{"meta":{"query_hash":"794324310b54","filters":{"venue":"Jahrbücher für Nationalökonomie und Statistik"},"cohort_total":16,"direct_labels_cover":0,"predictions_cover":16,"exported":16,"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/794324310b54","api":"https://metacan.xera.ac/api/v1/cohort?venue=Jahrb%C3%BCcher+f%C3%BCr+National%C3%B6konomie+und+Statistik"},"results":[{"id":"W1550404322","doi":"10.1515/jbnst-2010-0105","title":"What Drives Housing Prices Down? Evidence from an International Panel","year":2010,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Economics; Overheating (electricity); Per capita; Consumption (sociology); Urbanization; Interest rate; Population growth; Private consumption; Monetary economics; Population; Economic growth","score_opus":0.059312683755466104,"score_gpt":0.30812784640875235,"score_spread":0.24881516265328624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550404322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9730046,0.0028744352,0.00043618865,0.0016373774,0.00005604283,0.000025159363,0.006779334,0.000012002785,0.0151748825],"genre_scores_gemma":[0.9928108,0.0010219498,0.00010762991,0.0002382399,0.00003417004,0.0000059251292,0.004422126,0.000004949498,0.0013542413],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99954337,0.0001244705,0.000031978103,0.000108658234,0.00008107936,0.00011054146],"domain_scores_gemma":[0.9957688,0.0010886487,0.0016804045,0.000389207,0.0007191433,0.0003538713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011873748,0.0002468487,0.00039242484,0.00073794357,0.0004985048,0.0015560389,0.000429089,0.0005001234,0.0046406914],"category_scores_gemma":[0.0034844442,0.00016165736,0.00050790375,0.002133911,0.00041761526,0.00049539097,0.00043045182,0.00059267215,0.00048687315],"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":[0.00021024705,0.000053803455,0.9839865,0.000069090995,0.0004674407,0.00016217543,0.00040832208,0.00048971205,0.00022195566,0.0011500284,0.0038509364,0.008929749],"study_design_scores_gemma":[0.000012727229,0.000024426505,0.9948415,0.00003320177,0.0002048939,0.000028411385,0.0005305947,0.00036110572,0.00018323689,0.00019311489,0.0035784943,0.000008340093],"about_ca_topic_score_codex":0.26613456,"about_ca_topic_score_gemma":0.29686534,"teacher_disagreement_score":0.26613456,"about_ca_system_score_codex":0.00080789183,"about_ca_system_score_gemma":0.0005840239,"threshold_uncertainty_score":0.529171},"labels":[],"label_agreement":null},{"id":"W2125128933","doi":"10.1515/jbnst-2010-0610","title":"User Costs versus Waiting Services and Depreciation in a Model of Production","year":2010,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Economic theories and models","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":"University of British Columbia","funders":"","keywords":"Depreciation (economics); Economics; Capital (architecture); Production (economics); Capital good; Consumption of fixed capital; Investment (military); Fixed capital; Stock (firearms); Investment goods; Microeconomics; Cost of capital; Monetary economics; Capital formation; Business; Goods and services; Financial capital; Economy; Profit (economics); Engineering","score_opus":0.02833930585372837,"score_gpt":0.2638827821406889,"score_spread":0.2355434762869605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125128933","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32523084,0.0021615701,0.5611761,0.00470385,0.00018737148,0.00017382424,0.0022998191,0.0005044086,0.103562124],"genre_scores_gemma":[0.9436969,0.000937387,0.013793988,0.00013947625,0.00005934929,0.000141869,0.00032904735,0.00008874447,0.040813148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992842,0.000299589,0.000027949956,0.00013614466,0.00007547971,0.00017662255],"domain_scores_gemma":[0.9984364,0.0009716,0.00019048812,0.00013771917,0.000102334336,0.0001614365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010974376,0.00087692915,0.0008426098,0.0007294407,0.0005538701,0.003216189,0.0016172549,0.0017117432,0.011798841],"category_scores_gemma":[0.0032039098,0.00070725975,0.0013072056,0.0010972453,0.0017337913,0.0031908643,0.0010996761,0.001469454,0.0011188671],"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":[0.00013691174,0.00007089948,0.0012942218,0.0000767004,0.000029836518,0.00028542953,0.00020432306,0.6535019,0.00089239364,0.3357185,0.0017263764,0.006062498],"study_design_scores_gemma":[0.000066921806,0.000104338906,0.0011942607,0.00004501444,0.00004074495,0.00014356224,0.00016230649,0.8415117,0.0003279763,0.15065941,0.005699774,0.000044009692],"about_ca_topic_score_codex":0.009111269,"about_ca_topic_score_gemma":0.004287461,"teacher_disagreement_score":0.011798841,"about_ca_system_score_codex":0.0028400982,"about_ca_system_score_gemma":0.001260242,"threshold_uncertainty_score":0.03947103},"labels":[],"label_agreement":null},{"id":"W2131514580","doi":"10.1515/jbnst-2010-0606","title":"Notes