{"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15245102,0.00045522247,0.83300555,0.0000827321,0.0005999266,0.00008062286,0.00002139822,0.000016237303,0.013287293],"genre_scores_gemma":[0.76639175,0.00017213695,0.2331295,0.000059232938,0.00014796884,0.0000038099845,6.01979e-7,0.000010675811,0.0000843146],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99871695,0.00011325722,0.0004994986,0.00010474448,0.00014588365,0.0004196559],"domain_scores_gemma":[0.99648845,0.0028553307,0.00018585598,0.00014506871,0.00007198203,0.0002532823],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0022564358,0.000115372335,0.00026578337,0.00057962263,0.00006214151,0.00009272961,0.00019377848,0.00007604531,0.0010522868],"category_scores_gemma":[0.005850398,0.00009770404,0.000048903854,0.0006479988,0.000025476846,0.00041378173,0.000062884144,0.0003909325,0.000044422304],"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":[0.0000066479442,0.00014271254,0.0629987,0.000025895022,0.000021704172,0.000006699029,0.0007339226,0.0003333332,0.00000612925,0.92006576,0.0006935,0.014965028],"study_design_scores_gemma":[0.0002788648,0.000039766936,0.010189721,0.000028492635,0.0000114933555,0.000036096517,0.000083581785,0.013383727,0.0000266958,0.9752996,0.00046408374,0.000157899],"about_ca_topic_score_codex":0.000008175369,"about_ca_topic_score_gemma":0.000001345687,"teacher_disagreement_score":0.6139407,"about_ca_system_score_codex":0.00012340138,"about_ca_system_score_gemma":0.000051223364,"threshold_uncertainty_score":0.9998609},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25979245,0.00033250565,0.6727898,0.0005391051,0.00088337454,0.0006457474,0.000035853864,0.000033862543,0.064947315],"genre_scores_gemma":[0.9273155,0.00023348154,0.06980215,0.00017717954,0.00027126717,0.00003596646,0.000007622621,0.00004209081,0.0021147472],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981233,0.00012332262,0.0010040655,0.0002161766,0.00024084077,0.0002923245],"domain_scores_gemma":[0.99882513,0.00011643285,0.0003882523,0.00029092334,0.0001521159,0.00022715396],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0022146045,0.00014629589,0.0002961917,0.0011560874,0.00006960283,0.00010182807,0.00023591895,0.00007926826,0.0010858955],"category_scores_gemma":[0.00018361653,0.00014102421,0.00007654516,0.0009395331,0.0000107625365,0.0004013479,0.000052545816,0.00018714575,0.00011141353],"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":[0.00019899511,0.0021814832,0.016034871,0.0004250357,0.00018300086,0.00003216988,0.046856303,0.026169544,0.000030467585,0.8705955,0.024936186,0.012356449],"study_design_scores_gemma":[0.0038264696,0.000737606,0.013673919,0.00032810654,0.00004747127,0.000098583325,0.0074910917,0.045295637,0.00049963186,0.9010002,0.025540847,0.0014604515],"about_ca_topic_score_codex":0.00004439749,"about_ca_topic_score_gemma":0.000014840914,"teacher_disagreement_score":0.6675231,"about_ca_system_score_codex":0.00060282944,"about_ca_system_score_gemma":0.000049213373,"threshold_uncertainty_score":0.99982727},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8170758,0.0017264882,0.061082844,0.00033070444,0.0013718368,0.00017771729,0.00025531437,0.000028088049,0.11795123],"genre_scores_gemma":[0.99575377,0.00021541306,0.0028234536,0.00010152276,0.00026485557,0.000006178131,0.000029948498,0.00002625123,0.00077860145],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99786615,0.000025792811,0.0013929068,0.00030295024,0.000055563272,0.00035662588],"domain_scores_gemma":[0.9979469,0.00009706352,0.0014114832,0.00026527626,0.00006331013,0.00021594083],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011912024,0.00021209902,0.0005198421,0.0017950777,0.0002045128,0.00011876414,0.00029918054,0.00015465304,0.004754732],"category_scores_gemma":[0.00046695818,0.0002422415,0.0002269109,0.0005838269,0.00008236471,0.0012592709,0.000022884848,0.00036596565,0.00058979995],"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":[0.0006759067,0.0013184904,0.26178503,0.00016087614,0.00090744987,0.000019891957,0.0054712435,0.20303358,0.00007270749,0.49027026,0.021442542,0.014842028],"study_design_scores_gemma":[0.0037687276,0.0011242155,0.41609374,0.000056627436,0.00006460086,0.0006270892,0.000555147,0.2798297,0.0014809864,0.27881724,0.01623635,0.0013455764],"about_ca_topic_score_codex":0.00032073446,"about_ca_topic_score_gemma":0.0000120208115,"teacher_disagreement_score":0.21145302,"about_ca_system_score_codex":0.00020215176,"about_ca_system_score_gemma":0.00005342625,"threshold_uncertainty_score":0.9961551},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9745223,0.004061412,0.0024949978,0.0015917673,0.0024290031,0.0002676728,0.00056792813,0.000028346712,0.014036585],"genre_scores_gemma":[0.9943153,0.0014785122,0.002759518,0.0002709272,0.0002939878,0.000009607789,0.000028015233,0.000047319267,0.0007967698],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99718064,0.000055937064,0.0012414433,0.0007585851,0.00005102857,0.00071235467],"domain_scores_gemma":[0.99579006,0.0005026612,0.001246882,0.0020910758,0.00003139279,0.00033791782],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0041032373,0.00028672005,0.0007590042,0.0016868842,0.00061206176,0.0010438669,0.002797981,0.0002228388,0.00024141317],"category_scores_gemma":[0.0033397602,0.00035393576,0.00017283195,0.00035993836,0.00010423023,0.003288562,0.00072702806,0.00063790235,0.00094446575],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006708044,0.0005508642,0.9437715,0.00007798483,0.00021738606,0.00043040465,0.00036075414,0.008870075,0.000024150339,0.030903699,0.0076446882,0.0064777303],"study_design_scores_gemma":[0.004111167,0.0002035046,0.69869125,0.000045099634,0.000009802524,0.00012957587,0.00008134798,0.16572776,0.000017816656,0.074982956,0.055267893,0.0007318059],"about_ca_topic_score_codex":0.00019266059,"about_ca_topic_score_gemma":0.000057091453,"teacher_disagreement_score":0.2450802,"about_ca_system_score_codex":0.00041789163,"about_ca_system_score_gemma":0.00008004485,"threshold_uncertainty_score":0.99999315},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04548988,0.000053231215,0.941821,0.000017041368,0.0001979108,0.000054618537,0.000008883901,0.000010225269,0.01234726],"genre_scores_gemma":[0.54059374,0.000030470796,0.4592852,0.0000137225015,0.00004093423,0.0000012127485,2.393983e-7,0.000007165401,0.000027349144],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989709,0.0000654251,0.0005698832,0.000092572955,0.00014314019,0.000158041],"domain_scores_gemma":[0.9985642,0.0006503228,0.00036355268,0.00014135768,0.00015685825,0.00012375377],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011409991,0.00008386025,0.00024165696,0.000404774,0.000050428258,0.000021612095,0.00016786731,0.000062307496,0.0010977242],"category_scores_gemma":[0.00305354,0.00007209186,0.00007177164,0.00039299365,0.00004209061,0.0001914474,0.000029757983,0.00020287365,0.000015716949],"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":[0.00006442601,0.00031097137,0.0041623237,0.00007607172,0.0000919729,0.0000117388245,0.0010932051,0.003013089,0.000010748364,0.83065885,0.00048484473,0.16002177],"study_design_scores_gemma":[0.00024339963,0.00009527337,0.002296381,0.00001521575,0.000018701006,0.000020168733,0.000022343671,0.23928796,0.00029500423,0.7576125,0.000021755435,0.00007126292],"about_ca_topic_score_codex":0.0000056843164,"about_ca_topic_score_gemma":6.4976365e-7,"teacher_disagreement_score":0.49510384,"about_ca_system_score_codex":0.000027905471,"about_ca_system_score_gemma":0.00005814234,"threshold_uncertainty_score":0.9998154},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.928275,0.0008534488,0.022874724,0.0012167718,0.0020985305,0.00022030261,0.00007926631,0.00007879435,0.044303194],"genre_scores_gemma":[0.9938481,0.00011169336,0.003097476,0.00028848034,0.00083025347,0.000009515655,0.000022189754,0.000079066405,0.0017132513],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99712443,0.00006621132,0.0012481336,0.00071213103,0.000064998705,0.00078410166],"domain_scores_gemma":[0.99721545,0.00026053755,0.0012879143,0.00058406545,0.0001252516,0.0005267517],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0029363756,0.00038504973,0.00084150134,0.0017478099,0.0003934536,0.00044984068,0.0006214262,0.00022301968,0.0020577456],"category_scores_gemma":[0.0009965441,0.00040828533,0.00020756682,0.001282082,0.00012888703,0.0011333525,0.00009839409,0.00085848774,0.0019351483],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018822514,0.00026470443,0.93398386,0.000034351488,0.00029918927,0.000027483049,0.00031735835,0.00312223,0.000015587098,0.05492722,0.002145945,0.004673844],"study_design_scores_gemma":[0.006606803,0.0019376272,0.70274585,0.00005501403,0.00006690482,0.0014944398,0.00020179573,0.014222336,0.00012077901,0.06337962,0.20701833,0.0021504737],"about_ca_topic_score_codex":0.000060766033,"about_ca_topic_score_gemma":0.00005207632,"teacher_disagreement_score":0.231238,"about_ca_system_score_codex":0.00023430193,"about_ca_system_score_gemma":0.00010366323,"threshold_uncertainty_score":0.9998369},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88529855,0.0016015907,0.005125152