978,0.42926413,0.0007838235,0.097526535],"study_design_scores_gemma":[0.000060465656,0.000095513904,0.0009798426,0.000044303608,0.000043474713,0.000064284875,0.000028901914,0.773274,0.0018866123,0.22315349,0.00032975132,0.000039293667],"about_ca_topic_score_codex":0.0012473892,"about_ca_topic_score_gemma":0.0014768055,"teacher_disagreement_score":0.0321456,"about_ca_system_score_codex":0.0015506868,"about_ca_system_score_gemma":0.0021201447,"threshold_uncertainty_score":0.17000425},"labels":[],"label_agreement":null},{"id":"W2006834884","doi":"10.1111/j.1368-423x.2005.00165.x","title":"On the arbitrariness of some asymptotic test statistics based on generalized inverses","year":2005,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Mathematics; Statistics; Ancillary statistic; Estimator; Statistic; Completeness (order theory); PRESS statistic; Test statistic; Sufficient statistic; Weighting; Applied mathematics; Statistical hypothesis testing; Mathematical analysis","score_opus":0.0732137880782555,"score_gpt":0.29168445397711945,"score_spread":0.21847066589886394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006834884","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012455966,0.0006229028,0.9823715,0.0007710901,0.00006640316,0.000029113877,0.00005381472,0.00011348031,0.003515624],"genre_scores_gemma":[0.5208294,0.0023127305,0.46884623,0.0014133541,0.0008844616,0.0007010613,0.00035274948,0.0003895164,0.0042705936],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97900134,0.0141135035,0.00096624956,0.0023266824,0.0030665018,0.00052584906],"domain_scores_gemma":[0.7819467,0.19479445,0.0074830144,0.01037286,0.0045601125,0.00084283156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03994473,0.0011495359,0.0022419153,0.0028940358,0.0011428925,0.0034037833,0.0020629417,0.0029361076,0.0032915242],"category_scores_gemma":[0.23874371,0.00076615805,0.001828036,0.0024556045,0.011835184,0.006608885,0.0037111703,0.0057807043,0.00067378685],"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":[0.000042909356,0.00001256805,0.0008058125,0.000072959396,0.000039981653,0.0001871569,0.00014413333,0.012123437,0.0005078186,0.97268033,0.0005736501,0.01280939],"study_design_scores_gemma":[0.000032127682,0.000053259642,0.00050243264,0.000059428625,0.000023363249,0.0002531305,0.000028941084,0.0844654,0.00080361514,0.9119655,0.0017759954,0.000036872247],"about_ca_topic_score_codex":0.0007595801,"about_ca_topic_score_gemma":0.0004273067,"teacher_disagreement_score":0.03994473,"about_ca_system_score_codex":0.0014686504,"about_ca_system_score_gemma":0.0016051029,"threshold_uncertainty_score":0.21125042},"labels":[],"label_agreement":null},{"id":"W2023969011","doi":"10.1111/1368-423x.00091","title":"Multinomial probit estimation without nuisance parameters","year":2002,"lang":"ca","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Multinomial probit; Covariance; Mathematics; Multinomial distribution; Statistics; Monte Carlo method; Rank (graph theory); Econometrics; Covariance matrix; Probit; Law of total covariance; Estimation of covariance matrices; Set (abstract data type); Probit model; Covariance intersection; Computer science","score_opus":0.14305975602852325,"score_gpt":0.341287233149511,"score_spread":0.19822747712098773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023969011","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021643946,0.00010324641,0.9962063,0.000116598436,0.000018801888,0.000051222913,0.00009930455,0.0001244778,0.0011155916],"genre_scores_gemma":[0.14371184,0.00060049497,0.8470208,0.00014013117,0.00009825039,0.00075230433,0.00064783514,0.00014791742,0.006880462],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953837,0.0030217164,0.00021440923,0.00053781294,0.0006724496,0.00016988233],"domain_scores_gemma":[0.99182206,0.0058323215,0.0006886657,0.00082659785,0.0007431765,0.00008711243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00664656,0.0011405732,0.0017536619,0.0010482465,0.00081367046,0.0018436725,0.0017536677,0.0015766233,0.0072605642],"category_scores_gemma":[0.041979015,0.0008506135,0.001073544,0.002129516,0.000958985,0.0023664571,0.00212171,0.0020680598,0.0025097856],"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":[0.000111517,0.0001447791,0.005113812,0.0003667793,0.00024685432,0.0003771525,0.00034884445,0.277949,0.0011379292,0.47411597,0.0063991514,0.23368816],"study_design_scores_gemma":[0.000032357068,0.000044278015,0.00093736785,0.00007861917,0.000052344094,0.00015160181,0.000046616486,0.82678074,0.00061353226,0.16480578,0.00642869,0.000028145812],"about_ca_topic_score_codex":0.008516528,"about_ca_topic_score_gemma":0.009906081,"teacher_disagreement_score":0.008516528,"about_ca_system_score_codex":0.0010415482,"about_ca_system_score_gemma":0.003848526,"threshold_uncertainty_score":0.035150766},"labels":[],"label_agreement":null},{"id":"W2045648793","doi":"10.1111/j.1368-423x.2006.00183.x","title":"Unit root tests and structural change when the initial observation is drawn from its unconditional distribution","year":2006,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":7,"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":"","keywords":"Unit root; Cointegration; Econometrics; Asymptotic distribution; Mathematics; Statistic; Economics; Context (archaeology); Structural break; Statistics","score_opus":0.19102386225583662,"score_gpt":0.26548954168581546,"score_spread":0.07446567942997884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045648793","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07302271,0.003228632,0.9106559,0.0017206591,0.0002175707,0.00013753586,0.00041561553,0.00038927057,0.01021217],"genre_scores_gemma":[0.8756876,0.0030939307,0.11527541,0.00059571676,0.00055325095,0.0006613242,0.0008280566,0.00019413121,0.0031104821],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9806985,0.013928383,0.00060543575,0.001881015,0.0022971828,0.0005894479],"domain_scores_gemma":[0.7956521,0.18007275,0.010529986,0.010345391,0.0027530266,0.00064673676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02254654,0.0007879317,0.0018928193,0.0036360333,0.0006310841,0.0024302918,0.0019471879,0.0021510003,0.0067799673],"category_scores_gemma":[0.19373243,0.00053525966,0.0011833947,0.0050493698,0.0056434874,0.0063403635,0.00224528,0.003641223,0.0009386806],"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":[0.00024111687,0.00012471671,0.022039752,0.00035273217,0.0004093953,0.0008638664,0.0010926576,0.03808448,0.00068331853,0.7648607,0.004896009,0.16635138],"study_design_scores_gemma":[0.000044840668,0.0001682153,0.00746589,0.0001305363,0.0000572914,0.00028082484,0.00021814626,0.0932075,0.0007217714,0.8938306,0.0038253053,0.000049024926],"about_ca_topic_score_codex":0.0010051903,"about_ca_topic_score_gemma":0.0007082934,"teacher_disagreement_score":0.02254654,"about_ca_system_score_codex":0.0011247001,"about_ca_system_score_gemma":0.0009003142,"threshold_uncertainty_score":0.11923897},"labels":[],"label_agreement":null},{"id":"W2096708933","doi":"10.1111/j.1368-423x.2008.00236.x","title":"Asymptotic local power of pooled t-ratio tests for unit roots in panels with fixed effects","year":2008,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":50,"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; Center for Interuniversity Research and Analysis on Organizations; Université du Québec à Montréal","funders":"","keywords":"Unit root; Power (physics); Unit (ring theory); Library science; History; Demography; Mathematics; Sociology; Econometrics; Physics; Computer science; Mathematics education","score_opus":0.05191093548786536,"score_gpt":0.2316857431806975,"score_spread":0.17977480769283216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096708933","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09234728,0.0012072716,0.8987744,0.0004921029,0.00009528847,0.00016167063,0.00023611153,0.00056839286,0.0061174463],"genre_scores_gemma":[0.86430585,0.0007938356,0.130615,0.00039512743,0.00041486198,0.00079453166,0.0006285508,0.00034904058,0.0017031026],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9761948,0.016468847,0.00095652626,0.0029573785,0.0027316203,0.00069075933],"domain_scores_gemma":[0.62008774,0.3442249,0.011771245,0.016510168,0.006104211,0.0013017616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.042759363,0.0014628634,0.0034030878,0.0040229405,0.0006885851,0.002851981,0.0026165931,0.0024649655,0.008664043],"category_scores_gemma":[0.32821354,0.00070517237,0.003360778,0.0026221168,0.0052600037,0.006307529,0.0036066554,0.0022063807,0.0017385879],"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":[0.0018835132,0.00036050336,0.05111504,0.0015829379,0.003826303,0.003456879,0.0023983768,0.25086266,0.0067256005,0.34428966,0.006441236,0.32705727],"study_design_scores_gemma":[0.00034050416,0.001082757,0.022150438,0.00040650694,0.0010235268,0.0017766131,0.00066434644,0.49902725,0.005854063,0.4640968,0.0033313879,0.00024578595],"about_ca_topic_score_codex":0.00084072235,"about_ca_topic_score_gemma":0.0004320069,"teacher_disagreement_score":0.042759363,"about_ca_system_score_codex":0.0010394794,"about_ca_system_score_gemma":0.0012199304,"threshold_uncertainty_score":0.22613579},"labels":[],"label_agreement":null},{"id":"W2100811430","doi":"10.1111/j.1368-423x.2007.00225.x","title":"Size matters: covariance matrix estimation under the alternative","year":2007,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Monte Carlo method; Covariance matrix; Econometrics; Generalized method of moments; Mathematics; Covariance; Estimation; Statistics; Test (biology); Applied