on Unit Value Index Bias","year":2010,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":13,"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":"Value (mathematics); Index (typography); Unit (ring theory); Mathematics; Order (exchange); Statistics; Price index; Econometrics; Unit price; Economics; Computer science; Microeconomics","score_opus":0.04903875397102524,"score_gpt":0.3108793071935005,"score_spread":0.26184055322247524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131514580","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08048455,0.038953267,0.43242124,0.17666683,0.021446707,0.00036233864,0.0034024676,0.0015893654,0.24467327],"genre_scores_gemma":[0.8171635,0.010417581,0.08202698,0.037029676,0.022158895,0.00043384236,0.000860506,0.0012026579,0.028706335],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9627321,0.01584209,0.002447914,0.004704448,0.013368045,0.0009055685],"domain_scores_gemma":[0.7643168,0.17343011,0.013233188,0.030787408,0.017504979,0.00072757236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.031166052,0.00063719065,0.0016071575,0.003294891,0.0014517115,0.00398638,0.0029313553,0.002161318,0.014799591],"category_scores_gemma":[0.22176597,0.0003665233,0.0012467068,0.005397459,0.007189879,0.0067872573,0.0030727088,0.0058018332,0.0027368471],"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":[0.00028062923,0.00004240659,0.010266126,0.00041802129,0.00017720411,0.00031748367,0.00095788913,0.0018415482,0.00062839536,0.80868876,0.06747436,0.10890723],"study_design_scores_gemma":[0.00004819896,0.00009056701,0.006886707,0.00036597514,0.00007239207,0.0003634273,0.0003014674,0.005584503,0.0030401824,0.9007863,0.08236375,0.0000966796],"about_ca_topic_score_codex":0.0025216928,"about_ca_topic_score_gemma":0.0009809396,"teacher_disagreement_score":0.031166052,"about_ca_system_score_codex":0.0032166827,"about_ca_system_score_gemma":0.0008532343,"threshold_uncertainty_score":0.16482377},"labels":[],"label_agreement":null},{"id":"W2223165180","doi":"10.1515/jbnst-2015-0608","title":"Growth Regressions, Principal Components Augmented Regressions and Frequentist Model Averaging","year":2015,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Frequentist inference; Econometrics; Principal component analysis; Contrast (vision); Statistics; Mathematics; Set (abstract data type); Economics; Computer science; Bayesian probability; Bayesian inference; Artificial intelligence","score_opus":0.17779684917293226,"score_gpt":0.3128452227634579,"score_spread":0.13504837359052563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2223165180","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09940513,0.0013366449,0.89366394,0.0008605098,0.0001225172,0.000050077382,0.00065225025,0.00089460216,0.0030142176],"genre_scores_gemma":[0.8724172,0.0008809763,0.12148092,0.00014686187,0.0003777274,0.00008574151,0.0011718072,0.00021334537,0.003225374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948487,0.0035187525,0.00019404711,0.00076310534,0.0004915508,0.00018384929],"domain_scores_gemma":[0.97962624,0.013453491,0.0024913433,0.0031020292,0.0011292897,0.00019761795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007190067,0.0007852064,0.0015829997,0.0015120138,0.00056519517,0.0016829089,0.0010924876,0.00066272967,0.0019067108],"category_scores_gemma":[0.029670903,0.00043237236,0.0013145385,0.0017854382,0.00082052103,0.0017003809,0.0012174862,0.0017131103,0.00045731594],"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":[0.00015993779,0.00008236135,0.017412556,0.00015079413,0.00089571596,0.00023866961,0.00023080733,0.74264306,0.00092141127,0.108059086,0.004479729,0.12472583],"study_design_scores_gemma":[0.00000823138,0.000037993406,0.0047505624,0.000016304755,0.00005851673,0.00003181278,0.000030719362,0.91146857,0.0003039625,0.08111314,0.0021534895,0.000026731803],"about_ca_topic_score_codex":0.013410648,"about_ca_topic_score_gemma":0.011993391,"teacher_disagreement_score":0.013410648,"about_ca_system_score_codex":0.0007157128,"about_ca_system_score_gemma":0.0009948906,"threshold_uncertainty_score":0.03802514},"labels":[],"label_agreement":null},{"id":"W2330069606","doi":"10.1515/jbnst-2014-2-303","title":"The