{"meta":{"query_hash":"dbf2f9e4b535","filters":{"venue":"Journal of Urban Economics"},"cohort_total":61,"direct_labels_cover":0,"predictions_cover":61,"exported":61,"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/dbf2f9e4b535","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Urban+Economics"},"results":[{"id":"W1965757984","doi":"10.1006/juec.2001.2235","title":"Innovation and Input Sharing","year":2002,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":132,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Order (exchange); Process (computing); Innovation process; Business; Industrial organization; Knowledge management; Knowledge sharing; Computer science; Marketing; Work in process","score_opus":0.04919932570742486,"score_gpt":0.19971613911103794,"score_spread":0.1505168134036131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965757984","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":[0.4625288,0.0033432327,0.06941445,0.00990702,0.00025874507,0.00008245576,0.0005449073,0.00018972195,0.4537307],"genre_scores_gemma":[0.9767898,0.0005950629,0.0017406698,0.00016962057,0.00011742845,0.000017711334,0.000052193456,0.00001982552,0.0204978],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99874544,0.00039291606,0.00006752901,0.00023586804,0.00024155753,0.0003166405],"domain_scores_gemma":[0.99112743,0.005794,0.0008292005,0.0010881516,0.0007191728,0.0004420568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021096857,0.0004023097,0.0011713961,0.0010761895,0.0012316011,0.004368778,0.0008819876,0.002070473,0.034996543],"category_scores_gemma":[0.010929372,0.0002980917,0.00096131495,0.00155784,0.0029767063,0.0052733836,0.0024838487,0.0012002856,0.0015458954],"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":[0.00010058082,0.000092238755,0.0032083553,0.000069362286,0.00006510065,0.00018093019,0.0003941193,0.010083414,0.0006640272,0.9564077,0.0027060872,0.02602807],"study_design_scores_gemma":[0.000025875563,0.000026192762,0.0018601989,0.000020904608,0.000037733767,0.000104675564,0.00029847035,0.005346076,0.00035256165,0.9871952,0.0047207396,0.000011314107],"about_ca_topic_score_codex":0.0017315157,"about_ca_topic_score_gemma":0.0013241337,"teacher_disagreement_score":0.034996543,"about_ca_system_score_codex":0.0015202782,"about_ca_system_score_gemma":0.0012145616,"threshold_uncertainty_score":0.117075086},"labels":[],"label_agreement":null},{"id":"W1970740637","doi":"10.1016/s0094-1190(02)00002-5","title":"Private roads, competition, and incentives to adopt time-based congestion tolling","year":2002,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Toll; Congestion pricing; Toll road; Microeconomics; Duopoly; Incentive; Price elasticity of demand; Competition (biology); Economics; Business; Road pricing; Revenue; Traffic congestion; Dilemma; Industrial organization; Finance; Cournot competition; Transport engineering","score_opus":0.01546114126786572,"score_gpt":0.22438736282700267,"score_spread":0.20892622155913695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970740637","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":[0.9593828,0.00025385775,0.009703518,0.0045214593,0.000055183886,0.00010306857,0.00035553976,0.000048547976,0.025575986],"genre_scores_gemma":[0.9980476,0.000046851652,0.00036235774,0.00007871905,0.000018170853,0.000009986696,0.000024581836,0.0000024001235,0.0014093166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99746007,0.0010908628,0.00013363153,0.00022197209,0.00026983864,0.0008236684],"domain_scores_gemma":[0.95381993,0.028218493,0.010029304,0.0015261058,0.0025413528,0.003864724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045399982,0.00025455144,0.00078963,0.0007768354,0.00093287684,0.0026590277,0.0009898853,0.0031828315,0.013735007],"category_scores_gemma":[0.02318637,0.00046235629,0.00047317412,0.00097407954,0.0021085637,0.0025334058,0.0010606783,0.0019094669,0.00037494645],"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":[0.004509368,0.0035326164,0.15919854,0.00042180342,0.00061770325,0.0010003463,0.0012324369,0.35211506,0.005559756,0.39341784,0.013289322,0.06510514],"study_design_scores_gemma":[0.0018047513,0.0018159994,0.14465275,0.000098194934,0.000450079,0.00070544,0.0039167837,0.39920467,0.0026379116,0.42686477,0.017557178,0.0002915219],"about_ca_topic_score_codex":0.010946663,"about_ca_topic_score_gemma":0.030408159,"teacher_disagreement_score":0.013735007,"about_ca_system_score_codex":0.0024291512,"about_ca_system_score_gemma":0.00291731,"threshold_uncertainty_score":0.045948148},"labels":[],"label_agreement":null},{"id":"W1978549132","doi":"10.1016/j.jue.2007.02.003","title":"The price of residential land in large US cities","year":2007,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":309,"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":"AGE-WELL","keywords":"Metropolitan area; Land Values; Agricultural economics; Sample (material); Land value; Land price; Volatility (finance); Value (mathematics); Land