mathematics; Economics","score_opus":0.08875223255824052,"score_gpt":0.27430082438918363,"score_spread":0.1855485918309431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100811430","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07504978,0.0007631982,0.9091595,0.003903723,0.00031162397,0.00009772952,0.0002682071,0.00022832515,0.010217919],"genre_scores_gemma":[0.84279037,0.0009948026,0.14851367,0.0010960753,0.00077267,0.00024576855,0.00052444317,0.00017880603,0.0048834137],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98355156,0.010310007,0.0005272915,0.0027578736,0.0021928803,0.00066044385],"domain_scores_gemma":[0.88265496,0.09346315,0.006822651,0.012590437,0.0037115733,0.0007573367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0206557,0.00073920196,0.0014359055,0.0012333937,0.0009465141,0.0031948907,0.0023132907,0.002245327,0.011525178],"category_scores_gemma":[0.15676261,0.00052388257,0.0013188462,0.0019276874,0.003509675,0.007451116,0.0021996044,0.0033235336,0.0010626789],"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":[0.0003034653,0.00010694943,0.016832361,0.00019508979,0.000322339,0.00048755683,0.00049183884,0.027202604,0.0007749764,0.84171253,0.0052453354,0.10632497],"study_design_scores_gemma":[0.00010563257,0.00014254801,0.0071837306,0.00008751245,0.0000925262,0.00035912127,0.00023490522,0.14885543,0.00068440504,0.8386012,0.0035986265,0.00005441784],"about_ca_topic_score_codex":0.003849038,"about_ca_topic_score_gemma":0.0026523403,"teacher_disagreement_score":0.0206557,"about_ca_system_score_codex":0.00092015625,"about_ca_system_score_gemma":0.0021931545,"threshold_uncertainty_score":0.1092391},"labels":[],"label_agreement":null},{"id":"W2102591219","doi":"10.1111/1368-423x.00085","title":"Distributions of error correction tests for cointegration","year":2002,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":326,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Cointegration; Quantile; Statistic; Monte Carlo method; Sample (material); Sample size determination; Statistics; Error detection and correction; Mathematics; Standard error; Applied mathematics; Computer science; Econometrics; Algorithm; Physics","score_opus":0.23307865302906605,"score_gpt":0.2757505888953286,"score_spread":0.042671935866262556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102591219","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15803346,0.0015792417,0.82385963,0.001204921,0.00018242786,0.00040631488,0.0014481699,0.0020275428,0.011258312],"genre_scores_gemma":[0.92420566,0.00049055845,0.070334926,0.00027550236,0.0001944797,0.0009703716,0.0017141174,0.0005157368,0.0012986636],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97761744,0.011344762,0.001343772,0.0033284095,0.0053316974,0.0010338372],"domain_scores_gemma":[0.529443,0.43500778,0.009049352,0.015517913,0.00954529,0.0014365498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03471177,0.0009402372,0.0024013047,0.0085487105,0.0011664396,0.0038364907,0.0030005164,0.0029582684,0.010269761],"category_scores_gemma":[0.30916265,0.00066991936,0.0017064129,0.0037754246,0.006115427,0.0061846785,0.0027989165,0.0038479886,0.0012908193],"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":[0.0004889946,0.00016979262,0.032619383,0.0006439192,0.0005402533,0.0007372724,0.0012652169,0.09813496,0.0017250028,0.71286553,0.0077027907,0.1431069],"study_design_scores_gemma":[0.00014918204,0.0002912709,0.012388037,0.0003972698,0.000099483055,0.00093677297,0.00048562285,0.20115158,0.003928726,0.7743421,0.0056693982,0.00016060521],"about_ca_topic_score_codex":0.00082561735,"about_ca_topic_score_gemma":0.0002996635,"teacher_disagreement_score":0.03471177,"about_ca_system_score_codex":0.0017541067,"about_ca_system_score_gemma":0.0013508757,"threshold_uncertainty_score":0.18357557},"labels":[],"label_agreement":null},{"id":"W2105045605","doi":"10.1111/j.1368-423x.2008.00235.x","title":"Bootstrapping Autoregression under Non-stationary Volatility","year":2008,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":37,"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 Alberta","funders":"Yale University","keywords":"Bootstrapping (finance); Volatility (finance); Autoregressive model; Econometrics; Economics; Library science; Financial economics; History; Computer science","score_opus":0.11993949225471882,"score_gpt":0.24348384349072322,"score_spread":0.1235443512360044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105045605","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07714894,0.0003405728,0.9215321,0.00009465847,0.000029443707,0.000024286668,0.00003117982,0.00019182834,0.0006070202],"genre_scores_gemma":[0.82113576,0.00054871396,0.17703898,0.00007792438,0.00007657301,0.000072133174,0.00021762794,0.00014863911,0.0006836441],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99476033,0.0038883938,0.00018646204,0.00040667516,0.00059740647,0.0001607155],"domain_scores_gemma":[0.9528918,0.04144355,0.0018010791,0.0027770174,0.0009505177,0.00013600335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013007647,0.00055909937,0.0010238127,0.0011362848,0.000322136,0.0010786802,0.0016013271,0.0009574102,0.0009709769],"category_scores_gemma":[0.0726041,0.0003993724,0.000949208,0.0013005957,0.001524321,0.0023511716,0.0010715995,0.0012302481,0.0002358152],"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":[0.00022080184,0.00010964634,0.008222476,0.00018867568,0.00031983716,0.00055324653,0.00034325136,0.63266045,0.0033887823,0.23428118,0.0007075146,0.11900415],"study_design_scores_gemma":[0.000013961004,0.00004812426,0.001039492,0.000018223542,0.000022584616,0.00006666766,0.000026435133,0.9381907,0.0012656112,0.058960833,0.00033286543,0.000014433698],"about_ca_topic_score_codex":0.0019012296,"about_ca_topic_score_gemma":0.0012478022,"teacher_disagreement_score":0.013007647,"about_ca_system_score_codex":0.0004797994,"about_ca_system_score_gemma":0.0006179867,"threshold_uncertainty_score":0.06879181},"labels":[],"label_agreement":null},{"id":"W2113670824","doi":"10.1111/j.1368-423x.2008.00247.x","title":"Bootstrap inference in a linear equation estimated by instrumental variables","year":2008,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; McGill University","funders":"","keywords":"Instrumental variable; Inference; Econometrics; Library science; Sociology; Computer science; Economics; Artificial intelligence","score_opus":0.3436461324905379,"score_gpt":0.4059698372335064,"score_spread":0.0623237047429685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113670824","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07402614,0.00044865732,0.9227453,0.0006047867,0.000044299726,0.000046644593,0.00005260266,0.0002162587,0.0018154003],"genre_scores_gemma":[0.7882885,0.0008699529,0.20787254,0.00028787542,0.00018056217,0.00030639285,0.0002804284,0.00012017188,0.0017937467],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98989165,0.0080134235,0.00026006077,0.00050945015,0.0009835486,0.00034178904],"domain_scores_gemma":[0.8240288,0.16297425,0.0069547454,0.0035394349,0.0020808773,0.00042197766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022475427,0.000846688,0.0019514451,0.0019776574,0.0005842731,0.0012625885,0.0021516052,0.00145805,0.0031351265],"category_scores_gemma":[0.16884047,0.0004613892,0.0016198747,0.0022485296,0.0024478317,0.0021723495,0.0020308953,0.0022027346,0.00044108342],"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":[0.00039095306,0.00034935522,0.025032388,0.0004352148,0.0008693263,0.0010559651,0.000692859,0.26093996,0.0016400447,0.6012547,0.002217579,0.10512155],"study_design_scores_gemma":[0.00012311655,0.00009099897,0.0030563737,0.00008137778,0.000095376374,0.00007873442,0.00012151046,0.8267713,0.0016071566,0.16701756,0.0009216692,0.000034802502],"about_ca_topic_score_codex":0.0026001316,"about_ca_topic_score_gemma":0.0016628426,"teacher_disagreement_score":0.022475427,"about_ca_system_score_codex":0.00071128324,"about_ca_system_score_gemma":0.0013366892,"threshold_uncertainty_score":0.11886281},"labels":[],"label_agreement":null},{"id":"W2113798046","doi":"10.1111/j.1368-423x.2007.00216.x","title":"Estimation of impulse response functions using long autoregression","year":2007,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Estimator; Impulse response; Asymptotic distribution; Autoregressive model; Mathematics; Applied mathematics; Vector autoregression; Consistency (knowledge bases); Econometrics; Parametric statistics; Impulse (physics); Statistics","score_opus":0.12450601048206113,"score_gpt":0.2835555158086151,"score_spread":0.15904950532655399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113798046","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011419484,0.00030248423,0.9863797,0.00022330221,0.000034626166,0.000021368927,0.00006330879,0.0002942691,0.0012614549],"genre_scores_gemma":[0.57133275,0.0012990766,0.42008522,0.00033377018,0.00030600853,0.00031420178,0.00074523536,0.00020722127,0.00537661],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99584574,0.0026111042,0.00020699696,0.00047053894,0.0006194551,0.00024610446],"domain_scores_gemma":[0.98583984,0.011003102,0.0015328532,0.00084509264,0.00069099874,0.000088033376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0071436483,0.0008461685,0.0016066565,0.0026083235,0.00034848895,0.001803647,0.0014686281,0.0014739191,0.003628616],"category_scores_gemma":[0.029791031,0.0006080139,0.0013244855,0.0022571813,0.0008035834,0.0025389823,0.0011135797,0.0021919142,0.00085770286],"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":[0.00014437262,0.00030402283,0.017318968,0.00047490755,0.0010333799,0.00030175818,0.00071116525,0.3276132,0.0028040877,0.3925309,0.003097171,0.25366607],"study_design_scores_gemma":[0.00004593959,0.000112099464,0.006830949,0.00012437376,0.00011513141,0.00010903261,0.00011260478,0.8076457,0.002443509,0.17636834,0.0059746737,0.00011753986],"about_ca_topic_score_codex":0.002291002,"about_ca_topic_score_gemma":0.002177189,"teacher_disagreement_score":0.0071436483,"about_ca_system_score_codex":0.00093260483,"about_ca_system_score_gemma":0.0011963351,"threshold_uncertainty_score":0.03777969},"labels":[],"label_agreement":null},{"id":"W2134368299","doi":"10.1111/j.1368-423x.2010.00340.x","title":"Statistical inference in the presence of heavy tails","year":2012,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University","funders":"","keywords":"Inference; Statistical inference; History; Library science; Computer science; Statistics; Artificial