Routinization of Creativity","year":2014,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Creativity in Education and Neuroscience","field":"Psychology","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Creativity; Knowledge management; Context (archaeology); Feeling; Sociology; Convergent thinking; Psychology; Social psychology; Computer science","score_opus":0.029880391131269956,"score_gpt":0.404481396302064,"score_spread":0.37460100517079403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330069606","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08251454,0.0059767463,0.036053255,0.01450554,0.00032914124,0.00007897295,0.000119263335,0.0002135809,0.86020887],"genre_scores_gemma":[0.9654929,0.0013577339,0.0049019284,0.0004600322,0.00022853221,0.0000643671,0.000059626258,0.00010926858,0.02732555],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99355656,0.0037569876,0.00022262853,0.0008962113,0.0010532362,0.00051440013],"domain_scores_gemma":[0.99232423,0.002919462,0.0007754462,0.0027115077,0.00086697895,0.00040233455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003431045,0.00038404413,0.00037611887,0.001676481,0.0036243827,0.010911371,0.0010962783,0.0012732338,0.0070103914],"category_scores_gemma":[0.0073830825,0.0002199083,0.00047338498,0.0016162413,0.03233584,0.0066601746,0.006178647,0.0024321354,0.000805677],"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":[0.000012812456,0.0000057906773,0.00044677855,0.000052001415,0.0000059959666,0.00016232452,0.015423558,0.00022932111,0.000313342,0.970184,0.0011517329,0.012012244],"study_design_scores_gemma":[0.000016672486,0.00002761335,0.0015791669,0.00019843897,0.000011700918,0.0004158113,0.013285072,0.00085446856,0.00080464646,0.767615,0.21516968,0.00002177069],"about_ca_topic_score_codex":0.0026995402,"about_ca_topic_score_gemma":0.0020311861,"teacher_disagreement_score":0.010911371,"about_ca_system_score_codex":0.0056558843,"about_ca_system_score_gemma":0.003152816,"threshold_uncertainty_score":0.041036487},"labels":[],"label_agreement":null},{"id":"W2343000160","doi":"10.1515/jbnst-2000-0405","title":"Blood, Sweat, and Tears: The Rise and Decline of the East German Economy, 1949–1988 / Blut, Schweiß, Tränen: Aufstieg und Niedergang der ostdeutschen Wirtschaft, 1949–1988","year":2000,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"European history and politics","field":"Social Sciences","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","funders":"","keywords":"German; Economics; Autocracy; German economy; Period (music); Institutional change; Economy; Political science; Economic history; Democracy; Geography; Philosophy; Law; Politics","score_opus":0.018233447572585604,"score_gpt":0.3072490417409238,"score_spread":0.2890155941683382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2343000160","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99383765,0.0011814826,0.000028656468,0.00091004383,0.000007611137,0.000002577341,0.0005197027,0.000002333284,0.0035100058],"genre_scores_gemma":[0.99767226,0.0009234732,0.000023845412,0.000056211877,0.000011018779,0.0000016623387,0.00028178404,0.000001725367,0.0010279084],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99988043,0.000011868024,0.000012954098,0.000015403733,0.000024916202,0.00005437618],"domain_scores_gemma":[0.99945205,0.00007028428,0.00030016073,0.000025476653,0.00009469029,0.000057317768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032793896,0.000100921076,0.00015525971,0.0015495577,0.0004767626,0.001067042,0.00014841219,0.00026093322,0.0016062275],"category_scores_gemma":[0.001047952,0.000095334784,0.0000827747,0.0023334324,0.0007950145,0.0009285693,0.00057458406,0.00039934082,0.00019252888],"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":[0.0005422574,0.00009247859,0.87246585,0.0002960735,0.00011318759,0.0010784754,0.017677842,0.001588372,0.0017315099,0.021036087,0.016030958,0.06734699],"study_design_scores_gemma":[0.0000034000395,0.000018208919,0.98027587,0.000041552554,0.000012726806,0.00007696253,0.0036464792,0.00013920014,0.0002457496,0.00047223226,0.01506066,0.000007009199],"about_ca_topic_score_codex":0.03954019,"about_ca_topic_score_gemma":0.06672005,"teacher_disagreement_score":0.03954019,"about_ca_system_score_codex":0.0017332012,"about_ca_system_score_gemma":0.00046542488,"threshold_uncertainty_score":0.078620076},"labels":[],"label_agreement":null},{"id":"W2526660935","doi":"10.1515/jbnst-2004-1-217","title":"German