,0.000103914324,0.0011747895,0.00013377728,0.00028103217,0.00002092186,0.10626028],"genre_scores_gemma":[0.99533606,0.0012572957,0.0022250137,0.0001802338,0.00029684414,0.0000044784806,0.0000088029155,0.000045589593,0.0006456733],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973093,0.000021396321,0.0016163972,0.0003902505,0.000043758308,0.0006188513],"domain_scores_gemma":[0.99810594,0.00009704841,0.00094710244,0.00041075324,0.00004566725,0.0003934791],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001324283,0.00027525463,0.00076991756,0.0021894951,0.00014887414,0.00009771859,0.0006336277,0.00015532826,0.005152869],"category_scores_gemma":[0.00027563353,0.00031284717,0.00040054653,0.0006608149,0.00010379765,0.0008748483,0.0000724415,0.00040748517,0.0006432833],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006872677,0.00029392893,0.9585125,0.000044491368,0.00033861664,0.000033216726,0.0017499707,0.000111517045,0.000008168601,0.028169312,0.0051560826,0.0055134627],"study_design_scores_gemma":[0.0013377711,0.00058137404,0.8810752,0.000030162355,0.000037644582,0.0005238508,0.00010735759,0.0030963516,0.00068629667,0.103803195,0.007827484,0.0008933073],"about_ca_topic_score_codex":0.00011250835,"about_ca_topic_score_gemma":0.0000070550627,"teacher_disagreement_score":0.11003752,"about_ca_system_score_codex":0.00016878388,"about_ca_system_score_gemma":0.000022843922,"threshold_uncertainty_score":0.99993235},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21618281,0.0006363792,0.78128606,0.00014452956,0.0005542069,0.00010256308,0.000072816525,0.000006708645,0.0010138961],"genre_scores_gemma":[0.95665115,0.00010890359,0.042847045,0.0000711203,0.00014571428,0.000006268539,0.000009977727,0.000014573835,0.00014522873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99839294,0.000038721286,0.0010794664,0.00021451604,0.00007700603,0.00019732714],"domain_scores_gemma":[0.9983188,0.0001700735,0.0011109356,0.00020382859,0.0001193281,0.00007703935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013295896,0.00012844593,0.00033530558,0.0006815027,0.0003925834,0.00003768168,0.00028727486,0.0000865492,0.00014335342],"category_scores_gemma":[0.001086623,0.00012278097,0.00021109523,0.0006702161,0.00010608392,0.0005285389,0.00005565732,0.00032729542,0.00004069995],"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":[0.000012507049,0.000071014234,0.0039105574,0.000007092098,0.00003853321,6.6531163e-7,0.0005890989,0.93772215,0.0000149421185,0.05242342,0.00015373463,0.0050562974],"study_design_scores_gemma":[0.00026148313,0.000025338632,0.009587699,0.000005366457,0.0000047469284,0.000046482204,0.000008150727,0.71640956,0.00012042281,0.27336764,0.0000675131,0.00009556214],"about_ca_topic_score_codex":0.00003165274,"about_ca_topic_score_gemma":0.0000017637644,"teacher_disagreement_score":0.7404684,"about_ca_system_score_codex":0.00020512454,"about_ca_system_score_gemma":0.00007983988,"threshold_uncertainty_score":0.5006863},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23227775,0.000097273,0.7668766,0.00012501828,0.00008184303,0.00018929217,0.00001812762,0.000010816815,0.00032332793],"genre_scores_gemma":[0.29259163,0.000038675873,0.7072165,0.000033592547,0.000036123285,0.0000113039705,0.0000022091824,0.000012182313,0.000057807738],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987096,0.00010279155,0.000596101,0.00019838783,0.00015712416,0.00023599417],"domain_scores_gemma":[0.9969492,0.0023584124,0.00030194208,0.00012871182,0.00011228424,0.00014944868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019729338,0.00013667363,0.00036112437,0.0005229369,0.00018722106,0.00007364407,0.00009996334,0.0000803154,0.00011658002],"category_scores_gemma":[0.0029873215,0.00011452602,0.000059544203,0.00028691333,0.00003028773,0.00025169394,0.000029157554,0.00025033567,0.0000014443534],"study_design_candidate":"design_other","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":[0.00031137932,0.00085602514,0.041526362,0.00034717083,0.000089129004,0.00006479416,0.0014731399,0.0014643308,0.00020772923,0.027507624,0.0024448454,0.9237075],"study_design_scores_gemma":[0.000725313,0.000093377734,0.004809389,0.000055328364,0.000009042095,0.000029625202,0.000015029884,0.730932,0.000055589444,0.26312935,0.00004323842,0.0001027232],"about_ca_topic_score_codex":0.000005467365,"about_ca_topic_score_gemma":6.3059514e-7,"teacher_disagreement_score":0.9236047,"about_ca_system_score_codex":0.00012518668,"about_ca_system_score_gemma":0.000064719825,"threshold_uncertainty_score":0.46702355},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14793782,0.00006521959,0.8509407,0.00031109172,0.00017964112,0.000096363736,0.0002578066,0.000008596693,0.00020275955],"genre_scores_gemma":[0.76522356,0.00024589055,0.23437767,0.000056451543,0.00006759463,0.0000020744183,0.000006952514,0.0000071654367,0.000012636294],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99832344,0.000077674544,0.0008004635,0.0002150311,0.00024360807,0.00033978035],"domain_scores_gemma":[0.9862968,0.012518438,0.0004017009,0.00029050745,0.00020622478,0.00028635067],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0011023631,0.00017256709,0.0004346085,0.0004229551,0.00012802087,0.0000546369,0.00035114546,0.00012926343,0.00018427515],"category_scores_gemma":[0.06906261,0.00014471907,0.00006585495,0.0008140757,0.00011133258,0.00021166001,0.00010963998,0.0005584243,0.000003314399],"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":[0.00024723436,0.0021237358,0.20433047,0.0003879486,0.00013875155,0.00010953737,0.0013910644,0.00453388,0.00031941143,0.637734,0.0009673755,0.1477166],"study_design_scores_gemma":[0.0008760061,0.00035900561,0.05911289,0.00018092286,0.000022353934,0.000014238089,0.000069137925,0.06608877,0.00030187675,0.87268996,0.000067546614,0.00021728704],"about_ca_topic_score_codex":0.000024909577,"about_ca_topic_score_gemma":0.000044633423,"teacher_disagreement_score":0.6172857,"about_ca_system_score_codex":0.00009635274,"about_ca_system_score_gemma":0.00011890252,"threshold_uncertainty_score":0.93877906},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28812796,0.00033747172,0.6728718,0.01046806,0.0020430794,0.0009182258,0.0019361649,0.00013268182,0.023164533],"genre_scores_gemma":[0.7785119,0.00014188867,0.21532756,0.0041730255,0.00091583753,0.00001271654,0.000013295924,0.00006801247,0.0008357735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99846905,0.00008619745,0.00063113606,0.00016094506,0.00036936445,0.00028332873],"domain_scores_gemma":[0.9881359,0.010953233,0.0003617971,0.00023891045,0.00012455434,0.00018563587],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00062571274,0.00018210478,0.00036079047,0.00045682883,0.00015841688,0.00007829238,0.00030309113,0.000058059493,0.002335992],"category_scores_gemma":[0.007974027,0.00011546206,0.000111319496,0.0006928999,0.000105640655,0.00008486379,0.00002840806,0.0004237316,0.00012413813],"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":[0.00011155977,0.0013953516,0.00127691,0.000056370627,0.00009243272,0.00003171156,0.000064187385,0.0020449508,0.0000136579965,0.94408864,0.025430053,0.025394158],"study_design_scores_gemma":[0.0022274815,0.001145834,0.0049460684,0.00006370876,0.000099036464,0.000035849404,0.000039443938,0.18888773,0.0007439491,0.7969672,0.004424447,0.00041923762],"about_ca_topic_score_codex":0.0000033285833,"about_ca_topic_score_gemma":0.0000015886307,"teacher_disagreement_score":0.49038392,"about_ca_system_score_codex":0.00013142895,"about_ca_system_score_gemma":0.00007603717,"threshold_uncertainty_score":0.998576},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017252252,0.0010300417,0.9688878,0.0005948798,0.002241449,0.00043171993,0.000089992805,0.000045344503,0.009426495],"genre_scores_gemma":[0.21979629,0.00052574323,0.77820796,0.00013444091,0.000497324,0.000011724224,0.0000020337031,0.00005470527,0.00076981436],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99651456,0.00033758883,0.0014713595,0.00047592266,0.00042499395,0.0007755839],"domain_scores_gemma":[0.99490064,0.0026105917,0.0012316863,0.00043369026,0.00025561947,0.000567798],"candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0016992057,0.0004362848,0.0008248338,0.0010089619,0.0004311078,0.0009139837,0.00050861447,0.0002812252,0.00679727],"category_scores_gemma":[0.010776639,0.00041956417,0.00027758177,0.0011811134,0.00020747066,0.00053511566,0.00008823414,0.0011728052,0.001156975],"study_design_candidate":"design_other","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":[0.00007095504,0.0009382538,0.007374521,0.00042094543,0.00032223028,0.00012865636,0.0014279784,0.0003420188,0.000021525948,0.058140557,0.019778637,0.9110337],"study_design_scores_gemma":[0.0032077483,0.0007893567,0.0033930354,0.0004677123,0.00037963284,0.00093379203,0.0001822442,0.634308,0.00022918901,0.35070345,0.004200936,0.001204927],"about_ca_topic_score_codex":0.0000057846523,"about_ca_topic_score_gemma":0.0000013886245,"teacher_disagreement_score":0.9098288,"about_ca_system_score_codex":0.0004489695,"about_ca_system_score_gemma":0.00007865143,"threshold_uncertainty_score":0.9998256},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