intelligence; Mathematics","score_opus":0.23765496509282655,"score_gpt":0.42237806557790825,"score_spread":0.1847231004850817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134368299","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017665219,0.0063399677,0.95691144,0.010048794,0.0013394634,0.00010047508,0.00047799433,0.0004509586,0.0066657914],"genre_scores_gemma":[0.708495,0.0115201,0.2496213,0.005924864,0.0077413544,0.00070616667,0.0012824108,0.0005500219,0.014158856],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9483282,0.037442494,0.0022709735,0.004843856,0.005884073,0.0012303846],"domain_scores_gemma":[0.46415237,0.4847223,0.016754067,0.023083204,0.009350114,0.0019378645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06576843,0.00090977864,0.0034279015,0.0044654114,0.0017232832,0.0054468927,0.0023141264,0.0035124428,0.007391177],"category_scores_gemma":[0.35777655,0.0017412463,0.001973271,0.004763749,0.009877477,0.008441387,0.0044749645,0.009377655,0.0011684302],"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":[0.00018883661,0.00012599546,0.014617058,0.000751368,0.0011455,0.0010074816,0.000826834,0.053462896,0.0004003096,0.8442946,0.01922569,0.06395342],"study_design_scores_gemma":[0.00004472388,0.000042822023,0.0016023839,0.00020326614,0.00009452807,0.00015169091,0.00009647865,0.077405736,0.00019633668,0.91631216,0.003814982,0.00003488222],"about_ca_topic_score_codex":0.0046967,"about_ca_topic_score_gemma":0.0032096258,"teacher_disagreement_score":0.06576843,"about_ca_system_score_codex":0.002197254,"about_ca_system_score_gemma":0.0037953658,"threshold_uncertainty_score":0.34782088},"labels":[],"label_agreement":null},{"id":"W2137409623","doi":"10.1111/j.1368-423x.2007.00198.x","title":"Semiparametric efficiency bounds in dynamic non‐linear systems under elliptical symmetry","year":2007,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","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":"Université du Québec à Montréal","funders":"National Science Foundation","keywords":"Symmetry (geometry); History; Library science; Demography; Mathematics; Sociology; Computer science; Geometry","score_opus":0.0832034829491839,"score_gpt":0.37584783157107265,"score_spread":0.29264434862188876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137409623","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01434581,0.0002905144,0.9831798,0.00044572548,0.000015807691,0.000020854295,0.000057366953,0.00006983766,0.001574357],"genre_scores_gemma":[0.8775114,0.0013736662,0.113700464,0.00037315622,0.00017082937,0.00033640012,0.0004997784,0.00020007454,0.0058343075],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99214715,0.0046464265,0.00045002726,0.0008414739,0.0013359998,0.00057892426],"domain_scores_gemma":[0.8844442,0.09635118,0.008528643,0.0063535264,0.0035892748,0.00073318055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016449047,0.0011692881,0.0019509298,0.0012082263,0.00047501636,0.0028919273,0.0021292486,0.0013236998,0.0036471998],"category_scores_gemma":[0.09532247,0.0009654564,0.0013322694,0.0012487688,0.0035145765,0.0040438273,0.0046565575,0.0024210003,0.0006002371],"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":[0.00005896832,0.000055206903,0.0019044693,0.00016346459,0.00012801906,0.00017571023,0.00029754883,0.39182383,0.00096619537,0.582691,0.000814173,0.020921335],"study_design_scores_gemma":[0.000015232433,0.00003431081,0.00088323123,0.000049746806,0.000027031321,0.000058778176,0.0000530255,0.7008518,0.00092892704,0.29610217,0.0009723845,0.000023322375],"about_ca_topic_score_codex":0.0016249121,"about_ca_topic_score_gemma":0.0009824575,"teacher_disagreement_score":0.016449047,"about_ca_system_score_codex":0.0017314744,"about_ca_system_score_gemma":0.0014627422,"threshold_uncertainty_score":0.086991906},"labels":[],"label_agreement":null},{"id":"W2146753116","doi":"10.1111/j.1368-423x.2007.00209.x","title":"A model selection method for S‐estimation","year":2007,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":1,"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 British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Ben-Gurion University of the Negev","keywords":"Selection (genetic algorithm); Estimation; Library science; Model selection; Columbia university; Operations research; History; Econometrics; Statistics; Computer science; Economics; Sociology; Management; Mathematics; Media studies; Artificial intelligence","score_opus":0.3072701141490533,"score_gpt":0.5026012081409788,"score_spread":0.19533109399192544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146753116","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00045747941,0.000056317367,0.99892694,0.000090292255,0.000027344578,0.000048397716,0.000036233145,0.00013600738,0.00022098569],"genre_scores_gemma":[0.03727329,0.0002794171,0.9584943,0.00017999878,0.00014393889,0.0009116381,0.00045543906,0.00020472049,0.0020571921],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99012893,0.007820304,0.0002967723,0.0007176998,0.0009089048,0.00012743827],"domain_scores_gemma":[0.98788446,0.009511754,0.0004722718,0.00089999544,0.0011142936,0.000117271986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009723823,0.0018490895,0.0018377746,0.0025538346,0.0011894901,0.0011596682,0.0018322966,0.0018229062,0.00759551],"category_scores_gemma":[0.025342744,0.00089765404,0.0030991696,0.0026246184,0.0011756909,0.0013376736,0.0019925353,0.0032136983,0.0025813903],"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":[0.00021979501,0.00019024775,0.0033074387,0.0005538033,0.0011449383,0.00048012336,0.00036639138,0.2689849,0.0041685984,0.23178877,0.017733758,0.47106114],"study_design_scores_gemma":[0.00008991646,0.00014904769,0.00061109936,0.00007262508,0.000095014286,0.00020893126,0.00004192668,0.91185457,0.0016355667,0.07276852,0.012413845,0.0000589934],"about_ca_topic_score_codex":0.0030859315,"about_ca_topic_score_gemma":0.00389498,"teacher_disagreement_score":0.009723823,"about_ca_system_score_codex":0.0008835323,"about_ca_system_score_gemma":0.0025369073,"threshold_uncertainty_score":0.0514251},"labels":[],"label_agreement":null},{"id":"W2152700426","doi":"10.1111/j.1368-423x.2009.00300.x","title":"Smoothness adaptive average derivative estimation","year":2010,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Smoothness; Estimation; Library science; History; Art history; Media studies; Sociology; Mathematics; Computer science; Management; Economics","score_opus":0.0910335240818234,"score_gpt":0.23442860228092716,"score_spread":0.14339507819910374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152700426","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008824039,0.00033908972,0.9890282,0.00015447728,0.000037097532,0.000023894361,0.000051172094,0.00031523345,0.001226756],"genre_scores_gemma":[0.58588624,0.0010005113,0.4076318,0.00019643219,0.00018538308,0.00010544431,0.00039469943,0.0003361278,0.004263331],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985238,0.00057682325,0.0000768144,0.00030688656,0.00042106822,0.000094769486],"domain_scores_gemma":[0.9950642,0.003086549,0.00046327742,0.00080583774,0.0004930173,0.00008714916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003673132,0.00086684996,0.0014304338,0.0014370675,0.0004835699,0.0015781807,0.002074768,0.0016205589,0.0020780782],"category_scores_gemma":[0.021938369,0.0006549029,0.0011271085,0.0014441279,0.001120172,0.003093563,0.001576425,0.0021725646,0.0005306987],"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":[0.00019182927,0.00013438564,0.005787809,0.0002291827,0.00028576225,0.00015924223,0.00013149338,0.57934314,0.008568,0.19309197,0.0033725684,0.20870453],"study_design_scores_gemma":[0.000011573216,0.000025317915,0.00084701594,0.000018044442,0.000029570017,0.000050888655,0.00000750476,0.95409703,0.0016091659,0.041760437,0.0015214869,0.000021956808],"about_ca_topic_score_codex":0.0030949044,"about_ca_topic_score_gemma":0.002302473,"teacher_disagreement_score":0.003673132,"about_ca_system_score_codex":0.0008589047,"about_ca_system_score_gemma":0.0009993531,"threshold_uncertainty_score":0.01942563},"labels":[],"label_agreement":null},{"id":"W2156555479","doi":"10.1111/j.1368-423x.2007.00221.x","title":"Moments of IV and JIVE estimators","year":2007,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","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":"Queen's University; McGill University","funders":"","keywords":"Library science; Estimator; Queen (butterfly); Media studies; Sociology; Computer science; Mathematics; Statistics","score_opus":0.09638540066116245,"score_gpt":0.24299153952123576,"score_spread":0.1466061388600733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156555479","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0057888473,0.00066592084,0.9898282,0.00030887307,0.00005294324,0.000019673884,0.00008271143,0.000080974074,0.0031718388],"genre_scores_gemma":[0.60545397,0.0035205346,0.37856883,0.000638364,0.00078862853,0.00050557393,0.0007190865,0.00034098997,0.009463954],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9957931,0.0025297436,0.00019948467,0.00050021167,0.0006587218,0.00031883092],"domain_scores_gemma":[0.9697703,0.02343579,0.002488045,0.0023706884,0.0016329311,0.0003022812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075295353,0.0005922452,0.0013557031,0.0021352305,0.00042956255,0.0023854917,0.0014028597,0.0011519651,0.0046628937],"category_scores_gemma":[0.072713755,0.0006422884,0.0011176505,0.0015112753,0.0020172151,0.0029614319,0.0025324346,0.002330261,0.00067187176],"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":[0.00003476165,0.000012554551,0.0020710635,0.000120437915,0.00007313321,0.00010820093,0.00014318665,0.03707986,0.00063902116,0.93166065,0.0012735837,0.02678362],"study_design_scores_gemma":[0.00002141323,0.000052511852,0.0019112981,0.00014654515,0.000048828846,0.00022380463,0.000088960536,0.23971376,0.0016758319,0.74613196,0.009936449,0.000048628273],"about_ca_topic_score_codex":0.00076502835,"about_ca_topic_score_gemma":0.0005660253,"teacher_disagreement_score":0.0075295353,"about_ca_system_score_codex":0.000982451,"about_ca_system_score_gemma":0.00072020735,"threshold_uncertainty_score":0.039820492},"labels":[],"label_agreement":null},{"id":"W2234399507","doi":"10.1111/1368-423x.00060","title":"Asymptotic approximations in the near‐integrated model with a non‐zero initial condition","year":2001,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Advanced Mathematical Modeling in Engineering","field":"Computer Science","cited_by":2,"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":"Luonnontieteiden ja Tekniikan Tutkimuksen Toimikunta; Université de Montréal","keywords":"Zero (linguistics); Mathematics; Approximations of π; Applied