Register Data for Regression Estimation in Survey Sampling – A Study on the German Microcensus Respecting for Data Protection / Stichproben-Regressionsschätzungen im deutschen Mikrozensus mit Registerdaten unter Berücksichtigung des Datenschutzes","year":2004,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"German; Estimator; Estimation; Matching (statistics); Econometrics; Statistics; Sampling (signal processing); Sample (material); Population; Identification (biology); Computer science; Mathematics; Demography; Geography; Economics; Sociology","score_opus":0.6249061368714397,"score_gpt":0.5663620139468306,"score_spread":0.05854412292460909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526660935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":"methods","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":"methods","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89375716,0.0098202145,0.054791827,0.006498204,0.0001877291,0.0012426552,0.0029135926,0.00009588467,0.030692808],"genre_scores_gemma":[0.9838283,0.0012568799,0.010940956,0.0003081692,0.000055938384,0.00045885812,0.0011779374,0.000022276061,0.0019506708],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.88888144,0.09686034,0.0032857386,0.0024925573,0.007356908,0.0011230455],"domain_scores_gemma":[0.83191466,0.135868,0.011753439,0.011779365,0.008134559,0.00054999854],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.047638163,0.00022375383,0.00060947245,0.0027740784,0.0008858872,0.0017550003,0.0011534118,0.0006861021,0.004961506],"category_scores_gemma":[0.12094715,0.000315258,0.0005130033,0.007934273,0.0014079034,0.0013346139,0.0011314454,0.00058277056,0.00057280064],"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":[0.0009305993,0.00029712965,0.5044785,0.0011529102,0.0006468671,0.0006375514,0.0068300567,0.012199325,0.0006531375,0.19209018,0.015341577,0.26474217],"study_design_scores_gemma":[0.00038199357,0.0013282395,0.82083476,0.0015120766,0.00083239947,0.00068715285,0.013114718,0.038892288,0.0026044433,0.025984526,0.09368486,0.00014259513],"about_ca_topic_score_codex":0.034478255,"about_ca_topic_score_gemma":0.026818292,"teacher_disagreement_score":0.9523618,"about_ca_system_score_codex":0.002765604,"about_ca_system_score_gemma":0.0029553205,"threshold_uncertainty_score":0.2519377},"labels":[],"label_agreement":null},{"id":"W2858294449","doi":"10.1515/jbnst-2018-0024","title":"Tail Risk in a Retail Payments System","year":2018,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Carleton University; Lakehead University","funders":"","keywords":"Default; Collateral; Payment; Econometrics; Extreme value theory; Maxima; Actuarial science; Position (finance); Economics; Credit risk; Cover (algebra); Business; Statistics; Finance; Mathematics","score_opus":0.030733440422640663,"score_gpt":0.26944505344312475,"score_spread":0.23871161302048408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2858294449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.891388,0.00023313404,0.09926449,0.00092117797,0.000020731308,0.000121505946,0.00039733644,0.0003218551,0.0073318426],"genre_scores_gemma":[0.996049,0.00004394704,0.0021787484,0.000019047979,0.000009306921,0.000012911302,0.0000680146,0.000008499851,0.0016105882],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99826765,0.0005473243,0.000072928524,0.000291949,0.00030355545,0.0005165041],"domain_scores_gemma":[0.98979,0.0048384005,0.0023376031,0.00081963744,0.001428199,0.00078611233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003646453,0.00041109734,0.00097067625,0.00092768716,0.00094157964,0.001995894,0.0013528913,0.0012037433,0.0041617597],"category_scores_gemma":[0.017086655,0.0003219699,0.0005368174,0.0007945823,0.0021837885,0.0018407345,0.0012213785,0.0013519151,0.00030327684],"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":[0.0005536129,0.00020633626,0.04671568,0.00009480408,0.000084473904,0.00078774354,0.0005899108,0.7518513,0.0044377544,0.16125889,0.0040880325,0.029331459],"study_design_scores_gemma":[0.000048952745,0.00014364993,0.013942913,0.000021907454,0.000037796053,0.00014455614,0.00020723105,0.9400807,0.0007932297,0.043535296,0.001000678,0.000043133834],"about_ca_topic_score_codex":0.07435462,"about_ca_topic_score_gemma":0.034217354,"teacher_disagreement_score":0.07435462,"about_ca_system_score_codex":0.0034562042,"about_ca_system_score_gemma":0.00200528,"threshold_uncertainty_score":0.14784366},"labels":[],"label_agreement":null},{"id":"W2884732929","doi":"10.1515/jbnst-2018-0015","title":"Studying