98338777,0.0032860464,0.00070886203,0.004443156,0.000891378,0.0001873555,0.005840018,0.000019521769,0.0012358673],"genre_scores_gemma":[0.99478436,0.00011309586,0.00020880239,0.0009386412,0.0024683748,0.000013443886,0.0011068087,0.00002335325,0.00034315322],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981895,0.000031384072,0.00092714326,0.0003585488,0.000061651604,0.00043177232],"domain_scores_gemma":[0.99853253,0.00021487765,0.00081665034,0.00022743041,0.000043649205,0.00016488225],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006618495,0.00024118024,0.0003761319,0.00046173946,0.00074214366,0.0007931652,0.00030543326,0.00015335539,0.0032780955],"category_scores_gemma":[0.00018315864,0.00023173708,0.00014101744,0.00038428413,0.000112187176,0.001496115,0.00007199973,0.00041180965,0.00037117358],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033211807,0.000049991144,0.9421898,0.000011318517,0.00014989491,0.00000851298,0.0007149263,0.00052408635,0.0000029937723,0.038060788,0.015319913,0.0029345744],"study_design_scores_gemma":[0.0006855306,0.000054471042,0.7879116,0.0000069685243,0.000013672657,0.000058694968,0.000025919917,0.009589507,0.000023226887,0.15837207,0.0430062,0.00025216845],"about_ca_topic_score_codex":0.0016768258,"about_ca_topic_score_gemma":0.00016233558,"teacher_disagreement_score":0.15427822,"about_ca_system_score_codex":0.0002396375,"about_ca_system_score_gemma":0.00003466877,"threshold_uncertainty_score":0.99763304},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9159093,0.0012029851,0.08052584,0.0001238621,0.0002876873,0.0002598118,0.00017843355,0.000010369731,0.0015017265],"genre_scores_gemma":[0.99786115,0.00023425349,0.0013536077,0.00010092935,0.000077232784,0.000016271599,0.00003801681,0.000029955603,0.0002886069],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980915,0.000029176314,0.0010634015,0.00034140496,0.0000724091,0.00040208112],"domain_scores_gemma":[0.9980836,0.00051787385,0.00079436996,0.00029995205,0.00011727208,0.0001869373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007001946,0.00021348929,0.0007929945,0.0023340555,0.00014299035,0.000067730485,0.00035135343,0.00012466389,0.00040376198],"category_scores_gemma":[0.00060980674,0.00020915049,0.00020263734,0.001958787,0.00009743852,0.00045644934,0.00003840426,0.0002677399,0.00010005322],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012487239,0.00033925223,0.9866096,0.000057712514,0.00034032253,0.00006660864,0.0003743675,0.0054212315,0.000034252385,0.004303965,0.00038625766,0.0019415725],"study_design_scores_gemma":[0.0028651366,0.0007554744,0.9863756,0.00004039448,0.000038117807,0.00014067286,0.000070969625,0.0042019933,0.00018940638,0.0033343718,0.0016098086,0.00037811216],"about_ca_topic_score_codex":0.00015246845,"about_ca_topic_score_gemma":0.000082969826,"teacher_disagreement_score":0.08195184,"about_ca_system_score_codex":0.00013733184,"about_ca_system_score_gemma":0.00008089921,"threshold_uncertainty_score":0.85289097},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45077008,0.0036837235,0.5070069,0.015184592,0.0037254244,0.00034102637,0.00016328754,0.000051971798,0.019072976],"genre_scores_gemma":[0.9852661,0.00036801974,0.006758018,0.004721854,0.00094372424,0.000004356814,0.000005803717,0.000038125458,0.0018940086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99762404,0.000027345275,0.0012769571,0.0003495888,0.00005899526,0.0006630526],"domain_scores_gemma":[0.9974018,0.0007974465,0.0011281914,0.00039328667,0.000027403943,0.00025189592],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0041183666,0.00023969893,0.00043129336,0.00085196143,0.0004368655,0.000475681,0.00061162503,0.00011895198,0.0030537588],"category_scores_gemma":[0.0004299665,0.00022207257,0.00023308897,0.00069615303,0.000103509265,0.0009386653,0.00006936075,0.00054806477,0.0027424165],"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":[0.0002612836,0.0004344696,0.056138158,0.00006192262,0.0013194943,0.00009753704,0.0031895307,0.2803613,0.00002051097,0.58176905,0.062125187,0.014221562],"study_design_scores_gemma":[0.0030962382,0.00029443376,0.1941673,0.000034611072,0.00004297088,0.0010640522,0.0008102598,0.10083036,0.00018617825,0.5527116,0.1454983,0.0012637093],"about_ca_topic_score_codex":0.00018221431,"about_ca_topic_score_gemma":0.000011731678,"teacher_disagreement_score":0.534496,"about_ca_system_score_codex":0.00049869006,"about_ca_system_score_gemma":0.000025675627,"threshold_uncertainty_score":0.99803406},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67390597,0.0060202735,0.2679795,0.0025136233,0.007636627,0.000667141,0.0022071963,0.000059580074,0.039010108],"genre_scores_gemma":[0.9949852,0.00042495775,0.0018846677,0.00009157702,0.0003795031,0.000013333248,0.000037894228,0.000019241628,0.0021636044],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983598,0.000011625478,0.0010515527,0.000228355,0.000023520777,0.00032513696],"domain_scores_gemma":[0.9984381,0.00020968542,0.0009367839,0.0002087164,0.000048198985,0.00015847101],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00078956655,0.00014478384,0.00041965433,0.0010486247,0.00022601764,0.00010280204,0.0001976868,0.00010575766,0.002601546],"category_scores_gemma":[0.0009884886,0.00016824158,0.00027900343,0.0005035364,0.000050423532,0.0005582219,0.000016436048,0.00020889657,0.00037061088],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001267823,0.0014241843,0.30923182,0.00012550183,0.00072821457,0.0000055911037,0.0017907441,0.015017017,0.00007017212,0.16032857,0.46888125,0.04227017],"study_design_scores_gemma":[0.0034851898,0.0011795355,0.10589848,0.00004305014,0.000055084674,0.000393963,0.000221593,0.5081285,0.00048131938,0.0823847,0.2967755,0.00095304946],"about_ca_topic_score_codex":0.00004876955,"about_ca_topic_score_gemma":0.000010361142,"teacher_disagreement_score":0.49311152,"about_ca_system_score_codex":0.00025643967,"about_ca_system_score_gemma":0.000010310997,"threshold_uncertainty_score":0.9983102},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7667159,0.0037690953,0.21763417,0.00033112158,0.001156519,0.00011909653,0.000053081374,0.0000391154,0.0101819355],"genre_scores_gemma":[0.9946492,0.0011636417,0.0027413792,0.00021525245,0.0004433027,0.000005455682,0.000013374246,0.000031224394,0.0007372277],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99773705,0.000021159069,0.0012377048,0.00044322814,0.00009079155,0.00047006365],"domain_scores_gemma":[0.99848634,0.00013007151,0.00070440135,0.0003111128,0.000111942776,0.00025613484],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001193773,0.00022150492,0.000494474,0.0012868404,0.0007818824,0.00011666184,0.00032674716,0.00017645402,0.00095100445],"category_scores_gemma":[0.00037347563,0.00025467676,0.00026199388,0.0009727618,0.000093740426,0.0008990176,0.000069779686,0.0006028146,0.0003990569],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050678398,0.0002958751,0.95622635,0.00003222987,0.0000978547,0.00005345798,0.0011736307,0.0074901115,0.000017805325,0.022587199,0.007794545,0.004180291],"study_design_scores_gemma":[0.000910513,0.000100090445,0.7413479,0.000026458456,0.000005598466,0.00018331356,0.00010105498,0.17053811,0.000023435252,0.06635092,0.01994454,0.00046804402],"about_ca_topic_score_codex":0.000058875983,"about_ca_topic_score_gemma":0.0000031318002,"teacher_disagreement_score":0.22793327,"about_ca_system_score_codex":0.0003362034,"about_ca_system_score_gemma":0.00012442582,"threshold_uncertainty_score":0.9999905},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49526304,0.00012284865,0.5014602,0.00005805623,0.00027713203,0.00008913789,0.000036519894,0.00002164989,0.002671403],"genre_scores_gemma":[0.7082719,0.00023583663,0.29129395,0.000044172502,0.000050692473,0.000004282824,0.0000050190697,0.000011448044,0.000082702856],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986594,0.0000964629,0.00061867695,0.00016225103,0.00018632221,0.00027693607],"domain_scores_gemma":[0.9973627,0.002028916,0.00025409172,0.00011622968,0.0000804734,0.00015761168],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00085241674,0.00013349792,0.00027187975,0.0005522721,0.00011660082,0.0000631125,0.00018153744,0.00008843394,0.0008942611],"category_scores_gemma":[0.008430351,0.00012483042,0.000043117296,0.00085391355,0.00006478656,0.00024155894,0.000037845333,0.0003980287,0.000035431403],"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":[0.00013617433,0.0020727376,0.5374914,0.00015971044,0.00018508402,0.00029805626,0.001746503,0.00088899763,0.0010184991,0.28106508,0.011888516,0.16304928],"study_design_scores_gemma":[0.0028161388,0.0005794196,0.054761693,0.00016780394,0.000034472796,0.00050016196,0.00014913171,0.15910147,0.0012408397,0.7786052,0.0013219451,0.00072167994],"about_ca_topic_score_codex":0.000021775018,"about_ca_topic_score_gemma":0.0000017405273,"teacher_disagreement_score":0.49754015,"about_ca_system_score_codex":0.00015821008,"about_ca_system_score_gemma":0.00011587849,"threshold_uncertainty_score":0.99992204},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8266761,0.0013651194,0.16870385,0.00011582193,0.0010905615,0.00008853919,0.00007294552,0.000015976797,0