mathematics","score_opus":0.039056314366672173,"score_gpt":0.26889797803192095,"score_spread":0.22984166366524877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2234399507","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04767829,0.0006885417,0.94358164,0.00047759156,0.00004728869,0.000021830345,0.000046924357,0.00023898498,0.0072189183],"genre_scores_gemma":[0.8662975,0.0013118384,0.12139459,0.00028003438,0.00013357533,0.000110605804,0.0002681537,0.00018927954,0.010014549],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99908996,0.0003419193,0.00004022062,0.00012855412,0.00029647734,0.00010291482],"domain_scores_gemma":[0.99297875,0.0052466653,0.0006112172,0.00047340337,0.0005346875,0.00015526453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032859286,0.00052087364,0.00093530695,0.000838215,0.0005361026,0.0013585084,0.0018530223,0.0010989419,0.0030067991],"category_scores_gemma":[0.022967,0.00045586136,0.0009850797,0.0007538469,0.001979958,0.003392352,0.0014138139,0.0021938873,0.0005035093],"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":[0.000038453654,0.000045314147,0.0016265914,0.00009257681,0.000038135127,0.0002433216,0.00032917218,0.4974993,0.0006948882,0.48392496,0.0009949774,0.014472386],"study_design_scores_gemma":[0.0000077322175,0.000017928738,0.0004127379,0.000024943012,0.000013204627,0.000056503177,0.00004543875,0.8886403,0.0002654257,0.10964183,0.0008579834,0.000015943504],"about_ca_topic_score_codex":0.013132192,"about_ca_topic_score_gemma":0.0075248866,"teacher_disagreement_score":0.013132192,"about_ca_system_score_codex":0.0014895571,"about_ca_system_score_gemma":0.0015024358,"threshold_uncertainty_score":0.026111484},"labels":[],"label_agreement":null},{"id":"W2604738972","doi":"10.1111/ectj.12092","title":"Oracle and adaptive false discovery rate controlling methods for one‐sided testing: theory and application in treatment effect evaluation","year":2017,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":9,"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 Toronto","funders":"Connaught Fund; Simon Fraser University; Deutsche Forschungsgemeinschaft; Royal Economic Society; Royal Society","keywords":"False discovery rate; Oracle; Multiple comparisons problem; Computer science; Monte Carlo method; Parametric statistics; Econometrics; Sample size determination; Deconvolution; Statistics; Machine learning; Mathematics; Algorithm","score_opus":0.4302061907665916,"score_gpt":0.515759728347448,"score_spread":0.08555353758085638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604738972","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002349484,0.0005191186,0.9955153,0.00040875713,0.00008563057,0.00027792685,0.00008154703,0.00034322363,0.00041898264],"genre_scores_gemma":[0.18513528,0.0008116081,0.8082548,0.000878095,0.00031923584,0.0030708534,0.00035528254,0.0002584427,0.0009163897],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.75883496,0.21504438,0.005316792,0.00972936,0.009879038,0.0011954445],"domain_scores_gemma":[0.30756906,0.6446021,0.014854615,0.025473762,0.006159641,0.0013408817],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.21163285,0.0027841944,0.005029359,0.0057435036,0.0015493061,0.0041468954,0.0077280276,0.006908888,0.0046972283],"category_scores_gemma":[0.5058984,0.001469981,0.0038530603,0.0052470537,0.010999022,0.005605521,0.004355255,0.009046352,0.0008045538],"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":[0.0027640627,0.0005097349,0.0225286,0.0024108423,0.0038402528,0.0014741472,0.0015683058,0.107367195,0.0032874607,0.47914845,0.005562792,0.3695382],"study_design_scores_gemma":[0.0007577276,0.0009013556,0.0047846376,0.0004927791,0.00056258996,0.0008827281,0.00018284403,0.51558244,0.003919928,0.4658364,0.0058798,0.00021679436],"about_ca_topic_score_codex":0.0021129046,"about_ca_topic_score_gemma":0.0012141869,"teacher_disagreement_score":0.21163285,"about_ca_system_score_codex":0.0024325901,"about_ca_system_score_gemma":0.0045946813,"threshold_uncertainty_score":0.97219706},"labels":[],"label_agreement":null},{"id":"W2604913116","doi":"10.1093/ectj/utz006","title":"A simple, graphical approach to comparing multiple treatments","year":2019,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University","funders":"","keywords":"Spurious relationship; Graphical model; Resampling; Computer science; Simple (philosophy); Multiple comparisons problem; Jackknife resampling; Algorithm; Zero (linguistics); Mathematics; Statistics; Artificial intelligence; Machine learning","score_opus":0.6608640137915875,"score_gpt":0.5200311668773503,"score_spread":0.14083284691423725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604913116","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023837618,0.00080449495,0.9869283,0.002237393,0.0003887365,0.0007721436,0.0007738495,0.0006949422,0.0050164694],"genre_scores_gemma":[0.096354134,0.00084538345,0.8945135,0.0021226483,0.00032410864,0.0031480188,0.00040086667,0.00028610835,0.0020052847],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.8935343,0.0941533,0.0021170839,0.0026782132,0.006882489,0.0006346849],"domain_scores_gemma":[0.8816422,0.09929547,0.0058035394,0.00757658,0.0048617907,0.00082038884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.042709175,0.0015279701,0.0024505788,0.0044926866,0.00081949815,0.0031430123,0.0035239928,0.0025714391,0.02560348],"category_scores_gemma":[0.16006726,0.0006880511,0.003747492,0.0026477643,0.0028349457,0.002658187,0.0024893237,0.0050300863,0.002585413],"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":[0.0011532082,0.00031236897,0.0023569437,0.0025140601,0.0017878417,0.00048133513,0.0005710028,0.061088867,0.002315483,0.61111337,0.022279302,0.29402623],"study_design_scores_gemma":[0.0007293704,0.0010032326,0.0021892905,0.00070196803,0.0008333235,0.00041863014,0.00013366387,0.08550612,0.0012705205,0.86791307,0.03913113,0.00016968424],"about_ca_topic_score_codex":0.0020642586,"about_ca_topic_score_gemma":0.0024528494,"teacher_disagreement_score":0.042709175,"about_ca_system_score_codex":0.002439444,"about_ca_system_score_gemma":0.002892227,"threshold_uncertainty_score":0.22587037},"labels":[],"label_agreement":null},{"id":"W2995378146","doi":"10.1093/ectj/utz025","title":"Partial identification in nonseparable count data instrumental variable models","year":2019,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Instrumental variable; Identification (biology); Inference; Outcome (game theory); Moment (physics); Count data; Variable (mathematics); Set (abstract data type); Econometrics; Computer science; Data set; Estimation; Mathematics; Mathematical optimization; Statistics; Artificial intelligence; Economics; Poisson distribution; Mathematical economics","score_opus":0.1913697430092952,"score_gpt":0.3752746082601343,"score_spread":0.1839048652508391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995378146","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015848402,0.0002071483,0.9823255,0.00032622117,0.000016749218,0.000039707473,0.0001466512,0.00008724876,0.0010023856],"genre_scores_gemma":[0.7138823,0.00076554314,0.27758303,0.0003348824,0.000110097884,0.0007394969,0.00074274745,0.0000969834,0.0057448163],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9913209,0.005768724,0.00038920672,0.0010370179,0.0010592588,0.000424912],"domain_scores_gemma":[0.9157896,0.07425034,0.003933842,0.0042183623,0.0014306837,0.00037719996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015070653,0.0007292604,0.0021251582,0.0015592396,0.0005910472,0.0021229016,0.0026503408,0.0015328878,0.0039149686],"category_scores_gemma":[0.06585144,0.00092379306,0.0016761674,0.001664352,0.0025858127,0.0028931636,0.0035955955,0.0030230857,0.00045131618],"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":[0.00009430707,0.000055781864,0.004140949,0.00023941368,0.00018235098,0.0002469008,0.00035366285,0.277947,0.00048659305,0.6787608,0.0010135282,0.03647885],"study_design_scores_gemma":[0.000019385681,0.000030122876,0.0006687094,0.000043567816,0.000023483492,0.00003081776,0.00005278261,0.60502243,0.0003204141,0.39262378,0.001145733,0.000018801455],"about_ca_topic_score_codex":0.0025379306,"about_ca_topic_score_gemma":0.0020399245,"teacher_disagreement_score":0.015070653,"about_ca_system_score_codex":0.0010183404,"about_ca_system_score_gemma":0.0015211847,"threshold_uncertainty_score":0.07970214},"labels":[],"label_agreement":null},{"id":"W3011754248","doi":"10.1093/ectj/utaa005","title":"Artificial intelligence as structural estimation: Deep Blue, Bonanza, and AlphaGo","year":2020,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":30,"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":"Osaka University; Johns Hopkins University; Georgetown University; University of Toronto; Københavns Universitet; Harvard University","keywords":"Artificial intelligence; Computer science; Reinforcement learning; Artificial neural network; Value network; Structural estimation; Value (mathematics); Rust (programming language); Deep blue; Function (biology); Deep learning; Estimation; Machine learning; Miller; Econometrics; Mathematics; Economics; Management","score_opus":0.07141641563130557,"score_gpt":0.24336365443490818,"score_spread":0.1719472388036026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011754248","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06810117,0.0121945115,0.8258392,0.04186666,0.000492071,0.000045321653,0.00021377167,0.0005854074,0.05066191],"genre_scores_gemma":[0.84889317,0.0050526345,0.1282156,0.0022190595,0.00043496094,0.00007855425,0.0001213122,0.00015678527,0.014827904],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989753,0.00064575457,0.000024135621,0.00011113911,0.00018716711,0.000056412497],"domain_scores_gemma":[0.9936422,0.0050640767,0.00022391962,0.00048172972,0.0004102878,0.0001777352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036246204,0.00059086614,0.000676941,0.0010212999,0.0005238234,0.0018467966,0.0009831678,0.0010614708,0.0034042639],"category_scores_gemma":[0.018054118,0.00038548346,0.00045230382,0.0011273334,0.0036252749,0.0035972206,0.001977743,0.0030822763,0.0002962476],"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":[0.00005098479,0.000025546458,0.0015200886,0.000061593535,0.00004758899,0.00003154428,0.00011015623,0.089278616,0.00014980005,0.84578705,0.0030741254,0.05986293],"study_design_scores_gemma":[0.000011339396,0.000013704988,0.00044934123,0.000056319797,0.0000087043045,0.000013341579,0.000029306708,0.2801786,0.00014789621,0.71506083,0.004020111,0.000010416734],"about_ca_topic_score_codex":0.010035499,"about_ca_topic_score_gemma":0.010334456,"teacher_disagreement_score":0.010035499,"about_ca_system_score_codex":0.0019083814,"about_ca_system_score_gemma":0.0013663294,"threshold_uncertainty_score":0.019954145},"labels":[],"label_agreement":null},{"id":"W3046014911","doi":"10.1093/ectj/utab025","title":"Partially