Firm Growth Distributions with a Large Administrative Employment Database","year":2018,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Firm Innovation and 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":true,"ca_institutions":"Lakehead University; Statistics Canada","funders":"","keywords":"Distribution (mathematics); Annual growth %; Economics; Growth rate; Demographic economics; Econometrics; Labour economics; Database; Agricultural economics; Mathematics","score_opus":0.0747634164078612,"score_gpt":0.32655405659159,"score_spread":0.25179064018372876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884732929","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9177589,0.0003915268,0.0027212708,0.00030585335,0.000010042192,0.000072786825,0.07436289,0.00016615071,0.004210526],"genre_scores_gemma":[0.9305877,0.00024508973,0.0028807675,0.00004598078,0.000017022288,0.000045698896,0.0650816,0.000016100032,0.0010801147],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984876,0.00024012572,0.000095655254,0.00023071092,0.000701851,0.00024401511],"domain_scores_gemma":[0.98919755,0.0030983975,0.0018982558,0.0010962128,0.004060661,0.0006489391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016125168,0.00018155325,0.00031620348,0.0059372573,0.0008354954,0.0014378293,0.0006604503,0.00027900416,0.001560855],"category_scores_gemma":[0.009864781,0.00016425138,0.00022334608,0.012334497,0.00033229208,0.00047672304,0.00065980916,0.00037477812,0.00051240076],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013252535,0.00013696472,0.9418272,0.000059914488,0.0001236413,0.00016691249,0.00032164785,0.015154442,0.00048883504,0.0017242631,0.012079288,0.027784282],"study_design_scores_gemma":[0.000015659902,0.000022904302,0.95750135,0.000023300365,0.000023098279,0.000071826806,0.0005432962,0.03090776,0.000645386,0.00037193648,0.009852283,0.000021194797],"about_ca_topic_score_codex":0.8666572,"about_ca_topic_score_gemma":0.8507666,"teacher_disagreement_score":0.8666572,"about_ca_system_score_codex":0.0062490418,"about_ca_system_score_gemma":0.005792555,"threshold_uncertainty_score":0.26825613},"labels":[],"label_agreement":null},{"id":"W2889125608","doi":"10.1515/jbnst-2017-0136","title":"Euro Area Growth Signals from Industrial Production: Warnings from a Comparison of Gross Value Added and Production","year":2018,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Production (economics); Industrial production; Gross output; Economics; Quarter (Canadian coin); Value (mathematics); Gross value added; Econometrics; National accounts; Sign (mathematics); Industrial production index; Macroeconomics; Statistics; Mathematics; Geography","score_opus":0.14785034455031656,"score_gpt":0.30268126524738537,"score_spread":0.1548309206970688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889125608","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.884164,0.0090796,0.0083445255,0.017928213,0.0028520764,0.000042702963,0.0058508026,0.00076040067,0.070977755],"genre_scores_gemma":[0.9928975,0.0010826302,0.0011304234,0.0009226616,0.00060535804,0.000016335978,0.0016738893,0.00009051648,0.0015806254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979907,0.0006376802,0.00021241809,0.00022171815,0.00081655016,0.00012087231],"domain_scores_gemma":[0.9855834,0.005822583,0.004698089,0.00084990665,0.0027078118,0.0003381785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00324711,0.0002949937,0.0003619658,0.002097145,0.00020745044,0.0023441336,0.00029159544,0.0010000736,0.0020223516],"category_scores_gemma":[0.018070279,0.00014236885,0.00019928439,0.0029266234,0.0005718834,0.0013727759,0.0010057238,0.0012570363,0.0006174357],"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":[0.0047895727,0.00020958943,0.49299252,0.0009588975,0.0003436917,0.0018401765,0.0027722998,0.016386805,0.010128097,0.057429396,0.11042235,0.30172655],"study_design_scores_gemma":[0.00010847448,0.00051599136,0.83202976,0.0006256245,0.000096046075,0.0005099298,0.0026250025,0.023093076,0.008173468,0.018725533,0.11339968,0.00009731113],"about_ca_topic_score_codex":0.0028795993,"about_ca_topic_score_gemma":0.0014478926,"teacher_disagreement_score":0.00324711,"about_ca_system_score_codex":0.0006283386,"about_ca_system_score_gemma":0.00023680364,"threshold_uncertainty_score":0.017172575},"labels":[],"label_agreement":null},{"id":"W3121340206","doi":"10.1515/jbnst-2012-0404","title":"Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland","year":2012,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nowcasting; Real