.0018711068],"genre_scores_gemma":[0.99403596,0.00008130744,0.00491079,0.00008004122,0.00029297656,8.1217473e-7,0.000008337022,0.000028218416,0.0005615717],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99766463,0.0000336856,0.0015092011,0.00026991148,0.000047414287,0.00047514276],"domain_scores_gemma":[0.997709,0.00031440007,0.001358716,0.00030629974,0.000029641822,0.000281959],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0053469855,0.00018239605,0.00047583025,0.0029563233,0.000274009,0.00011135286,0.0002433761,0.00015281644,0.0013570399],"category_scores_gemma":[0.0008931817,0.00020936427,0.00024216971,0.00087401934,0.00007104463,0.0008361493,0.00005060677,0.00033195503,0.00030597186],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013708861,0.00039990654,0.6461292,0.00007616686,0.0004279591,0.0000695813,0.0013572266,0.29486436,0.00022925687,0.006481009,0.0038625805,0.044731893],"study_design_scores_gemma":[0.0018041413,0.00038606298,0.7062143,0.000057687754,0.000032215543,0.0006388903,0.00019458242,0.2739991,0.0006584739,0.010109583,0.005284626,0.00062033796],"about_ca_topic_score_codex":0.00008889298,"about_ca_topic_score_gemma":0.0000040266386,"teacher_disagreement_score":0.16735987,"about_ca_system_score_codex":0.0004920903,"about_ca_system_score_gemma":0.000049923812,"threshold_uncertainty_score":0.9995558},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20370016,0.00040581138,0.7864283,0.00021179204,0.00040575492,0.00014206408,0.00004467068,0.000006132912,0.008655335],"genre_scores_gemma":[0.8122109,0.00006929542,0.1875201,0.00005827617,0.00011115258,0.0000044217163,4.0194536e-7,0.000005877914,0.000019530833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983904,0.0003225147,0.0005907234,0.00008943653,0.00025498657,0.00035194232],"domain_scores_gemma":[0.9828667,0.016459513,0.00024251884,0.00019902679,0.00008658564,0.00014565315],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0038079806,0.00009754137,0.0002621344,0.0003278822,0.000058348298,0.00006262443,0.00036243215,0.000051886735,0.0008886459],"category_scores_gemma":[0.032842066,0.000064124244,0.000042770367,0.00070383126,0.00010657673,0.00019984091,0.000049350452,0.00043753965,0.000020764415],"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":[0.000011973736,0.00025534854,0.09215532,0.00003664343,0.000011246051,0.000005570306,0.0008329603,0.0000046283108,0.000009489467,0.88045055,0.0012068424,0.025019404],"study_design_scores_gemma":[0.00032380508,0.00017404082,0.18944608,0.000041151514,0.000021080848,0.000075860065,0.0005184293,0.0007222163,0.00013699292,0.80709183,0.0012909416,0.00015758065],"about_ca_topic_score_codex":0.000008684211,"about_ca_topic_score_gemma":0.0000018312412,"teacher_disagreement_score":0.6085108,"about_ca_system_score_codex":0.000041633306,"about_ca_system_score_gemma":0.000058661764,"threshold_uncertainty_score":0.9753047},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33716038,0.00059511437,0.65399307,0.000038645718,0.0009936717,0.0001319532,0.000008219347,0.000019450648,0.0070594777],"genre_scores_gemma":[0.8673836,0.00013558817,0.13186182,0.00006356835,0.00021920551,0.0000029463179,0.0000011807185,0.00003446019,0.00029765902],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969541,0.00013193952,0.0013377613,0.00033260923,0.00044336863,0.0008002084],"domain_scores_gemma":[0.9920232,0.0066802185,0.0003827913,0.0003046915,0.00018071147,0.00042837908],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006756132,0.0002471109,0.0005933136,0.0034194994,0.00015572962,0.00024426775,0.00042243805,0.00022942502,0.00024615575],"category_scores_gemma":[0.00879311,0.00021906485,0.00013600981,0.0047436063,0.00010892433,0.00015528,0.000077228375,0.0010385314,0.00011818413],"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":[0.000117855656,0.0020444684,0.056920905,0.0004473439,0.00019675367,0.0005658028,0.00038566522,0.0017885395,0.00014734778,0.87419915,0.001156542,0.062029604],"study_design_scores_gemma":[0.0030091754,0.0009807361,0.11155171,0.0002910462,0.00012901673,0.0013797571,0.0014973793,0.31252688,0.00012483713,0.56570995,0.00141558,0.0013839472],"about_ca_topic_score_codex":0.000013028907,"about_ca_topic_score_gemma":0.0000053187687,"teacher_disagreement_score":0.5302232,"about_ca_system_score_codex":0.0006584205,"about_ca_system_score_gemma":0.00013306615,"threshold_uncertainty_score":0.99955624},"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":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001084023,0.000037765945,0.9968632,0.00008092855,0.00019298196,0.00017329754,0.00001302926,0.00002859064,0.001526194],"genre_scores_gemma":[0.018113919,0.0000122145,0.98115146,0.0000800974,0.0001730827,0.000007734859,0.000001454415,0.000023261855,0.0004367857],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989527,0.00003281979,0.00046946164,0.00014749968,0.00011473115,0.00028277512],"domain_scores_gemma":[0.996738,0.002562152,0.00026708908,0.00007556632,0.00019741409,0.00015976497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041141063,0.00009961003,0.00020761439,0.000557722,0.00019332899,0.000057627632,0.00008612492,0.00007289802,0.000038673694],"category_scores_gemma":[0.00489474,0.00009258393,0.00009521839,0.00041608358,0.000010771526,0.00022692622,0.000012616949,0.00020898113,0.000002871905],"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":[0.00005138903,0.0000731095,0.000027879885,0.000033811964,0.000030342706,0.0000013949208,0.00010692552,0.02508862,0.00016639987,0.54429406,0.0010498947,0.42907614],"study_design_scores_gemma":[0.00021959735,0.000050015806,0.000017503344,0.0000033598214,0.000017021213,0.000042251813,0.000012404101,0.48278707,0.00022451412,0.51622826,0.00033603466,0.00006196354],"about_ca_topic_score_codex":4.5436673e-7,"about_ca_topic_score_gemma":0.0000023340651,"teacher_disagreement_score":0.45769843,"about_ca_system_score_codex":0.00017981212,"about_ca_system_score_gemma":0.000044235898,"threshold_uncertainty_score":0.5859815},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8806991,0.00051042065,0.06348604,0.00078305183,0.0035556655,0.00018511269,0.00017672707,0.000046735688,0.05055712],"genre_scores_gemma":[0.9892616,0.000119607685,0.008537521,0.00044888596,0.0006806771,0.000009320807,0.0000141558385,0.000040025086,0.0008881652],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979286,0.000020033636,0.0010524772,0.00040373756,0.000042421427,0.00055272836],"domain_scores_gemma":[0.9981149,0.00017965546,0.0009453026,0.0003648808,0.000035105502,0.00036014838],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0014538689,0.00025757178,0.00052912417,0.001581417,0.00036861075,0.0003680765,0.00045219852,0.0001934385,0.005785101],"category_scores_gemma":[0.0006666345,0.0003013188,0.000229797,0.00063817826,0.00009864021,0.0013272802,0.00006590505,0.00094548095,0.0030075961],"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":[0.00019968185,0.00066538976,0.23432367,0.000049190043,0.0008862264,0.00008201171,0.004079149,0.05758724,0.00008802646,0.63561946,0.016029332,0.050390612],"study_design_scores_gemma":[0.0035321866,0.00042189832,0.21783862,0.000017936793,0.00002218203,0.00062705146,0.00017360623,0.28277138,0.00036988873,0.40795323,0.084793195,0.0014788283],"about_ca_topic_score_codex":0.00009294948,"about_ca_topic_score_gemma":0.000014500308,"teacher_disagreement_score":0.22766624,"about_ca_system_score_codex":0.00019510179,"about_ca_system_score_gemma":0.000039930517,"threshold_uncertainty_score":0.9999439},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9624282,0.003458354,0.008045923,0.00019245817,0.0006855421,0.00008740336,0.00007806585,0.000010457877,0.025013566],"genre_scores_gemma":[0.99573994,0.0006542948,0.0027062665,0.00017719931,0.00020327985,8.736538e-7,0.0000031215166,0.00002120622,0.0004937956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980636,0.000007932538,0.0011936693,0.00025339404,0.00003212521,0.0004492294],"domain_scores_gemma":[0.9983897,0.00015750497,0.0009034248,0.00020283871,0.000018439909,0.0003280462],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0023024362,0.00016469383,0.0005119296,0.0018855403,0.00012892357,0.00008935354,0.00022577848,0.00010626465,0.00093365036],"category_scores_gemma":[0.0003162732,0.00019154897,0.00013618222,0.00046675844,0.00009019431,0.00051423366,0.00006059255,0.00025756736,0.00022616565],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005613466,0.0001344691,0.9472218,0.000039203176,0.00025999674,0.000019768147,0.0008022025,0.0006666487,0.000010315601,0.040061817,0.002081626,0.008646016],"study_design_scores_gemma":[0.0025775726,0.00042337851,0.8516068,0.000027240989,0.000023340428,0.00044191588,0.0003066983,0.0068642697,0.0002891247,0.09476501,0.041956604,0.0007180344],"about_ca_topic_score_codex":0.00007722172,"about_ca_topic_score_gemma":0.0000035666924,"teacher_disagreement_score":0.095614985,"about_ca_system_score_codex":0.00014663553,"about_ca_system_score_gemma":0.000014418019,"threshold_uncertainty_score":0.9999796},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04901841,0.000025173127,0.9481314,0.0003868076,0.00008092924,0.0001108975,0.0000012305463,0.000034604338,0.0022105859