linear models with endogeneity: a conditional moment-based approach","year":2021,"lang":"en","type":"preprint","venue":"Econometrics Journal","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Estimator; Endogeneity; Mathematics; Moment (physics); Econometrics; Minimum-variance unbiased estimator; Conditional expectation; Statistics; Independence (probability theory); Linear model; Generalized method of moments","score_opus":0.1199435414247341,"score_gpt":0.2359223272707022,"score_spread":0.1159787858459681,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046014911","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014213902,0.00041775365,0.98171014,0.0010003375,0.000044423083,0.00003212207,0.00044556905,0.0002415795,0.0018942057],"genre_scores_gemma":[0.7768029,0.0015015013,0.20645127,0.0006842677,0.0004111799,0.00028007667,0.0014950527,0.000271622,0.012102188],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99686146,0.0020131476,0.000109809414,0.0003969313,0.00037398364,0.00024471257],"domain_scores_gemma":[0.9812641,0.014473223,0.0018195788,0.0013154106,0.0008788057,0.00024888976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005353862,0.00080358767,0.0016284178,0.001411467,0.0004212405,0.0019155764,0.0020832305,0.0013557851,0.006539668],"category_scores_gemma":[0.020097401,0.000978056,0.002116528,0.0016643426,0.0016569811,0.0021294034,0.0021054917,0.0027116667,0.0007105109],"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":[0.00008603488,0.000052019917,0.004482215,0.00017038108,0.00030229887,0.0002826423,0.00016732162,0.4995242,0.0005809651,0.46203458,0.0032787456,0.02903857],"study_design_scores_gemma":[0.000018179922,0.000031729334,0.001089711,0.000042276923,0.00005642837,0.000056404744,0.000027891101,0.80765504,0.00025882546,0.18811718,0.0026090348,0.000037393886],"about_ca_topic_score_codex":0.008253363,"about_ca_topic_score_gemma":0.007366987,"teacher_disagreement_score":0.008253363,"about_ca_system_score_codex":0.0012498891,"about_ca_system_score_gemma":0.0017540358,"threshold_uncertainty_score":0.028314292},"labels":[],"label_agreement":null},{"id":"W3084047481","doi":"10.1093/ectj/utab013","title":"Exact Computation of Maximum Rank Correlation Estimator","year":2021,"lang":"en","type":"preprint","venue":"Econometrics Journal","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Estimator; Solver; Rank (graph theory); Computation; Mathematics; Mathematical optimization; Monte Carlo method; Binary number; Applied mathematics; Algorithm; Statistics; Combinatorics","score_opus":0.18425907349322987,"score_gpt":0.419174956068803,"score_spread":0.23491588257557314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084047481","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058885333,0.00042152195,0.99050504,0.00024318675,0.0000805075,0.000028461647,0.00015279156,0.00045499977,0.0022249876],"genre_scores_gemma":[0.28502074,0.0008370007,0.70206517,0.00034610543,0.0004192048,0.00027585827,0.0009817227,0.00082125684,0.009233022],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9946808,0.0029312775,0.00024838207,0.0006396603,0.00117311,0.00032679204],"domain_scores_gemma":[0.97193897,0.020386448,0.0011791787,0.0037316168,0.0022719437,0.0004918182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005859544,0.0012170307,0.0019720222,0.002144649,0.0007825952,0.0026126415,0.0022826577,0.0017388626,0.011190049],"category_scores_gemma":[0.056797996,0.0009816422,0.0010216954,0.0022621825,0.0017526187,0.0048239585,0.0034265008,0.0024498363,0.0033329686],"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":[0.0005310754,0.00019001997,0.0030400036,0.0007857593,0.0002402977,0.00059179787,0.00029719563,0.22081177,0.0063766167,0.53343254,0.0172735,0.21642944],"study_design_scores_gemma":[0.000047631773,0.000054872533,0.0007305437,0.00006917466,0.00003759437,0.00027018174,0.00004873957,0.72658545,0.003290519,0.26518953,0.0036299534,0.000045691017],"about_ca_topic_score_codex":0.0014604338,"about_ca_topic_score_gemma":0.0027962255,"teacher_disagreement_score":0.011190049,"about_ca_system_score_codex":0.0010340686,"about_ca_system_score_gemma":0.0027944378,"threshold_uncertainty_score":0.03743446},"labels":[],"label_agreement":null},{"id":"W3103432885","doi":"10.1093/ectj/utaa033","title":"Complete subset averaging with many instruments","year":2020,"lang":"en","type":"preprint","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Estimator; Mathematics; Mean squared error; Function (biology); Statistics; Sample size determination; Set (abstract data type); Class (philosophy); Applied mathematics; Econometrics; Mathematical optimization; Computer science","score_opus":0.1865947988405596,"score_gpt":0.23661312525341083,"score_spread":0.05001832641285123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3103432885","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03460955,0.00043428835,0.96168554,0.00027206063,0.000065545224,0.00005926761,0.00030787315,0.0002584036,0.0023074087],"genre_scores_gemma":[0.6331697,0.0005688305,0.35739997,0.00034366857,0.000370754,0.00025929173,0.0020685247,0.00014604465,0.0056731743],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99339855,0.003781181,0.00028564685,0.0012417883,0.0010654392,0.0002274445],"domain_scores_gemma":[0.9896114,0.0052201143,0.00079990504,0.0025998382,0.0016277736,0.00014091205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006840985,0.0010107278,0.0023935828,0.001034588,0.00060266996,0.0018331019,0.0014541529,0.00087873876,0.003166394],"category_scores_gemma":[0.02172741,0.0006705297,0.0015407732,0.0015378,0.00097536395,0.0022115642,0.0015426053,0.0012221308,0.0008413205],"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":[0.0004013097,0.00015453986,0.023479007,0.00037659524,0.0014362184,0.00035537186,0.00043369315,0.49748003,0.004153672,0.102450706,0.0073347483,0.36194408],"study_design_scores_gemma":[0.000056743927,0.00021044981,0.0069404882,0.0000636938,0.00018849818,0.00008459942,0.0000922301,0.88788575,0.0026457943,0.09468615,0.0070801643,0.00006543574],"about_ca_topic_score_codex":0.0025679693,"about_ca_topic_score_gemma":0.0029721924,"teacher_disagreement_score":0.006840985,"about_ca_system_score_codex":0.00048134584,"about_ca_system_score_gemma":0.001133968,"threshold_uncertainty_score":0.036179066},"labels":[],"label_agreement":null},{"id":"W3119443671","doi":"10.1111/j.1368-423x.2007.00213.x","title":"Bayesian inference for the mixed conditional heteroskedasticity model","year":2007,"lang":"en","type":"preprint","venue":"Econometrics Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; HEC Montréal","funders":"","keywords":"Gibbs sampling; Inference; Heteroscedasticity; Bayesian inference; Econometrics; Bayesian probability; Mathematics; Marginal likelihood; Statistics; Computer science; Artificial intelligence","score_opus":0.12188184701513576,"score_gpt":0.28298858849842234,"score_spread":0.16110674148328658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119443671","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017212586,0.0005937053,0.9788851,0.0007800381,0.000050492195,0.000036177218,0.0005021062,0.0003490004,0.0015907633],"genre_scores_gemma":[0.7000721,0.001459753,0.28627136,0.0005617329,0.0004315658,0.00039646612,0.00225537,0.0004908466,0.008060789],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9948186,0.0033510346,0.0001794826,0.0007654985,0.0006193771,0.00026598055],"domain_scores_gemma":[0.97723436,0.019258106,0.0011071154,0.0011865093,0.0009451254,0.0002687167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010520312,0.0009244684,0.0023947775,0.0017600424,0.0008193623,0.0024557763,0.002636058,0.0016943072,0.0073388135],"category_scores_gemma":[0.043083526,0.0012527549,0.0017063348,0.0019331982,0.0019471537,0.0032595154,0.0017450667,0.003514438,0.0012206214],"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":[0.00017165342,0.00009315917,0.0047797244,0.00020144769,0.00038495797,0.00018051421,0.00015637049,0.4858072,0.00066866935,0.46121088,0.0055239666,0.040821463],"study_design_scores_gemma":[0.000030975658,0.000011739365,0.0007290998,0.000033635242,0.00003266201,0.00003345577,0.000013816862,0.7353357,0.00020839962,0.26263645,0.0009095276,0.000024595822],"about_ca_topic_score_codex":0.010671156,"about_ca_topic_score_gemma":0.010996113,"teacher_disagreement_score":0.010671156,"about_ca_system_score_codex":0.0018402622,"about_ca_system_score_gemma":0.001979099,"threshold_uncertainty_score":0.05563736},"labels":[],"label_agreement":null},{"id":"W3121497619","doi":"10.1111/j.1368-423x.2005.00168.x","title":"Partially adaptive estimation via the maximum entropy densities","year":2005,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Water resources management and optimization","field":"Engineering","cited_by":23,"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":"Social Sciences and Humanities Research Council of Canada","keywords":"Library science; Computer science","score_opus":0.01644707081883471,"score_gpt":0.18469461237738471,"score_spread":0.16824754155855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121497619","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0071258075,0.00013277601,0.99190056,0.00010085818,0.000010306142,0.00001600907,0.000024011957,0.00008160332,0.00060808397],"genre_scores_gemma":[0.62814933,0.0006019907,0.3672298,0.00020027852,0.00012801649,0.00025159944,0.00028715917,0.00011117399,0.0030406513],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979025,0.0011395973,0.000085219355,0.00026111313,0.0005131466,0.00009838583],"domain_scores_gemma":[0.99061793,0.007080983,0.0007118103,0.0007604146,0.0007089568,0.000119902026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037933635,0.0007289547,0.0009844543,0.0011227946,0.0003552938,0.0012422049,0.001353673,0.0010101738,0.0017262684],"category_scores_gemma":[0.022544201,0.0006196482,0.0007524631,0.0008270946,0.0013953669,0.00302831,0.0018176689,0.0011186028,0.00034014],"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":[0.00011500135,0.00004966196,0.0025866285,0.00016174525,0.000117062824,0.00011506486,0.00015703897,0.7440315,0.0024426673,0.1420791,0.0011505592,0.10699402],"study_design_scores_gemma":[0.000008675177,0.00002373563,0.0004462578,0.000013832215,0.000007856085,0.000024206176,0.0000073370693,0.9610431,0.0006221352,0.037272327,0.0005138294,0.000016609458],"about_ca_topic_score_codex":0.0013285809,"about_ca_topic_score_gemma":0.00089085504,"teacher_disagreement_score":0.0037933635,"about_ca_system_score_codex":0.0006364802,"about_ca_system_score_gemma":0.0007963049,"threshold_uncertainty_score":0.020061433},"labels":[],"label_agreement":null},{"id":"W3121674998","doi":"10.1111/ectj.12096","title":"My