gross domestic product; Econometrics; Economics; Dynamic factor; Quarter (Canadian coin); Benchmark (surveying); Ranking (information retrieval); Real-time data; Order (exchange); Computer science; Finance; Geography","score_opus":0.5123140591325115,"score_gpt":0.4013558012778985,"score_spread":0.110958257854613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121340206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912982,0.00080589467,0.0016151613,0.0012239134,0.000030638013,0.000012166184,0.00095531467,0.0001207423,0.003938124],"genre_scores_gemma":[0.99869955,0.00025081355,0.00019481438,0.00002024958,0.000029537941,0.0000022371348,0.0006833905,0.000011784653,0.00010753379],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99803776,0.0008837566,0.0001313165,0.00024266113,0.00058532244,0.000119167045],"domain_scores_gemma":[0.95922995,0.027889168,0.0063269245,0.0023352471,0.0035894907,0.00062918896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004611513,0.000428832,0.00025875334,0.0015451103,0.00025454635,0.001989613,0.0004075339,0.0005304741,0.0020864129],"category_scores_gemma":[0.024942618,0.0002016926,0.00048303802,0.0012842905,0.00064695015,0.0014698879,0.0006927846,0.0006049374,0.000552276],"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":[0.0010793873,0.00014750753,0.8774978,0.00026695087,0.00038818648,0.00085616147,0.0013245372,0.049391996,0.0024144202,0.0024274802,0.004157389,0.060048185],"study_design_scores_gemma":[0.000044193304,0.00033270087,0.8967861,0.00019451416,0.00019729187,0.00029457355,0.0011762307,0.09379592,0.002599811,0.0013772687,0.0031079499,0.00009341405],"about_ca_topic_score_codex":0.021104015,"about_ca_topic_score_gemma":0.010728607,"teacher_disagreement_score":0.021104015,"about_ca_system_score_codex":0.000555202,"about_ca_system_score_gemma":0.00059442327,"threshold_uncertainty_score":0.041962326},"labels":[],"label_agreement":null},{"id":"W3192151548","doi":"10.1515/jbnst-2020-0055","title":"Optimal Price Indexes","year":2021,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Economic theories and models","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":"Université de Montréal","funders":"","keywords":"Harmonic mean; Mathematics; Logarithm; Index (typography); Price index; Function (biology); Harmonic; Geometric mean; Explained sum of squares; Base (topology); Least-squares function approximation; Applied mathematics; Mathematical optimization; Statistics; Econometrics; Mathematical analysis; Computer science","score_opus":0.02991244831743492,"score_gpt":0.26928408815436644,"score_spread":0.23937163983693152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3192151548","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08451259,0.00096925563,0.8666981,0.0010911496,0.00026284572,0.00010770492,0.00036201722,0.0002983404,0.045698047],"genre_scores_gemma":[0.80384743,0.0006937442,0.1854833,0.00017472183,0.00034803268,0.00014326737,0.0003789751,0.00024293446,0.008687626],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997996,0.00060737017,0.00012548389,0.00046162528,0.00065703166,0.00015250278],"domain_scores_gemma":[0.9969777,0.0012017745,0.00054138293,0.0003977829,0.0006963477,0.00018512795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002492742,0.00058066036,0.0010945012,0.0017362887,0.00062824966,0.004168296,0.0013371876,0.0014702912,0.006040134],"category_scores_gemma":[0.016280027,0.00037882203,0.0004092496,0.0018875783,0.0018592993,0.0051035797,0.001410112,0.0012093172,0.000847693],"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":[0.00012411502,0.000069583984,0.001598185,0.00016160843,0.000050261144,0.000066551045,0.000101497964,0.11741057,0.0044300924,0.7833454,0.0043753763,0.08826675],"study_design_scores_gemma":[0.00003659918,0.00013015296,0.0014168954,0.00005494303,0.000024724128,0.00008602691,0.00009228442,0.45814413,0.0038951584,0.5264235,0.009656676,0.000038822764],"about_ca_topic_score_codex":0.0005582181,"about_ca_topic_score_gemma":0.00047881092,"teacher_disagreement_score":0.006040134,"about_ca_system_score_codex":0.0016651406,"about_ca_system_score_gemma":0.0011967386,"threshold_uncertainty_score":0.020206213},"labels":[],"label_agreement":null},{"id":"W3199368817","doi":"10.1515/jbnst-2024-0013","title":"Payment