],"genre_scores_gemma":[0.6967466,0.000011270005,0.30305693,0.0001227475,0.000023826962,0.000011714959,0.0000012544328,0.0000074763466,0.000018174547],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909234,0.000024194755,0.00028489323,0.00015315691,0.00019529401,0.00025010123],"domain_scores_gemma":[0.9992531,0.00022494521,0.00011500245,0.0002410101,0.000087838576,0.00007811338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005495973,0.00011293654,0.00014484332,0.000511364,0.00015719299,0.00041962214,0.00059109495,0.000039411112,0.000011068006],"category_scores_gemma":[0.00020599016,0.000077645476,0.000038786544,0.0016611501,0.00003302453,0.00088692096,0.0000373533,0.00042919308,0.000018902861],"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":[0.0000023099374,0.000057842262,0.000074634234,0.000004514876,0.000006708149,0.000026440219,0.00044407774,0.97655755,0.0000035768999,0.020624002,0.000040498177,0.0021578681],"study_design_scores_gemma":[0.00034171896,0.000053674114,0.00018134077,0.000025428482,0.0000040757277,0.0005000204,0.00003817356,0.94880956,0.000005860637,0.049880963,0.000056730947,0.00010247238],"about_ca_topic_score_codex":8.684295e-7,"about_ca_topic_score_gemma":0.0000012651522,"teacher_disagreement_score":0.6477282,"about_ca_system_score_codex":0.0001251553,"about_ca_system_score_gemma":0.00009425214,"threshold_uncertainty_score":0.40464258},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29377505,0.00056149083,0.7044788,0.00004452781,0.000034126082,0.000906991,0.0000058454993,0.000017242613,0.00017590223],"genre_scores_gemma":[0.73797804,0.00017767768,0.26152208,0.0000085657275,0.000053753905,0.0002236918,0.0000012289079,0.000016004991,0.000018986808],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99871874,0.00045869293,0.00036284124,0.00021804964,0.00006819437,0.00017349793],"domain_scores_gemma":[0.9865258,0.012323063,0.00069995073,0.00022503007,0.0001562499,0.00006993856],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.010381358,0.0001499045,0.00038214438,0.00039839867,0.0003109863,0.00033493317,0.00010581771,0.00006884779,0.0000028156694],"category_scores_gemma":[0.023490004,0.00012173618,0.000042304906,0.00012367193,0.00006606363,0.0007404799,0.000040686555,0.00013714522,4.067335e-7],"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":[0.00031354974,0.00009787371,0.008371863,0.000031741278,0.000088358385,0.0000012236311,0.00022275705,0.00011012551,0.0022435654,0.047411878,0.0000025332267,0.94110453],"study_design_scores_gemma":[0.0021937205,0.0007300368,0.009472446,0.000066933775,0.00013463547,0.00001481086,0.000068489615,0.041972592,0.005708011,0.9394673,0.000021025793,0.0001499829],"about_ca_topic_score_codex":0.00000930358,"about_ca_topic_score_gemma":0.000011865601,"teacher_disagreement_score":0.94095457,"about_ca_system_score_codex":0.00031048214,"about_ca_system_score_gemma":0.00005142415,"threshold_uncertainty_score":0.98473555},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66864187,0.000044166023,0.30067402,0.00008806416,0.0011191732,0.00063900824,0.000032650263,0.000056487672,0.028704593],"genre_scores_gemma":[0.5223706,0.000014054017,0.47701904,0.00012151426,0.00023762153,0.000011036809,9.80096e-7,0.000027376887,0.0001978041],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99735785,0.0003313049,0.0011114982,0.0003812906,0.00034285124,0.00047518435],"domain_scores_gemma":[0.97858995,0.019972706,0.0003589408,0.00040647163,0.00010942008,0.0005625345],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003374046,0.00021431308,0.00085954263,0.00086428225,0.000117828626,0.00018331934,0.00045315237,0.00014034261,0.0005678058],"category_scores_gemma":[0.045408092,0.00018013678,0.00027432095,0.0012782234,0.000038157847,0.00012151679,0.0001517073,0.0005650676,0.00040153787],"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":[0.00029424138,0.0022629916,0.8418559,0.00013084213,0.0007854642,0.00002702813,0.00025338578,0.00041756968,0.000067773086,0.12251327,0.008797952,0.022593603],"study_design_scores_gemma":[0.004118696,0.00047027125,0.0687779,0.00003226615,0.00011999586,0.00009974243,0.000108329165,0.006017767,0.00007829194,0.9173448,0.0023846643,0.00044728376],"about_ca_topic_score_codex":0.0000030919432,"about_ca_topic_score_gemma":6.5509767e-7,"teacher_disagreement_score":0.7948315,"about_ca_system_score_codex":0.00017561189,"about_ca_system_score_gemma":0.000039264363,"threshold_uncertainty_score":0.96263283},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08345141,0.0000822354,0.9057184,0.0000792609,0.00082233286,0.0001845541,0.00014151972,0.000013116192,0.009507157],"genre_scores_gemma":[0.5296722,0.00009165953,0.46976814,0.000052470838,0.00011676784,0.0000053376684,0.000020786149,0.000017629438,0.0002549721],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99844265,0.000101835554,0.00067438825,0.00027913394,0.0002135831,0.00028842717],"domain_scores_gemma":[0.9982413,0.00077809737,0.0002910718,0.0005111285,0.00006227331,0.000116108284],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0026480595,0.000111391935,0.00027232122,0.00046195154,0.000073634576,0.00027694038,0.000541656,0.000072474904,0.0016958943],"category_scores_gemma":[0.0010998994,0.00010644283,0.000028469976,0.00070568064,0.00002452509,0.00090437516,0.00014122647,0.000330925,0.00016137173],"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":[0.00004287254,0.00033832685,0.018461784,0.0000693145,0.00004986208,0.000013957847,0.00013348681,0.0002854964,0.0001394356,0.9542742,0.002914353,0.023276938],"study_design_scores_gemma":[0.0005731778,0.000044797976,0.0015777234,0.00003250635,0.000015992982,0.000063738786,0.00007216722,0.16765165,0.00006665166,0.8285647,0.0011839817,0.0001528963],"about_ca_topic_score_codex":0.00002094074,"about_ca_topic_score_gemma":0.0000037280543,"teacher_disagreement_score":0.44622082,"about_ca_system_score_codex":0.00018148252,"about_ca_system_score_gemma":0.00014096659,"threshold_uncertainty_score":0.9992167},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68608356,0.022826714,0.26618776,0.009360335,0.0014123986,0.0003146148,0.00012670892,0.0000815173,0.013606428],"genre_scores_gemma":[0.9942732,0.00032372432,0.00406017,0.0005354873,0.0005847835,0.000003442379,0.000008258214,0.000024728128,0.00018620324],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979191,0.000018475623,0.0012314689,0.0004258805,0.0000690529,0.0003360351],"domain_scores_gemma":[0.9985375,0.00009149742,0.00069519144,0.00019171454,0.00006597495,0.00041811896],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005075998,0.0002090683,0.0005664849,0.0007098719,0.0003550567,0.00063275156,0.00030799856,0.00008819984,0.006011628],"category_scores_gemma":[0.0005368305,0.0002329101,0.00019891754,0.0012917959,0.00007325006,0.00057487487,0.00011476896,0.0003199917,0.0010242425],"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":[0.00007415678,0.0000577703,0.028258976,0.00008019707,0.0005365832,0.000079412624,0.0035950674,0.014105448,0.0000063826674,0.7397041,0.0009367417,0.21256518],"study_design_scores_gemma":[0.00030002982,0.00047068173,0.011624352,0.0000137540555,0.000048289345,0.00046043337,0.0013533462,0.6333823,0.00007438882,0.30155593,0.049844723,0.0008717219],"about_ca_topic_score_codex":0.00006903223,"about_ca_topic_score_gemma":0.000014663581,"teacher_disagreement_score":0.6192769,"about_ca_system_score_codex":0.00009459851,"about_ca_system_score_gemma":0.000027608203,"threshold_uncertainty_score":0.9997536},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10911881,0.00650916,0.7706308,0.0015713589,0.0018438123,0.00065568846,0.0024150927,0.00010196468,0.107153356],"genre_scores_gemma":[0.9645419,0.00033209228,0.030564385,0.001317006,0.0016913752,0.00012988597,0.00093257776,0.00014432828,0.00034642787],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99543107,0.000070240116,0.0020790247,0.0013106561,0.00014780287,0.000961185],"domain_scores_gemma":[0.9960287,0.00014555661,0.002134159,0.0008585584,0.00018267623,0.0006503086],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016736259,0.00070442184,0.0016100479,0.0025199163,0.00037708203,0.0010856638,0.0009808061,0.00062963116,0.0010165724],"category_scores_gemma":[0.00015182783,0.0008015368,0.00075434375,0.0008002534,0.00018844593,0.00075209065,0.0004383931,0.0020667093,0.00023124232],"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":[0.00013495902,0.0011041798,0.028864248,0.0003815243,0.001549688,0.00013797575,0.00045353753,0.78408223,0.0000014079288,0.17990303,0.0028984589,0.00048878393],"study_design_scores_gemma":[0.0043887715,0.00035426128,0.0058617317,0.00012906833,0.00013025034,0.00044916855,0.00019426548,0.5974528,0.00010075836,0.3732133,0.01535023,0.0023754064],"about_ca_topic_score_codex":0.000061704,"about_ca_topic_score_gemma":0.000011880814,"teacher_disagreement_score":0.8554231,"about_ca_system_score_codex":0.0008658907,"about_ca_system_score_gemma":0.0006816274,"threshold_uncertainty_score":0.9999513},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024456905,0.0008750104,0.97129714,0.00006686019,0.001632677,0.00019129843,0.00005924815,0.000020897265,0.0013999611],"genre_scores_gemma":[0.2323945,0.00