friend far, far away: a random field approach to exponential random graph models","year":2017,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":38,"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 Toronto; Université Laval","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; University of North Carolina at Chapel Hill; Social Sciences and Humanities Research Council of Canada; Fonds de Recherche du Québec-Société et Culture; University of Cambridge","keywords":"Exponential random graph models; Homophily; Estimator; Random graph; Computer science; Exponential function; Graph; Set (abstract data type); Theoretical computer science; Mathematics; Mathematical optimization; Applied mathematics; Econometrics; Statistics; Combinatorics","score_opus":0.04219228558657924,"score_gpt":0.2716649188249091,"score_spread":0.2294726332383299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121674998","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0286599,0.0006556029,0.9631884,0.002308321,0.00007955983,0.00006549189,0.0002723865,0.00019715636,0.0045732204],"genre_scores_gemma":[0.76201576,0.002477248,0.2167477,0.0011108911,0.000662188,0.0005169477,0.0007362856,0.0003233599,0.015409576],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979075,0.0014492517,0.000044303073,0.00027610763,0.00020855435,0.0001143502],"domain_scores_gemma":[0.97965896,0.016765855,0.0013151991,0.0009894458,0.0007171525,0.00055333355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006843914,0.0006804505,0.0011294666,0.0026180174,0.0008031716,0.0018323384,0.0026632966,0.0019344552,0.006221301],"category_scores_gemma":[0.029765353,0.00058503397,0.0011997735,0.0020382302,0.0019684806,0.004501118,0.0020663843,0.0026965316,0.00091823784],"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":[0.000038414604,0.00007879196,0.0020077403,0.000053103282,0.000055693545,0.00021793076,0.0002864497,0.18053532,0.00027279055,0.79873866,0.0034423186,0.014272881],"study_design_scores_gemma":[0.000017542001,0.000017463033,0.00031847678,0.000021470043,0.000013254322,0.000072153234,0.00005163114,0.6615499,0.00005618957,0.33608213,0.0017797699,0.000019895897],"about_ca_topic_score_codex":0.005065429,"about_ca_topic_score_gemma":0.004582772,"teacher_disagreement_score":0.006843914,"about_ca_system_score_codex":0.0014120599,"about_ca_system_score_gemma":0.0007788994,"threshold_uncertainty_score":0.036194503},"labels":[],"label_agreement":null},{"id":"W3125187092","doi":"10.1093/ectj/utab003","title":"On unit free assessment of the extent of multilateral distributional variation","year":2021,"lang":"en","type":"preprint","venue":"Econometrics Journal","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Seoul National University","keywords":"Categorical variable; Univariate; Econometrics; Inequality; Multivariate statistics; Divergence (linguistics); Cohesion (chemistry); Convergence (economics); Unit (ring theory); Scale (ratio); Statistics; Computer science; Geography; Mathematics; Economics; Cartography; Economic growth; Mathematics education","score_opus":0.08320428634523656,"score_gpt":0.3557782414356264,"score_spread":0.27257395509038984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125187092","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21752906,0.001173693,0.7579082,0.0010648004,0.00013090782,0.00012374355,0.0009525768,0.00028530083,0.020831732],"genre_scores_gemma":[0.94066334,0.0002799934,0.05624438,0.00015302098,0.00012330964,0.00016725212,0.00059930794,0.00012958195,0.001639712],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9868699,0.007921944,0.00052214216,0.0020539856,0.002180348,0.0004517596],"domain_scores_gemma":[0.9285395,0.05640035,0.0044283816,0.0066218046,0.0029507976,0.0010591613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0213644,0.00062205293,0.0012599912,0.0064246044,0.0007712238,0.0038430698,0.0015510663,0.0009921452,0.006860096],"category_scores_gemma":[0.07285694,0.00026683277,0.0010533249,0.004914545,0.005479859,0.0055308067,0.0055961977,0.00238941,0.00046152595],"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":[0.00027183173,0.00007017174,0.034719717,0.00033946903,0.00032975627,0.0003209853,0.0014667545,0.06923007,0.001677417,0.7798762,0.002669125,0.109028466],"study_design_scores_gemma":[0.000011272848,0.0000959863,0.021019613,0.0001777614,0.000032142125,0.00019643117,0.0007664952,0.17177883,0.0008295732,0.8014476,0.0035736475,0.000070742055],"about_ca_topic_score_codex":0.0013662903,"about_ca_topic_score_gemma":0.0008305039,"teacher_disagreement_score":0.0213644,"about_ca_system_score_codex":0.0013436108,"about_ca_system_score_gemma":0.0005231138,"threshold_uncertainty_score":0.1129871},"labels":[],"label_agreement":null},{"id":"W3126063643","doi":"10.1093/ectj/utaa013","title":"Two-way exclusion restrictions in models with heterogeneous treatment effects","year":2020,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":7,"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 Toronto","funders":"Social Sciences and Humanities Research Council of Canada; National Natural Science Foundation of China","keywords":"Outcome (game theory); Estimator; Latent variable; Instrumental variable; Econometrics; Structural equation modeling; Mathematics; Treatment effect; Monotone polygon; Variable (mathematics); Selection (genetic algorithm); Contrast (vision); Statistics; Applied mathematics; Computer science; Medicine; Mathematical economics; Artificial intelligence; Mathematical analysis","score_opus":0.2922863835589675,"score_gpt":0.3783037642443129,"score_spread":0.08601738068534537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126063643","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030391717,0.00020407395,0.966459,0.0006674597,0.00004969782,0.00014506826,0.0002654214,0.00018706602,0.0016303799],"genre_scores_gemma":[0.7721192,0.00041256455,0.214275,0.0006830117,0.00028190843,0.0013603352,0.0010824923,0.00015331378,0.009632138],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9804673,0.014512341,0.0006859562,0.0021734603,0.0013169686,0.00084392074],"domain_scores_gemma":[0.9096304,0.07535094,0.0062695597,0.0063071074,0.0017516894,0.0006902287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027745567,0.0007105058,0.0029402045,0.0016514702,0.0010685042,0.0022583555,0.0027720397,0.0019767513,0.0071539977],"category_scores_gemma":[0.073158026,0.0007931303,0.0026413314,0.001851411,0.0032772787,0.002956269,0.0033678128,0.0040793796,0.0005806933],"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":[0.00039403982,0.0002674927,0.02227079,0.00028173366,0.0008832165,0.0008853302,0.00093153474,0.15091051,0.0007583385,0.74374723,0.0029393167,0.07573054],"study_design_scores_gemma":[0.00018074135,0.00012436324,0.0066588437,0.00010646578,0.00017895552,0.00016990807,0.00019633943,0.48219863,0.0009814544,0.5025377,0.006593394,0.00007322067],"about_ca_topic_score_codex":0.0042484943,"about_ca_topic_score_gemma":0.003015183,"teacher_disagreement_score":0.027745567,"about_ca_system_score_codex":0.0012892154,"about_ca_system_score_gemma":0.0024000532,"threshold_uncertainty_score":0.1467343},"labels":[],"label_agreement":null},{"id":"W3179570277","doi":"10.1093/ectj/utab020","title":"Testing overidentifying restrictions with many instruments and heteroscedasticity using regularised jackknife IV","year":2021,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Center for Interuniversity Research and Analysis on Organizations; Université de Montréal","funders":"Social Sciences and Humanities Research Council of Canada; Universitat Pompeu Fabra","keywords":"Jackknife resampling; Heteroscedasticity; Econometrics; Mathematics; Sample size determination; Test statistic; Statistic; Statistics; Computer science; Statistical hypothesis testing; Estimator","score_opus":0.11870442724841816,"score_gpt":0.2527333168787972,"score_spread":0.134028889630379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179570277","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34187824,0.00018986272,0.6548141,0.00036383708,0.00006027271,0.000110937595,0.00014978195,0.00036027038,0.0020726344],"genre_scores_gemma":[0.93853855,0.00006538446,0.06036113,0.0001137049,0.00004512898,0.000080919024,0.00020028702,0.00004410207,0.0005508284],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.96546304,0.024360823,0.0017325568,0.0041333092,0.0032209363,0.001089291],"domain_scores_gemma":[0.80404013,0.15996133,0.015518165,0.014455802,0.0045219124,0.0015027218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.030407423,0.00075133465,0.001965087,0.0017428037,0.00066619355,0.0019378518,0.0020846117,0.0012034521,0.00284051],"category_scores_gemma":[0.12985599,0.0007148189,0.001641722,0.0013361851,0.0024170175,0.0022632084,0.0021655848,0.0021092,0.000381311],"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":[0.0027342571,0.00082458346,0.28654417,0.00070570287,0.0046762927,0.0029867098,0.0021385744,0.3094724,0.009865997,0.11058892,0.0031977037,0.2662647],"study_design_scores_gemma":[0.00026464503,0.0014554444,0.05475655,0.00017769595,0.0003992604,0.0006440606,0.00095863396,0.81960636,0.0070944065,0.11151518,0.002914999,0.00021286009],"about_ca_topic_score_codex":0.0026791173,"about_ca_topic_score_gemma":0.0019498819,"teacher_disagreement_score":0.030407423,"about_ca_system_score_codex":0.00047642255,"about_ca_system_score_gemma":0.0017541946,"threshold_uncertainty_score":0.16081178},"labels":[],"label_agreement":null},{"id":"W3188629815","doi":"10.1093/ectj/utab028","title":"Detecting common breaks in the means of high dimensional cross-dependent panels","year":2021,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"CUSUM; Statistic; Monte Carlo method; Mathematics; Series (stratigraphy); Test statistic; Applied mathematics; Statistics; Panel data; Asymptotic distribution; Statistical hypothesis