Habits during Covid-19: Evidence from High-Frequency Transaction Data","year":2024,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Business; Database transaction; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Payment; Computer science; Medicine; Virology; Database; Finance; Internal medicine; Outbreak","score_opus":0.09106571035195041,"score_gpt":0.3516198374171692,"score_spread":0.26055412706521874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199368817","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990333,0.00017384348,0.0004731181,0.00017225964,0.0000063720295,0.000028274108,0.007805562,0.000014567622,0.0009930221],"genre_scores_gemma":[0.99232966,0.00013569539,0.00024615965,0.00003648258,0.000007146782,0.000014273927,0.0069475477,0.000006286967,0.00027682493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971113,0.0011007062,0.00028336624,0.0004243922,0.0007500139,0.00033009506],"domain_scores_gemma":[0.96660423,0.0109451655,0.012971596,0.002959994,0.005021979,0.0014971057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034249672,0.00025980346,0.0003436733,0.0016890286,0.0005538793,0.0014578938,0.0010476205,0.00067362277,0.0028393366],"category_scores_gemma":[0.020468075,0.00032417616,0.0003492729,0.006667238,0.000931581,0.0007259166,0.00087742816,0.0007988072,0.0007067564],"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":[0.000085665946,0.000031246356,0.9964966,0.000024739364,0.00007551447,0.00005339984,0.00026975776,0.0004949194,0.000046343022,0.000079745114,0.0005905217,0.0017515313],"study_design_scores_gemma":[0.000006447671,0.000038781738,0.99532014,0.000026061769,0.000026305406,0.000059911577,0.00080214563,0.002841904,0.00007884193,0.000065787506,0.0007186555,0.000014866666],"about_ca_topic_score_codex":0.468104,"about_ca_topic_score_gemma":0.45722717,"teacher_disagreement_score":0.468104,"about_ca_system_score_codex":0.0019932778,"about_ca_system_score_gemma":0.0017263555,"threshold_uncertainty_score":0.93075866},"labels":[],"label_agreement":null},{"id":"W4206439381","doi":"10.1515/jbnst-2014-frontmatter2-3","title":"Titelei","year":2014,"lang":"de","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Outstanding Youth Science Fund Project of National Natural Science Foundation of China; HEC Montréal; Università Bocconi; University of New South Wales","keywords":"Economics","score_opus":0.03168636325338508,"score_gpt":0.25554013299706857,"score_spread":0.22385376974368348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206439381","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038804573,0.026415303,0.005504171,0.00804557,0.017152082,0.0002723675,0.009069268,0.0018529929,0.92780787],"genre_scores_gemma":[0.008987484,0.009342466,0.0026701381,0.0010014327,0.0015428687,0.0003009382,0.0036379008,0.00074671785,0.97177],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991216,0.00011446596,0.000084488245,0.00021549701,0.00032791434,0.00013603712],"domain_scores_gemma":[0.99946684,0.00007886378,0.000051452353,0.00014162215,0.00015916646,0.000102037266],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006816254,0.0013416142,0.0012644762,0.0035095885,0.0020266648,0.004414344,0.0009845204,0.0016723458,0.50073004],"category_scores_gemma":[0.0015158195,0.0005102567,0.00062675186,0.0029980522,0.0007432607,0.0035403294,0.0038191192,0.0025269948,0.50479037],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014094797,0.00007735341,0.00046763837,0.0006273749,0.000021361251,0.00019871797,0.00023966409,0.00029518135,0.0016817972,0.054609116,0.5001281,0.4415128],"study_design_scores_gemma":[0.000009076223,0.000018261828,0.0003859444,0.00012703995,0.0000042361153,0.00017860848,0.00004622069,0.00008790365,0.00028188244,0.00529388,0.9935592,0.000007747381],"about_ca_topic_score_codex":0.0011713521,"about_ca_topic_score_gemma":0.0016072178,"teacher_disagreement_score":0.49926996,"about_ca_system_score_codex":0.0013329929,"about_ca_system_score_gemma":0.0014728697,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4324065244","doi":"10.1515/jbnst-2023-0009","title":"The