024775314,0.7670734,0.000013189997,0.00015443121,0.0000049438613,0.00002683635,0.000034401884,0.00005053426],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99786776,0.00019694447,0.0011275667,0.00029669167,0.00029072387,0.0002203266],"domain_scores_gemma":[0.99579716,0.0018392899,0.0014634691,0.00024310482,0.00048168955,0.00017529134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013663295,0.00023104493,0.0007537731,0.00075313455,0.00010114263,0.0001348499,0.00019717663,0.0002570671,0.00024974503],"category_scores_gemma":[0.0052601965,0.00023367631,0.00025198466,0.00038837115,0.000060658836,0.00017234434,0.00020534049,0.0010113252,0.000004447321],"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":[0.00013272045,0.0009935303,0.0019046098,0.0028885799,0.0008986376,0.00020234914,0.0017224567,0.35243216,0.00007173169,0.10647696,0.002225244,0.530051],"study_design_scores_gemma":[0.00044748848,0.00005412007,0.0006221823,0.00025568844,0.0001156038,0.00008434016,0.00013005997,0.13870764,0.00005382785,0.85924375,0.000059138074,0.00022618617],"about_ca_topic_score_codex":0.0000026733728,"about_ca_topic_score_gemma":6.933358e-7,"teacher_disagreement_score":0.7527668,"about_ca_system_score_codex":0.00020847029,"about_ca_system_score_gemma":0.00022806818,"threshold_uncertainty_score":0.9529044},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8966942,0.0046674763,0.022440827,0.006567995,0.0049425885,0.0007549901,0.004509904,0.00014391239,0.059278127],"genre_scores_gemma":[0.9894688,0.0015357081,0.0048430357,0.0017738637,0.0014366221,0.000019779107,0.00024539974,0.00013363507,0.00054314826],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99572074,0.000044585526,0.0020465509,0.0011066893,0.00009599048,0.0009854402],"domain_scores_gemma":[0.99567956,0.00009059206,0.0026092215,0.000781178,0.000036553487,0.00080292014],"candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0012098813,0.0007044359,0.0016722656,0.0024279696,0.00037738026,0.0012211951,0.0012752943,0.00037726894,0.0034766095],"category_scores_gemma":[0.00018725585,0.00079824706,0.00051337865,0.0006344238,0.00011196753,0.00067595625,0.00066032185,0.0024697352,0.0030139599],"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":[0.00038837787,0.00046795886,0.84024435,0.00071247295,0.004806387,0.00043424018,0.003116688,0.05355101,0.0000050925373,0.049827773,0.03788101,0.008564668],"study_design_scores_gemma":[0.006440109,0.0009115742,0.17180777,0.0003298324,0.0001754179,0.0013187779,0.00023738977,0.14614393,0.000024775607,0.28731903,0.38077956,0.0045118444],"about_ca_topic_score_codex":0.00022410376,"about_ca_topic_score_gemma":0.000007633945,"teacher_disagreement_score":0.6684365,"about_ca_system_score_codex":0.000824474,"about_ca_system_score_gemma":0.00012402816,"threshold_uncertainty_score":0.9998316},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010454594,0.005905864,0.96014386,0.0010636445,0.004168988,0.00063992525,0.002240425,0.00003526961,0.015347421],"genre_scores_gemma":[0.98360467,0.0026482763,0.010282001,0.00097399723,0.0013275563,0.00012108415,0.0001480982,0.00006700571,0.00082730514],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968022,0.000020502095,0.0017103698,0.0006547888,0.000108486114,0.00070361304],"domain_scores_gemma":[0.9962538,0.00094110565,0.0018253325,0.00051965495,0.00021308102,0.00024700884],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0028506427,0.0004579726,0.00084823725,0.0014495893,0.00068757765,0.001027811,0.0010589936,0.00046765324,0.0005664536],"category_scores_gemma":[0.0014737346,0.00042598764,0.00065032684,0.00044562042,0.00022875603,0.0004167125,0.0003761946,0.0013799975,0.000087391025],"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":[0.000065155,0.00018316938,0.008057788,0.00014306423,0.00036424783,0.000005803361,0.00015467545,0.11406012,7.9728306e-7,0.85965455,0.0152222775,0.0020883526],"study_design_scores_gemma":[0.00052512647,0.00009071291,0.016824653,0.000029280063,0.000029319111,0.000013089714,0.000030895084,0.2610432,0.0000062600443,0.70389116,0.017039513,0.0004768036],"about_ca_topic_score_codex":0.000034736808,"about_ca_topic_score_gemma":0.000017505934,"teacher_disagreement_score":0.9731501,"about_ca_system_score_codex":0.00046190404,"about_ca_system_score_gemma":0.0003046191,"threshold_uncertainty_score":0.9998192},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08101704,0.0006089149,0.91215676,0.0005399733,0.00052243844,0.0001035588,0.0000014975031,0.000088119574,0.004961724],"genre_scores_gemma":[0.9902685,0.00017708482,0.008691745,0.00007800303,0.0005274363,0.0000031459056,0.000003857215,0.000016322776,0.00023387768],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994477,0.000016556158,0.00021054788,0.000058346257,0.000100209756,0.00016663184],"domain_scores_gemma":[0.9997433,0.00003317139,0.000062405976,0.00008234544,0.000029516426,0.000049302977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023374114,0.00008471194,0.000080414655,0.00034355745,0.00013371317,0.00023551505,0.00013391716,0.00002726697,0.00023626084],"category_scores_gemma":[0.000018510907,0.00006589368,0.0000470463,0.00029831304,0.00001602495,0.00037962827,0.00002042629,0.00014683188,0.00015267933],"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":[0.000003764715,0.0000058017763,0.00035179977,0.000002623349,0.000038772963,0.0000018665374,0.00027358226,0.9512341,0.0000034365587,0.00023586501,0.0014818849,0.04636651],"study_design_scores_gemma":[0.0001811305,0.000022706281,0.0015124313,0.0000035570868,0.00001870766,0.000021557014,0.00006646435,0.9764381,0.00015461941,0.0010647131,0.020423148,0.00009285953],"about_ca_topic_score_codex":9.95324e-7,"about_ca_topic_score_gemma":0.000004086236,"teacher_disagreement_score":0.9092515,"about_ca_system_score_codex":0.00011637084,"about_ca_system_score_gemma":0.000004261508,"threshold_uncertainty_score":0.26870662},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038805656,0.00031185805,0.8853789,0.00021021128,0.00037156805,0.00029238508,0.000019560666,0.000035168043,0.07457469],"genre_scores_gemma":[0.9814376,0.00009410428,0.016534846,0.00009982939,0.0012916956,0.00005182159,0.000013903957,0.000033070766,0.00044312287],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99803877,0.00008302589,0.0006707445,0.0004140733,0.00027122718,0.00052213133],"domain_scores_gemma":[0.99787885,0.00018498994,0.0006208861,0.0007841307,0.00014713692,0.0003839779],"candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0010872663,0.00028904926,0.0006816266,0.0011323099,0.001084714,0.0012510443,0.0011144114,0.000078165394,0.0009293877],"category_scores_gemma":[0.000070335474,0.00027246133,0.00067322917,0.0005242527,0.000043867425,0.0006884411,0.00030184735,0.0005542416,0.0000334989],"study_design_candidate":"design_other","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":[0.0020543218,0.0018244261,0.06788259,0.00003867171,0.0041314107,0.000039577786,0.002322022,0.031007236,0.00020963202,0.13010892,0.110621296,0.6497599],"study_design_scores_gemma":[0.04552283,0.00083311344,0.008851805,0.00013682041,0.0012739251,0.00012913726,0.0014344171,0.2226943,0.0020798738,0.508286,0.20456097,0.0041968115],"about_ca_topic_score_codex":0.00016819985,"about_ca_topic_score_gemma":0.0000053590215,"teacher_disagreement_score":0.94263196,"about_ca_system_score_codex":0.000052893705,"about_ca_system_score_gemma":0.00005893723,"threshold_uncertainty_score":0.9999839},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96696484,0.00017645952,0.009488443,0.001215025,0.005522073,0.00023084898,0.0005962771,0.000006685275,0.01579937],"genre_scores_gemma":[0.99816346,0.00029149395,0.0007996644,0.00006556235,0.00043004667,0.000003559498,0.00003682338,0.000006591296,0.00020279903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99747366,0.00056285405,0.00079960615,0.00019281951,0.00075890654,0.00021214336],"domain_scores_gemma":[0.9970682,0.00042303881,0.0013725671,0.0003917298,0.00064407766,0.00010037597],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0033343711,0.00013241633,0.00035394978,0.00034027622,0.00035640437,0.00016316003,0.0008148274,0.00022047822,0.0011225765],"category_scores_gemma":[0.002069573,0.000105570136,0.00037132535,0.0006083381,0.00013769869,0.00014273399,0.0004345269,0.0008270652,0.0000011723151],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004678023,0.0018164265,0.5266208,0.00023713104,0.00062172837,0.000007843802,0.008022045,0.01462989,0.000061728424,0.44215015,0.0022280174,0.003557427],"study_design_scores_gemma":[0.00039261268,0.000049603586,0.96595925,0.00010930928,0.000040957028,0.0000017810346,0.0004612885,0.0009537722,0.000059166923,0.030767387,0.0010622438,0.00014260231],"about_ca_topic_score_codex":0.00072242937,"about_ca_topic_score_gemma":0.00012505846,"teacher_disagreement_score":0.43933845,"about_ca_system_score_codex":0.0007595657,"about_ca_system_score_gemma":0.001387216,"threshold_uncertainty_score":0.99979055},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5572631,0.00046358604,0.43702087,0.00047885766,0.00009405726,0.0004366663,0.000007012045,0.0001677626,0.0040681115],"genre_scores_gemma":[0.92291856,0.0005479452,0.07619563,0.00011456061,0.00012