testing; Estimator","score_opus":0.1013008164762433,"score_gpt":0.2606019260068582,"score_spread":0.15930110953061494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188629815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6177077,0.0002887553,0.37969145,0.00037764298,0.000039988226,0.000036540245,0.00042023286,0.0002214781,0.0012162295],"genre_scores_gemma":[0.98395616,0.000041879786,0.015501281,0.000035844438,0.000021346817,0.000023532793,0.00024389446,0.000011353157,0.00016472315],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99270815,0.005192972,0.00029495548,0.0009368554,0.00057343993,0.00029370864],"domain_scores_gemma":[0.92514175,0.06057319,0.0056775007,0.0058709364,0.0021252502,0.00061148737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01384626,0.00031772532,0.0009943126,0.001915445,0.00060220604,0.0013325238,0.0009269212,0.00093786896,0.001120348],"category_scores_gemma":[0.057066634,0.00034038848,0.0008122753,0.0015768064,0.0017283552,0.0011284862,0.0014400615,0.0016404259,0.00013478003],"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":[0.0008719583,0.00021766135,0.4161266,0.00019739654,0.001714799,0.0012999868,0.0008731733,0.33016494,0.0076993126,0.08509277,0.0024825523,0.15325885],"study_design_scores_gemma":[0.000024290062,0.0001430831,0.10988191,0.000048242015,0.00008883852,0.00017532532,0.00030304,0.8070055,0.0031918094,0.077863775,0.0012005089,0.00007366081],"about_ca_topic_score_codex":0.0023961721,"about_ca_topic_score_gemma":0.0023423154,"teacher_disagreement_score":0.01384626,"about_ca_system_score_codex":0.0006577934,"about_ca_system_score_gemma":0.0005480411,"threshold_uncertainty_score":0.07322693},"labels":[],"label_agreement":null},{"id":"W4220729324","doi":"10.1093/ectj/utac008","title":"Estimation and inference on treatment effects under treatment-based sampling designs","year":2022,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":3,"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 British Columbia","funders":"Japan Society for the Promotion of Science; Social Sciences and Humanities Research Council of Canada","keywords":"Estimator; Population; Inference; Sampling (signal processing); Benchmark (surveying); Sampling design; Computer science; Sample size determination; Statistics; Econometrics; Causal inference; Statistical inference; Sample (material); Mathematics; Artificial intelligence","score_opus":0.5126904252324965,"score_gpt":0.45664355852416116,"score_spread":0.05604686670833536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220729324","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014106682,0.00017931128,0.98380417,0.0002821729,0.000027570199,0.00033217669,0.00010162062,0.00008621675,0.0010801425],"genre_scores_gemma":[0.48306686,0.00054145546,0.51216316,0.0003374939,0.00009555972,0.002286313,0.00037218767,0.000043825596,0.0010932102],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.8598069,0.12529577,0.0028462408,0.004524451,0.0065203193,0.0010062864],"domain_scores_gemma":[0.77541703,0.1977358,0.0089126015,0.013903746,0.003509714,0.00052111055],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.10832088,0.0009392702,0.002455865,0.0026865466,0.0007415801,0.0022453396,0.0025248022,0.0030162712,0.0033751559],"category_scores_gemma":[0.3213261,0.0009013055,0.0021681273,0.0022699644,0.0036097858,0.0024995867,0.0024174063,0.0028793693,0.0003248757],"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":[0.00064955244,0.00030005697,0.013216583,0.0007294942,0.0009408141,0.00020118992,0.0008301891,0.21077165,0.0009071113,0.6332257,0.0012665502,0.13696116],"study_design_scores_gemma":[0.00034916194,0.0005115481,0.004951176,0.0003359943,0.00031192743,0.000102661455,0.00014183095,0.4929304,0.00198253,0.4957378,0.0025901985,0.000054901422],"about_ca_topic_score_codex":0.002144814,"about_ca_topic_score_gemma":0.0011878631,"teacher_disagreement_score":0.8916791,"about_ca_system_score_codex":0.001928742,"about_ca_system_score_gemma":0.0025278088,"threshold_uncertainty_score":0.5728624},"labels":[],"label_agreement":null},{"id":"W4306321605","doi":"10.1093/ectj/utac025","title":"Dynamic demand for differentiated products with fixed-effects unobserved heterogeneity","year":2022,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Econometrics; Statistic; Identification (biology); Economics; Discrete choice; Product (mathematics); Panel data; Computer science; Statistics; Mathematics","score_opus":0.034042119782097584,"score_gpt":0.23231714640408532,"score_spread":0.19827502662198773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306321605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7905811,0.00023527145,0.19947428,0.0012067948,0.00003078917,0.00006503116,0.0032080668,0.00014744271,0.0050511216],"genre_scores_gemma":[0.98949206,0.00013036479,0.005331386,0.00005908148,0.000019442115,0.000037479873,0.0014905366,0.000011680637,0.0034279316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988668,0.000444459,0.000052875705,0.0003189087,0.00013455313,0.00018246997],"domain_scores_gemma":[0.99120015,0.0064182333,0.0013427347,0.00060701306,0.00026743367,0.00016448666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020316327,0.00033037062,0.0009788438,0.00063792954,0.00028266318,0.0017098669,0.0012901772,0.00109526,0.0048805815],"category_scores_gemma":[0.007564888,0.000705384,0.0010894373,0.0011890235,0.0007485578,0.0014796455,0.000684733,0.0014800944,0.000491177],"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":[0.00032961075,0.0002871421,0.081053734,0.0001538535,0.00037926022,0.00066129846,0.0002459609,0.8031679,0.0015528019,0.09283591,0.0026558759,0.016676726],"study_design_scores_gemma":[0.000033541895,0.00005282682,0.014710366,0.000018695104,0.00004368589,0.000060869315,0.00010981238,0.957116,0.00039433147,0.026452417,0.00097130967,0.0000360426],"about_ca_topic_score_codex":0.016861679,"about_ca_topic_score_gemma":0.012195391,"teacher_disagreement_score":0.016861679,"about_ca_system_score_codex":0.0016620727,"about_ca_system_score_gemma":0.0006858576,"threshold_uncertainty_score":0.033527076},"labels":[],"label_agreement":null},{"id":"W4309670936","doi":"10.1093/ectj/utac028","title":"Semi-parametric inference on Gini indices of two semi-continuous populations under density ratio models","year":2022,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Estimator; Mathematics; Inference; Parametric statistics; Statistics; Econometrics; Confidence interval; Gini coefficient; Statistical inference; Index (typography); Empirical likelihood; Limit (mathematics); Parametric model; Measure (data warehouse); Applied mathematics; Inequality; Economic inequality; Computer science; Mathematical analysis","score_opus":0.13492845561876685,"score_gpt":0.2785317614723514,"score_spread":0.14360330585358458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309670936","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11336034,0.00024354558,0.88398385,0.0004070329,0.000022750823,0.00005570432,0.00016125498,0.00015978051,0.0016056696],"genre_scores_gemma":[0.89992434,0.0002332877,0.09795187,0.0001261557,0.000058173002,0.00014909594,0.00040006702,0.000063002786,0.001093921],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99219316,0.005656438,0.00019840064,0.0010145929,0.0006624345,0.00027499243],"domain_scores_gemma":[0.92399776,0.066628985,0.0034716923,0.003510717,0.0018657167,0.0005251717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021958278,0.0005918536,0.0013586669,0.0018048974,0.0005481711,0.0021881254,0.0023764975,0.001315998,0.0025588595],"category_scores_gemma":[0.097205766,0.0004970959,0.0013469766,0.001364069,0.0033660063,0.0037236754,0.0024622327,0.002649849,0.0003313693],"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":[0.00030788727,0.00014474636,0.028012672,0.00016253223,0.0002694165,0.00046026433,0.00088983664,0.49299595,0.0012123893,0.41228274,0.0016784949,0.061583083],"study_design_scores_gemma":[0.000012535799,0.000024883193,0.0024888737,0.000023409195,0.000016479853,0.000065832144,0.000076574834,0.88306814,0.00031892175,0.113545075,0.00033811608,0.000021160025],"about_ca_topic_score_codex":0.0029366491,"about_ca_topic_score_gemma":0.001622828,"teacher_disagreement_score":0.021958278,"about_ca_system_score_codex":0.0013340139,"about_ca_system_score_gemma":0.00079125137,"threshold_uncertainty_score":0.11612785},"labels":[],"label_agreement":null},{"id":"W4385068040","doi":"10.1093/ectj/utad014","title":"Augmented two-step estimating equations with nuisance functionals and complex survey data","year":2023,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"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 Waterloo","funders":"Canadian Statistical Sciences Institute; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Empirical likelihood; Estimator; Nonparametric statistics; Mathematics; Quantile; Inference; Estimating equations; Nuisance parameter; Econometrics; Orthogonality; Applied mathematics; Mathematical optimization; Statistics; Computer science","score_opus":0.6556461221784378,"score_gpt":0.46952079325114093,"score_spread":0.18612532892729683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385068040","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021937441,0.0003392229,0.97651505,0.00027498556,0.000031164946,0.000114843744,0.00026479294,0.00010434905,0.00041810513],"genre_scores_gemma":[0.3699948,0.0010714924,0.622501,0.00029087267,0.00011873915,0.0012569552,0.0010387133,0.000056609122,0.0036709101],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9734997,0.022128219,0.0008544427,0.0018060283,0.001342212,0.00036933212],"domain_scores_gemma":[0.92886835,0.057311498,0.0039278953,0.006916871,0.0026436085,0.00033183268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0275325,0.0009186394,0.002176752,0.0013708809,0.0004712593,0.0021437614,0.0021873033,0.001565387,0.002310716],"category_scores_gemma":[0.062404793,0.0011348596,0.0021455572,0.0021240828,0.0013125457,0.0022270223,0.0022336948,0.0023268722,0.0004146478],"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":[0.00029589704,0.00019712516,0.03399767,0.0006086565,0.0012767019,0.0006122932,0.000820076,0.42639163,0.0012824532,0.37973937,0.0026172947,0.15216091],"study_design_scores_gemma":[0.00006532278,0.00016442187,0.0069993646,0.00010117563,0.00017677211,0.00010886762,0.0000853737,0.84236133,0.0005823836,0.14511913,0.004160729,0.00007517594],"about_ca_topic_score_codex":0.006832735,"about_ca_topic_score_gemma":0.00599596,"teacher_disagreement_score":0.0275325,"about_ca_system_score_codex":0.0010108877,"about_ca_system_score_gemma":0.0019579355,"threshold_uncertainty_score":0.14560753},"labels":[],"label_agreement":null},{"id":"W4390105437","doi":"10.1093/ectj/utad027","title":"A