High Frequency Firm Survey “Bundesbank Online Panel – Firms”","year":2023,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Public Administration and Political Analysis","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Panel survey; Survey data collection; Survey research; Business; Data collection; Survey methodology; Panel data; Coronavirus disease 2019 (COVID-19); Core (optical fiber); Accounting; Economics; Econometrics; Demographic economics; Computer science; Geography; Telecommunications; Statistics","score_opus":0.10512842917986702,"score_gpt":0.41269382931707715,"score_spread":0.3075654001372101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324065244","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043456174,0.00028877557,0.0016340361,0.00067514845,0.000091568945,0.00071145536,0.93752706,0.00018685052,0.015428878],"genre_scores_gemma":[0.07155607,0.00028066462,0.003248173,0.00036524842,0.000085254964,0.0019835357,0.9073953,0.00006819357,0.015017653],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9960311,0.0010680559,0.00048936787,0.0005793351,0.0013396882,0.0004924552],"domain_scores_gemma":[0.9905934,0.002034274,0.0021505328,0.0011196714,0.0032842034,0.0008179989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024998183,0.0003373435,0.00037954334,0.0029850209,0.00049950887,0.0012578148,0.0006253419,0.0008330132,0.026054284],"category_scores_gemma":[0.008278004,0.00029156765,0.00025997963,0.0065874276,0.00018576183,0.00069511787,0.0009392228,0.0007091647,0.01647094],"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":[0.0002482502,0.00033191775,0.10256981,0.0004107024,0.00009883481,0.00009412931,0.00035802615,0.0007625017,0.0009397124,0.002895085,0.8633659,0.027925063],"study_design_scores_gemma":[0.00008965918,0.00010562771,0.59997815,0.00015428274,0.000035460165,0.00008716817,0.0005837128,0.0007600102,0.001003434,0.0007453155,0.39640814,0.000049065962],"about_ca_topic_score_codex":0.031284686,"about_ca_topic_score_gemma":0.035817903,"teacher_disagreement_score":0.031284686,"about_ca_system_score_codex":0.0013714299,"about_ca_system_score_gemma":0.0018819073,"threshold_uncertainty_score":0.08716029},"labels":[],"label_agreement":null},{"id":"W4410592267","doi":"10.1515/jbnst-2024-0058","title":"Do Firms Issue More Equity When Markets Become More Liquid? The Case of Imperial Germany, 1898–1913","year":2025,"lang":"en","type":"article","venue":"Jahrbücher für Nationalökonomie und Statistik","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","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":"Concordia University","funders":"","keywords":"Equity (law); Business; Economics; Monetary economics; Commerce; Political science; Law","score_opus":0.019261992865028114,"score_gpt":0.30972542308960366,"score_spread":0.29046343022457555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410592267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956268,0.0005896263,0.000026764388,0.0008639523,0.0000036904662,0.0000017302311,0.00021555183,0.0000013813747,0.0026704539],"genre_scores_gemma":[0.99927765,0.00019939315,0.000015534744,0.000025606629,0.0000084864005,8.0188056e-7,0.00011190075,0.0000010186355,0.00035959683],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996879,0.00004692082,0.00002011942,0.00006774929,0.000049436007,0.00012786164],"domain_scores_gemma":[0.9985952,0.00036506262,0.00067387876,0.000095918425,0.000100974576,0.0001689671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041997945,0.000103675324,0.00026340754,0.0013316403,0.00064005493,0.0018851425,0.00032745628,0.00059015385,0.0026115233],"category_scores_gemma":[0.0022301704,0.00012698356,0.00018327656,0.0017363911,0.0016369995,0.0011638469,0.0007834156,0.0008059553,0.00020975707],"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":[0.00085127034,0.00019439898,0.9024923,0.000169476,0.00041356374,0.012880421,0.01605743,0.0030564184,0.0016703743,0.030933386,0.006952563,0.024328308],"study_design_scores_gemma":[0.00003012279,0.000047025496,0.9759731,0.000082137834,0.00011877368,0.00087509345,0.007609458,0.001534217,0.0007513202,0.0016822991,0.011265623,0.000030991738],"about_ca_topic_score_codex":0.1177666,"about_ca_topic_score_gemma":0.12940958,"teacher_disagreement_score":0.1177666,"about_ca_system_score_codex":0.0024344237,"about_ca_system_score_gemma":0.00052783225,"threshold_uncertainty_score":0.23416221},"labels":[],"label_agreement":null}]}