332031,0.000029297551,0.0000013696911,0.000033224194,0.000036124766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99889165,0.0000667465,0.00039015946,0.00022030824,0.00015232613,0.00027878885],"domain_scores_gemma":[0.9987758,0.000504493,0.00023532707,0.0001779404,0.000061977255,0.00024446886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001839882,0.00019049009,0.00033088666,0.00068418833,0.00011807531,0.00007781029,0.00016810853,0.000062114545,0.000047407906],"category_scores_gemma":[0.00030447074,0.00014926979,0.00007713507,0.0011015936,0.000024406392,0.00036706007,0.000053749613,0.00030302088,0.0000130389935],"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":[0.0011538363,0.004776478,0.044802155,0.0005066234,0.0010449642,0.0067976983,0.011513896,0.37970763,0.0024778794,0.26694024,0.0031134929,0.2771651],"study_design_scores_gemma":[0.0058847596,0.006743892,0.00084197737,0.00021337553,0.00013966199,0.0012866015,0.00024797738,0.050046198,0.012335587,0.9200074,0.0012621388,0.0009904072],"about_ca_topic_score_codex":0.0000136650115,"about_ca_topic_score_gemma":0.00002984968,"teacher_disagreement_score":0.6530672,"about_ca_system_score_codex":0.0005576763,"about_ca_system_score_gemma":0.00006527181,"threshold_uncertainty_score":0.60870457},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9129895,0.0016093326,0.08250819,0.00009561716,0.0005360172,0.00008536202,0.000045855668,0.00002354983,0.0021065832],"genre_scores_gemma":[0.9673582,0.00027157587,0.03193307,0.0000774448,0.00020509952,0.0000026201726,0.0000040996147,0.000033921766,0.00011399773],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99801785,0.000027948565,0.0009281267,0.0004996122,0.000080939455,0.00044550115],"domain_scores_gemma":[0.9985278,0.00012835501,0.0006711418,0.0002631171,0.0001734807,0.00023607558],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007815891,0.00020994818,0.00047129125,0.0009188131,0.00072029856,0.0006671301,0.00015648968,0.0001206934,0.00012112518],"category_scores_gemma":[0.0012110613,0.0002489223,0.00009861567,0.0015723531,0.000063904365,0.0008366697,0.00013085417,0.0005088849,0.000019370369],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021060565,0.00010026811,0.98400056,0.000038744074,0.00008649356,0.000052117062,0.00014527564,0.0024423578,0.00016377006,0.008287626,0.000029855635,0.0046318406],"study_design_scores_gemma":[0.0020725222,0.00017864029,0.7210591,0.0001325228,0.00005003392,0.0010276106,0.00024165734,0.24803023,0.00017402617,0.023823358,0.0024891433,0.0007211511],"about_ca_topic_score_codex":0.00012248347,"about_ca_topic_score_gemma":0.000013466278,"teacher_disagreement_score":0.26294148,"about_ca_system_score_codex":0.00030252087,"about_ca_system_score_gemma":0.00012461227,"threshold_uncertainty_score":0.9999963},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98792374,0.0025039173,0.000710525,0.0007597454,0.00087890466,0.00009131295,0.00018609532,0.000007009561,0.0069387406],"genre_scores_gemma":[0.99795383,0.00032366122,0.00047631076,0.0005965172,0.00030146653,0.0000042884903,0.000012072945,0.00002306132,0.0003088168],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99740785,0.000082803206,0.0015860535,0.00035252373,0.00007536528,0.0004953824],"domain_scores_gemma":[0.99796546,0.00048682396,0.00093713164,0.00043545652,0.00003840715,0.00013673777],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031221155,0.00019879674,0.00065626245,0.0010009474,0.00022627327,0.00028293213,0.0005095031,0.00013925541,0.0019167248],"category_scores_gemma":[0.0005747264,0.00019437482,0.00025992637,0.0008143334,0.000074963486,0.0005082202,0.00010468698,0.0006658981,0.0002161022],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070984905,0.00049824594,0.9001339,0.00005136578,0.00028306583,0.0002153497,0.0020330572,0.059422042,0.000040335664,0.02495615,0.0005083157,0.011787164],"study_design_scores_gemma":[0.002847592,0.00019861864,0.87953126,0.000037534173,0.000019811132,0.0017403667,0.0004444855,0.013057501,0.0010567758,0.09640793,0.0040602265,0.0005978834],"about_ca_topic_score_codex":0.0006047059,"about_ca_topic_score_gemma":0.00010199922,"teacher_disagreement_score":0.071451776,"about_ca_system_score_codex":0.00021938345,"about_ca_system_score_gemma":0.0000522441,"threshold_uncertainty_score":0.99899566},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37831756,0.00017541666,0.62043136,0.00014055385,0.00012481502,0.00031740766,0.000014507691,0.00010152048,0.00037686416],"genre_scores_gemma":[0.90537363,0.00010844798,0.094165266,0.000097376425,0.000038832768,0.0001091021,0.0000072253365,0.000026012238,0.00007410416],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989623,0.000118245625,0.0003072065,0.00021121389,0.00016130897,0.00023972205],"domain_scores_gemma":[0.99630606,0.0030418832,0.00029014313,0.00019653195,0.00003322339,0.0001321684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036950503,0.0002117556,0.00029336798,0.00086991116,0.0004503396,0.00011800716,0.000108145956,0.000041351886,0.00018373788],"category_scores_gemma":[0.0005367568,0.00017731109,0.00007819788,0.0004528181,0.00002854603,0.0001692468,0.00003267888,0.00020662615,0.000006646953],"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":[0.00018912011,0.0022179023,0.0069119786,0.00007944213,0.00042105702,0.000102482234,0.00090179866,0.10467209,0.00059713697,0.1264485,0.00020540704,0.7572531],"study_design_scores_gemma":[0.003498095,0.0126525285,0.0026527923,0.00007432819,0.00020515075,0.00019084841,0.0002660397,0.04647751,0.013178654,0.91903967,0.0010644835,0.0006999297],"about_ca_topic_score_codex":0.000005896853,"about_ca_topic_score_gemma":0.0000026255889,"teacher_disagreement_score":0.79259115,"about_ca_system_score_codex":0.0018958749,"about_ca_system_score_gemma":0.00012312211,"threshold_uncertainty_score":0.72305363},"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":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9947058,0.0006830983,0.0024105392,0.00029563272,0.0011009151,0.00046547578,0.000010125006,0.00005323694,0.00027515314],"genre_scores_gemma":[0.9987431,0.000016432565,0.00034276085,0.00027663508,0.00023176231,0.00007329517,0.000050714272,0.00004023786,0.00022504764],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99876475,0.0000302929,0.0003180233,0.0003000314,0.00021243593,0.00037447963],"domain_scores_gemma":[0.9990541,0.00014138108,0.00040490873,0.00019960599,0.0001702524,0.000029756931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077393075,0.00019122956,0.00027041894,0.00110353,0.00090492086,0.00052699115,0.00032743742,0.000028026048,0.00032946758],"category_scores_gemma":[0.00020971343,0.0001730737,0.00011323843,0.0015503105,0.000021101036,0.0006275177,0.00021783737,0.000321215,0.000010545624],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000374163,0.0004038458,0.9532713,0.0004314625,0.00025906423,0.000060177674,0.000041091796,0.000824059,0.0006272602,0.00014386086,0.0022979556,0.04126571],"study_design_scores_gemma":[0.003383047,0.00015999834,0.9515442,0.000028000166,0.00039843586,0.00012091041,0.00012311444,0.008449754,0.00012450301,0.0004116956,0.03465525,0.00060104934],"about_ca_topic_score_codex":0.000015389041,"about_ca_topic_score_gemma":0.000036063826,"teacher_disagreement_score":0.04066466,"about_ca_system_score_codex":0.000117685246,"about_ca_system_score_gemma":0.00004304987,"threshold_uncertainty_score":0.70577407},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90018445,0.0017633364,0.08664586,0.00036517382,0.0011025317,0.00017651878,0.00089252146,0.000027230473,0.008842381],"genre_scores_gemma":[0.99760675,0.0003377706,0.00085189525,0.00036317285,0.00017471689,0.000015939037,0.0001249661,0.00002707868,0.0004977092],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974484,0.000085213534,0.0014170123,0.0004726499,0.00018056319,0.0003961804],"domain_scores_gemma":[0.9971172,0.00037550076,0.0017096065,0.0004799627,0.000108485634,0.00020919685],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0016275445,0.00023663357,0.00077574886,0.004892174,0.00062588794,0.00022320688,0.0006704815,0.00008169753,0.0031972055],"category_scores_gemma":[0.00048585006,0.0002794249,0.0003292871,0.004366224,0.00005618439,0.0006841997,0.0002302449,0.0007307864,0.00014877011],"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":[0.000028688268,0.00033809646,0.35915446,0.000010617,0.0002357086,0.000010830026,0.0002943172,0.46321058,0.0000048891807,0.17405106,0.00090733834,0.0017534147],"study_design_scores_gemma":[0.0026028946,0.0007802554,0.17924319,0.000020794178,0.00014960294,0.00013210258,0.00075039745,0.27856973,0.00010155602,0.5306914,0.0057629417,0.0011951454],"about_ca_topic_score_codex":0.0008387198,"about_ca_topic_score_gemma":0.000073071686,"teacher_disagreement_score":0.35664034,"about_ca_system_score_codex":0.00039738516,"about_ca_system_score_gemma":0.000087129796,"threshold_uncertainty_score":0.9999658},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02069087,0.000050401308,0.9770028,0.0001601877,0.00030538198,0.000092854294,0.00034307613,0.000040843228,0.0013135851],"genre_scores_gemma":[0.15099248,0.000032544114,0.8483832,0.000075618336,0.0001698619,0.0000047380995