new method for generating random correlation matrices","year":2023,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Advanced Statistical Methods and Models","field":"Mathematics","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":"Austrian Science Fund","keywords":"Mathematics; Correlation; Applied mathematics; Statistics","score_opus":0.2238304600447305,"score_gpt":0.46810199830238447,"score_spread":0.24427153825765396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390105437","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011089867,0.000023757455,0.9978131,0.000045067132,0.000034730954,0.00003500873,0.000055010423,0.00028845703,0.0005958904],"genre_scores_gemma":[0.05430315,0.000102629776,0.9402691,0.00010409764,0.00009828087,0.00036801328,0.00034460402,0.00035867802,0.004051574],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997338,0.0011493342,0.00010336252,0.00043136222,0.00085416035,0.00012383492],"domain_scores_gemma":[0.9933954,0.0030447678,0.00046634753,0.0014505716,0.0014154349,0.00022759089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032022307,0.0007078211,0.0008314696,0.001802226,0.0006144122,0.0011771399,0.0016459172,0.00089877524,0.0076465504],"category_scores_gemma":[0.01229236,0.0007142812,0.0010226731,0.0012867834,0.0010499991,0.0016990167,0.0017108959,0.0019759245,0.0021982235],"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":[0.0002124729,0.00013386014,0.0020105494,0.00021915001,0.00014816529,0.00031981856,0.00027260656,0.23412937,0.0142892385,0.41189918,0.01335233,0.32301322],"study_design_scores_gemma":[0.00007904163,0.00005254633,0.0004069252,0.000033705262,0.000022742377,0.00020612213,0.00001890018,0.9012595,0.0054764617,0.07942323,0.012959403,0.000061498184],"about_ca_topic_score_codex":0.001831355,"about_ca_topic_score_gemma":0.001992868,"teacher_disagreement_score":0.0076465504,"about_ca_system_score_codex":0.0006488149,"about_ca_system_score_gemma":0.0013526034,"threshold_uncertainty_score":0.025580287},"labels":[],"label_agreement":null},{"id":"W4392121136","doi":"10.1093/ectj/utae006","title":"Threshold nonlinearities and the democracy-growth nexus","year":2024,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Political Conflict and Governance","field":"Social Sciences","cited_by":7,"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","keywords":"Nexus (standard); Democracy; Economics; Political science; Economic system; Computer science; Law; Politics","score_opus":0.03956971839418593,"score_gpt":0.30008011810238877,"score_spread":0.26051039970820283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392121136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90379524,0.00043950923,0.07958428,0.002093124,0.000026212914,0.000031972824,0.00041846017,0.00014041853,0.013470785],"genre_scores_gemma":[0.99789894,0.000066447705,0.0010072934,0.000024359686,0.000006447894,0.000007838025,0.000052010713,0.0000067040714,0.0009299293],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9992361,0.0003096848,0.000043189637,0.00017392449,0.00012246864,0.00011460776],"domain_scores_gemma":[0.9926795,0.0045766835,0.0014840465,0.0006327458,0.0004281095,0.00019888501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002151807,0.00014632994,0.00045311725,0.0007104432,0.00028659301,0.0018739866,0.00041333423,0.00052888907,0.0049306126],"category_scores_gemma":[0.010173652,0.0001568797,0.0004305503,0.00097362406,0.0011058489,0.001511987,0.0012908833,0.0011934629,0.00038108186],"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":[0.00023636337,0.00020239569,0.33736125,0.00021840804,0.00030928658,0.00071352004,0.0007942443,0.24585725,0.0032162433,0.3572088,0.002179244,0.05170304],"study_design_scores_gemma":[0.000023673763,0.000090082634,0.10040042,0.00006844432,0.00007961829,0.00017997046,0.0006151225,0.5742156,0.001770905,0.31908837,0.0034264405,0.00004144139],"about_ca_topic_score_codex":0.0031127483,"about_ca_topic_score_gemma":0.0029873631,"teacher_disagreement_score":0.0049306126,"about_ca_system_score_codex":0.0010930268,"about_ca_system_score_gemma":0.00062240724,"threshold_uncertainty_score":0.016494572},"labels":[],"label_agreement":null},{"id":"W4399025718","doi":"10.1093/ectj/utae013","title":"The maximally selected likelihood ratio test in random coefficient models","year":2024,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Likelihood-ratio test; Statistics; Mathematics; Test (biology); Geology","score_opus":0.07777393675850071,"score_gpt":0.3270037933605977,"score_spread":0.249229856602097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399025718","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030763457,0.0007777055,0.96553093,0.00070558913,0.00006190036,0.00006667021,0.00013350525,0.00027364254,0.001686594],"genre_scores_gemma":[0.7712659,0.00051669567,0.22513051,0.00044266143,0.0004231618,0.00038140992,0.00039559495,0.00016111853,0.001283084],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.96958935,0.026439022,0.00049479963,0.0015533116,0.0014839128,0.00043962544],"domain_scores_gemma":[0.89808327,0.09143452,0.004080411,0.0034294361,0.0022361132,0.0007362163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02482704,0.0006954276,0.0017640633,0.003263614,0.00044559775,0.0014689344,0.0024717154,0.0014612568,0.0026929074],"category_scores_gemma":[0.1136036,0.0004296027,0.0015394555,0.0018007958,0.0033323858,0.0028773847,0.0024273621,0.0021724685,0.00047300477],"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":[0.00067958445,0.0001579178,0.01699474,0.00071449066,0.0010747345,0.0018094034,0.00043854746,0.18514228,0.0033136054,0.58103704,0.0061731795,0.20246442],"study_design_scores_gemma":[0.000089167566,0.00028367055,0.0040369774,0.000100885074,0.00009550751,0.000535259,0.000079443,0.5669307,0.0012444897,0.42379344,0.0027420612,0.000068477166],"about_ca_topic_score_codex":0.00048574695,"about_ca_topic_score_gemma":0.00031040565,"teacher_disagreement_score":0.02482704,"about_ca_system_score_codex":0.00069217285,"about_ca_system_score_gemma":0.0011273732,"threshold_uncertainty_score":0},"labels":[{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"grok","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"opus","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W4403527377","doi":"10.1093/ectj/utae019","title":"On robust inference in time-series regression","year":2024,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Fault Detection and Control Systems","field":"Engineering","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":"Concordia University","funders":"","keywords":"Inference; Series (stratigraphy); Econometrics; Computer science; Time series; Regression; Mathematics; Statistics; Artificial intelligence","score_opus":0.01968725976226844,"score_gpt":0.23038238101903757,"score_spread":0.21069512125676915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403527377","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032198422,0.000976297,0.99221987,0.0008949488,0.00009463312,0.00003610386,0.00014691352,0.00024107823,0.002170209],"genre_scores_gemma":[0.40260562,0.0055798637,0.5815431,0.00088616257,0.0013278744,0.00065236114,0.0008640177,0.0005719534,0.0059691034],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97639275,0.018119514,0.0007940881,0.0016960567,0.0024793788,0.00051829],"domain_scores_gemma":[0.8035878,0.18016233,0.0045910785,0.0070494954,0.004247479,0.00036182298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.040648963,0.0013671344,0.0030966217,0.0029722503,0.00085573713,0.0029367218,0.0032532336,0.002367162,0.004263173],"category_scores_gemma":[0.1988277,0.0010600085,0.0020892792,0.0041736877,0.0034812186,0.0035315661,0.002965595,0.0044174492,0.0008922351],"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":[0.00010078738,0.000049509814,0.0020519928,0.00028395653,0.00032397092,0.00024469467,0.00012254907,0.3801688,0.00037790416,0.5483155,0.002650809,0.06530954],"study_design_scores_gemma":[0.000033412336,0.00003114987,0.0005474697,0.000078587436,0.00003458459,0.000029987552,0.000024611772,0.6796431,0.00035366084,0.31631592,0.0028784906,0.000029007944],"about_ca_topic_score_codex":0.012019915,"about_ca_topic_score_gemma":0.00594744,"teacher_disagreement_score":0.040648963,"about_ca_system_score_codex":0.0025890726,"about_ca_system_score_gemma":0.0028926684,"threshold_uncertainty_score":0.21497488},"labels":[],"label_agreement":null},{"id":"W7116976449","doi":"10.1093/ectj/utaf029","title":"Covariates hiding in the tails","year":2025,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Covariate; Index (typography); Power law; Sampling bias; Variation (astronomy)","score_opus":0.06186418459962754,"score_gpt":0.24384600562341593,"score_spread":0.1819818210237884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116976449","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3183999,0.027756792,0.46129733,0.045701545,0.003942015,0.0004518672,0.09569848,0.0030511033,0.04370088],"genre_scores_gemma":[0.92736334,0.005148604,0.017273711,0.0035354062,0.0020000131,0.00026444712,0.021363217,0.0003173736,0.022733865],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99768627,0.0009724333,0.00022576559,0.0005990197,0.00037636553,0.00014006892],"domain_scores_gemma":[0.95516604,0.02574804,0.007155762,0.008011793,0.0029573059,0.00096116844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046519497,0.00044823694,0.0009156246,0.0008952935,0.00061366434,0.002134189,0.0009614959,0.0011724734,0.029561058],"category_scores_gemma":[0.059910152,0.00028037452,0.00086608535,0.0029505938,0.0007867672,0.0033752422,0.0009134724,0.0020611843,0.0043907897],"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":[0.0012243291,0.00015532797,0.32601458,0.0021397446,0.00104406,0.0010198638,0.0009715779,0.0165937,0.001388771,0.19616881,0.14782965,0.3054496],"study_design_scores_gemma":[0.00020069953,0.00053189084,0.2144042,0.0017885425,0.0011326198,0.0019183393,0.0006944426,0.0539379,0.0037157116,0.54927945,0.17216018,0.00023610685],"about_ca_topic_score_codex":0.0035829165,"about_ca_topic_score_gemma":0.0038765583,"teacher_disagreement_score":0.029561058,"about_ca_system_score_codex":0.0005840498,"about_ca_system_score_gemma":0.0011877663,"threshold_uncertainty_score":0.098891616},"labels":[],"label_agreement":null}]}