,0.000113212474,0.00002074812,0.00020757678],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987354,0.00017542101,0.00041980756,0.00022667149,0.0002104637,0.00023220219],"domain_scores_gemma":[0.9899108,0.009176449,0.00027922753,0.00029691632,0.00018043134,0.00015617353],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0034271467,0.0001119801,0.00024114341,0.00043419114,0.0002908381,0.00021951237,0.000253166,0.00002653222,0.00067451235],"category_scores_gemma":[0.017148105,0.00009174394,0.00001580641,0.001307776,0.000066043205,0.00022256355,0.00015825518,0.00022540687,0.0000467431],"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":[0.00013353996,0.00041795184,0.26530814,0.00027088387,0.0007368983,0.000084852494,0.00043500715,0.0024447846,0.00005286268,0.3015065,0.10763975,0.32096884],"study_design_scores_gemma":[0.0008099875,0.000115080074,0.2045116,0.00005286793,0.000039039074,0.00008286285,0.00010699043,0.69152796,0.0000015585501,0.10191933,0.0006232056,0.00020954738],"about_ca_topic_score_codex":0.00002096118,"about_ca_topic_score_gemma":0.000031246258,"teacher_disagreement_score":0.68908316,"about_ca_system_score_codex":0.0000407304,"about_ca_system_score_gemma":0.00006768348,"threshold_uncertainty_score":0.9911309},"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":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005570161,0.00022981704,0.99733394,0.00019625123,0.0006715706,0.0001870017,0.000021003887,0.000055567896,0.0007478144],"genre_scores_gemma":[0.0006490853,0.00013720024,0.99637127,0.000052173975,0.00066336157,0.000013449229,0.000004860544,0.000028584018,0.002079991],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99885947,0.000090951304,0.0004919483,0.00016164797,0.00012786496,0.00026811703],"domain_scores_gemma":[0.9923185,0.006979424,0.00032145646,0.00009909674,0.00009904502,0.00018249238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026732206,0.000104541396,0.0002726045,0.00065076357,0.000242737,0.00012961736,0.00011790839,0.00006430446,0.00023208153],"category_scores_gemma":[0.007811434,0.000093931085,0.000131313,0.0008872333,0.000006317444,0.0002017285,0.000028695355,0.00018633848,0.000022672415],"study_design_candidate":"design_other","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":[0.000081613274,0.0000242227,0.000089143825,0.000066805755,0.00008970963,0.0000106015605,0.00035948792,0.024442622,0.000113152775,0.14556128,0.040254842,0.7889065],"study_design_scores_gemma":[0.0011559774,0.000052753894,0.00002553731,0.000010077969,0.000036184454,0.000032440123,0.000054917917,0.37474582,0.00005806263,0.6190863,0.004641827,0.000100084755],"about_ca_topic_score_codex":0.0000017227615,"about_ca_topic_score_gemma":9.906068e-7,"teacher_disagreement_score":0.78880644,"about_ca_system_score_codex":0.000056635396,"about_ca_system_score_gemma":0.000065794266,"threshold_uncertainty_score":0.935158},"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":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11073608,0.03934212,0.0009131036,0.08695757,0.0028659718,0.00016549787,0.000029439503,0.0000821611,0.75890803],"genre_scores_gemma":[0.98575425,0.0035157674,0.00008294118,0.0009184655,0.0014940012,0.000001574408,2.4466618e-7,0.000007066364,0.008225705],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99918324,0.00005664205,0.00018417208,0.00009924076,0.00019289047,0.00028380044],"domain_scores_gemma":[0.99885696,0.0008120363,0.000043991742,0.0000587992,0.000056933364,0.0001712704],"candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0015470558,0.00006491722,0.000119338074,0.00018873297,0.0006528787,0.001080466,0.00022485007,0.00005008321,0.00027545073],"category_scores_gemma":[0.001082646,0.00004325912,0.00007852486,0.0005543407,0.0004890562,0.0003870353,0.00004372899,0.00036603102,0.000051387833],"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":[0.000006197858,0.000004956095,0.0018759721,0.0000061956775,0.000021042006,0.000015035687,0.002251631,0.0000012697114,1.5624717e-7,0.9901192,0.0026164462,0.0030818773],"study_design_scores_gemma":[0.00038660763,0.000019322257,0.003812855,0.000022531973,0.000022997932,0.000049929837,0.0011214794,0.0011328006,0.000005281062,0.43890625,0.554402,0.000117972035],"about_ca_topic_score_codex":0.00026812445,"about_ca_topic_score_gemma":0.00006604374,"teacher_disagreement_score":0.8750182,"about_ca_system_score_codex":0.000077805424,"about_ca_system_score_gemma":0.00018182237,"threshold_uncertainty_score":0.9999565},"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":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013406262,0.0020331207,0.9727626,0.0006522131,0.000709075,0.00019598426,0.00002820727,0.000042814605,0.01016973],"genre_scores_gemma":[0.90913576,0.0012261336,0.088898666,0.00007430481,0.0002633516,0.000020166699,0.0000013625003,0.00003604875,0.00034423266],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984791,0.00013432818,0.00064411,0.00017660139,0.0002052656,0.00036054236],"domain_scores_gemma":[0.9881938,0.011233849,0.00011148231,0.00014823864,0.00017592747,0.00013671865],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0028276641,0.00013042954,0.00024201458,0.0005985356,0.00019053713,0.00071652967,0.00025878943,0.00006011427,0.00021149116],"category_scores_gemma":[0.011799799,0.00008484471,0.00007516865,0.002036352,0.00004549356,0.00014204787,0.00004349753,0.00058212975,0.000044306147],"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":[0.000074830794,0.00037097087,0.0011980362,0.00009503336,0.00011401715,0.0001547818,0.0007908062,0.001061131,0.00007778513,0.7819041,0.009765486,0.20439303],"study_design_scores_gemma":[0.0006799227,0.00012872093,0.0007969167,0.00006154514,0.00002129419,0.00011401911,0.00007644262,0.36266702,0.000055615365,0.63322806,0.0020283633,0.00014207413],"about_ca_topic_score_codex":0.00000322587,"about_ca_topic_score_gemma":0.00001056451,"teacher_disagreement_score":0.8957295,"about_ca_system_score_codex":0.0001677897,"about_ca_system_score_gemma":0.00029684577,"threshold_uncertainty_score":0.9965242},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88948756,0.011257936,0.017049508,0.0004958262,0.0105215395,0.00021929754,0.000015737061,0.0006814655,0.070271105],"genre_scores_gemma":[0.99802655,0.0003310618,0.00006998862,0.000015626656,0.00019600312,0.000003983378,6.4964854e-7,0.000016248534,0.0013399125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943334,0.000016891283,0.00023045982,0.00008333798,0.00009572259,0.00014022074],"domain_scores_gemma":[0.9996804,0.00014903887,0.000018966459,0.000071153874,0.000010675552,0.00006977426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030698848,0.000085196734,0.00012402437,0.0011509883,0.000034539677,0.00029958287,0.000102394624,0.000057817368,0.0005049175],"category_scores_gemma":[0.00014488434,0.00007129886,0.000048120815,0.0007682933,0.000006609361,0.00025642663,0.000008504859,0.0003607462,0.00062714977],"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":[0.00005428532,0.000055601646,0.0055968594,0.00017998173,0.00012681019,0.00038639296,0.00050603756,0.79247123,0.0008340532,0.0031119506,0.024240466,0.17243631],"study_design_scores_gemma":[0.0006837636,0.00021820347,0.0046393992,0.00060132716,0.000008241554,0.00027480503,0.00009264878,0.8778466,0.000497605,0.0024181115,0.11230584,0.0004134536],"about_ca_topic_score_codex":0.0000014176628,"about_ca_topic_score_gemma":0.0000033200472,"teacher_disagreement_score":0.17202286,"about_ca_system_score_codex":0.00017351266,"about_ca_system_score_gemma":0.000015282014,"threshold_uncertainty_score":0.80609506},"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":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5093021,0.027941661,0.08039881,0.016505402,0.004035566,0.0004281852,0.00027949782,0.000045893827,0.3610629],"genre_scores_gemma":[0.9962283,0.0010373244,0.0005518694,0.0012178413,0.00017828449,0.000008175414,0.000012567698,0.000007360184,0.0007582843],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99857724,0.000038665017,0.0008188089,0.00023639321,0.0000367819,0.0002920905],"domain_scores_gemma":[0.99897945,0.00032045873,0.00033872548,0.00028226138,0.000027834016,0.000051287258],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00256845,0.000119577606,0.000352255,0.0024632246,0.00021591158,0.00046495785,0.000659564,0.00007547462,0.0011115571],"category_scores_gemma":[0.0007394016,0.00010338904,0.00016687214,0.0031057938,0.000029894265,0.00036307337,0.00005891879,0.00038752944,0.00041517953],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000085527745,0.00009871417,0.61174536,0.000011244986,0.00012178065,0.000015387403,0.00037950958,0.00036488456,0.0000019687072,0.37482053,0.007281143,0.0051509095],"study_design_scores_gemma":[0.0011425455,0.000060630508,0.34602273,0.000029514329,0.000031499563,0.00005117342,0.0007189702,0.005251706,0.000019924411,0.33350012,0.31279048,0.00038068424],"about_ca_topic_score_codex":0.00022773379,"about_ca_topic_score_gemma":0.00004325428,"teacher_disagreement_score":0.48692623,"about_ca_system_score_codex":0.00014209667,"about_ca_system_score_gemma":0.000032515607,"threshold_uncertainty_score":0.9998016},"labels":[],"label_agreement":null}]}