use; Geography; Economics; Econometrics; Statistics","score_opus":0.014611467633303708,"score_gpt":0.20208628095455922,"score_spread":0.1874748133212555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978549132","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":[0.99709094,0.00013728735,0.000119366065,0.00076160085,0.0000075749945,0.000004067755,0.0009024142,0.000009041448,0.0009676987],"genre_scores_gemma":[0.9988984,0.000045888333,0.000027225198,0.000029117595,0.0000100007765,0.000002129073,0.000518203,0.0000031835048,0.00046585218],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99958676,0.00010576634,0.000033148703,0.000067853005,0.00011455377,0.00009201055],"domain_scores_gemma":[0.9966994,0.0010630606,0.0010529701,0.00008608668,0.00054459745,0.00055379915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004376232,0.00016951692,0.000353445,0.0009394474,0.0005832112,0.002417473,0.0007861842,0.0010485132,0.0037306657],"category_scores_gemma":[0.0034793282,0.00040205132,0.0004140745,0.00246892,0.00083468336,0.0016662063,0.0008484962,0.0010611407,0.00040828864],"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":[0.00040150803,0.00021900363,0.9764513,0.000035381312,0.00016886613,0.0005290367,0.00071194733,0.009103044,0.00077287666,0.0043477234,0.004282826,0.002976524],"study_design_scores_gemma":[0.00004671489,0.00006502646,0.9719772,0.000012156927,0.00005020348,0.00013810165,0.0031028322,0.020794928,0.00029734327,0.0017756997,0.001704849,0.000034930123],"about_ca_topic_score_codex":0.17120616,"about_ca_topic_score_gemma":0.28483918,"teacher_disagreement_score":0.17120616,"about_ca_system_score_codex":0.0035365215,"about_ca_system_score_gemma":0.0009482657,"threshold_uncertainty_score":0.3404193},"labels":[],"label_agreement":null},{"id":"W1978991631","doi":"10.1006/juec.2001.2230","title":"The Determinants of Agglomeration","year":2001,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":1174,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Economies of agglomeration; Perishability; Pooling; Microfoundations; Proxy (statistics); Product (mathematics); Economics; Microeconomics; Economic geography; Industrial organization; Business; Marketing; Computer science","score_opus":0.0270593323061467,"score_gpt":0.21141723305413015,"score_spread":0.18435790074798344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978991631","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":[0.96835446,0.0013181486,0.002724059,0.0057497076,0.000024826124,0.000019209552,0.0004570981,0.000061023846,0.0212914],"genre_scores_gemma":[0.9990558,0.00013804635,0.00008494803,0.000020054706,0.000014626038,0.0000019366753,0.00004129701,0.0000043219025,0.0006389451],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994462,0.00020491115,0.000022124661,0.000064871536,0.00009651608,0.00016537508],"domain_scores_gemma":[0.987347,0.007746545,0.0022061572,0.0006217565,0.0011174558,0.0009610296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091979204,0.0001499679,0.0004078133,0.0010737736,0.0008293114,0.002294878,0.0004689184,0.00092266663,0.011631672],"category_scores_gemma":[0.011459617,0.0003118169,0.00033433342,0.0016952851,0.0023678478,0.0016697977,0.001036145,0.0010060166,0.0008670334],"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":[0.00026777163,0.00028106847,0.6943512,0.00010531849,0.0002906847,0.0004949989,0.002008429,0.02039965,0.0010497045,0.24220328,0.011597107,0.026950806],"study_design_scores_gemma":[0.00006217846,0.00007349899,0.81973577,0.000058876787,0.0002710322,0.00033689095,0.004181838,0.022997763,0.0006953315,0.1404121,0.011129866,0.00004486844],"about_ca_topic_score_codex":0.024505794,"about_ca_topic_score_gemma":0.036403533,"teacher_disagreement_score":0.024505794,"about_ca_system_score_codex":0.0013817614,"about_ca_system_score_gemma":0.0008273649,"threshold_uncertainty_score":0.04872632},"labels":[],"label_agreement":null},{"id":"W1991532335","doi":"10.1016/j.jue.2014.01.004","title":"The effect of government corruption on the efficiency of US commercial airports","year":2014,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Corruption and Economic Development","field":"Social Sciences","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Allocative efficiency; Language change; Public good; Context (archaeology); Incentive; Productivity; Economics; Public economics; Corporate governance; Government (linguistics); Stochastic frontier analysis; Variable (mathematics); Business; Industrial organization; Microeconomics; Macroeconomics; Production (economics); Finance","score_opus":0.0108699508768979,"score_gpt":0.23501910153330127,"score_spread":0.22414915065640337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991532335","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":[0.9934238,0.00012739193,0.00017301706,0.0006876557,0.000008405462,0.000005798151,0.00012901079,0.0000068955483,0.0054380256],"genre_scores_gemma":[0.9996227,0.000022156062,0.0000144263295,0.000019918665,0.0000028686914,7.515792e-7,0.000024171124,0.0000015954417,0.0002913561],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977737,0.00092392426,0.000105985884,0.00011771499,0.00025306907,0.00082556304],"domain_scores_gemma":[0.97740513,0.008413083,0.007723067,0.0012282148,0.0034577276,0.0017728384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018599029,0.00019846747,0.00036942615,0.00077655935,0.0007747089,0.00294866,0.00039921497,0.0008078484,0.0035422847],"category_scores_gemma":[0.014604069,0.00022290315,0.00044788548,0.0011889281,0.001632311,0.0012793867,0.0008053531,0.0014450441,0.00039098572],"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":[0.0015662705,0.00065339863,0.8747178,0.000058006615,0.00039277977,0.00046498075,0.0008384545,0.07295803,0.0018792916,0.027177539,0.0045135207,0.014779927],"study_design_scores_gemma":[0.00009610627,0.00029605808,0.9579828,0.000037826034,0.00017152316,0.00009122184,0.0037249278,0.028544735,0.0019959076,0.0048250393,0.002194862,0.00003907443],"about_ca_topic_score_codex":0.06724188,"about_ca_topic_score_gemma":0.08563606,"teacher_disagreement_score":0.06724188,"about_ca_system_score_codex":0.0046488307,"about_ca_system_score_gemma":0.0022203708,"threshold_uncertainty_score":0.13370097},"labels":[],"label_agreement":null},{"id":"W2003010992","doi":"10.1016/j.jue.2011.06.001","title":"Local labor market impacts of energy boom-bust-boom in Western Canada","year":2011,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":226,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Alberta","funders":"University of Alberta; Canadian Association of Petroleum Producers","keywords":"Boom; Bust; Earnings; Economics; Labour economics; Service (business); Business; Economy; Finance; Engineering","score_opus":0.045879339073041425,"score_gpt":0.20073138364976156,"score_spread":0.15485204457672014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003010992","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":[0.98998696,0.0003677342,0.0000363112,0.0024983506,0.000022321261,0.000019521043,0.0020851132,0.00001509566,0.00496853],"genre_scores_gemma":[0.9932092,0.00023673505,0.000026164364,0.00018328076,0.0000080583195,0.0000067301594,0.0007771395,0.000006515335,0.005546209],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992956,0.000040093928,0.000019514764,0.000045786168,0.000103675586,0.00049538625],"domain_scores_gemma":[0.9982204,0.0000987385,0.00016164499,0.000027188562,0.00060668145,0.0008853737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044739392,0.0002085263,0.00057956175,0.0010151569,0.0042266254,0.003006113,0.0012180053,0.001021601,0.010254166],"category_scores_gemma":[0.0014130299,0.00027729743,0.00061429775,0.0028521558,0.0013134886,0.0006607676,0.0015103135,0.0011818581,0.00059033866],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008892921,0.0004089286,0.940124,0.00011851501,0.00017290945,0.00091973017,0.007996629,0.004382754,0.00086128106,0.0066634696,0.023366928,0.014095625],"study_design_scores_gemma":[0.000046342444,0.000042092586,0.96248144,0.00005208275,0.000047544872,0.000030901327,0.025094492,0.0026425386,0.00016873186,0.0003186408,0.0090327505,0.000042428346],"about_ca_topic_score_codex":0.99828064,"about_ca_topic_score_gemma":0.99942696,"teacher_disagreement_score":0.056470897,"about_ca_system_score_codex":0.056470897,"about_ca_system_score_gemma":0.04585993,"threshold_uncertainty_score":0.40972698},"labels":[],"label_agreement":null},{"id":"W2011879432","doi":"10.1016/j.jue.2008.11.003","title":"Industry location and welfare when transport costs are endogenous","year":2008,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Merger and Competition Analysis","field":"Economics, Econometrics and Finance","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Welfare; Endogeny; Economics; Business; Market economy; Chemistry; Biochemistry","score_opus":0.0403031658479311,"score_gpt":0.18652180306030086,"score_spread":0.14621863721236977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011879432","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":[0.96442777,0.00050790585,0.016902028,0.003617861,0.000029869676,0.000018272101,0.0002830966,0.000039745282,0.014173451],"genre_scores_gemma":[0.99567986,0.00022267111,0.0005395884,0.000088998684,0.000033804066,0.000008637668,0.000048980262,0.000008157275,0.0033692229],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992219,0.00031461866,0.000017391463,0.00006270347,0.000039871047,0.00034343812],"domain_scores_gemma":[0.9942654,0.003937052,0.0008954149,0.0003011026,0.00023623696,0.00036480633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015264476,0.00035449277,0.0010690896,0.00088640733,0.0006753587,0.0027867681,0.0006742988,0.0018832512,0.008662221],"category_scores_gemma":[0.0057169637,0.00044442847,0.0006671183,0.0015953896,0.0016991437,0.003564392,0.001115647,0.0013064961,0.0005323394],"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":[0.0022173638,0.0015170485,0.14076163,0.00025196592,0.0005429587,0.0020892036,0.0010102955,0.24667816,0.003651374,0.5478143,0.008435932,0.045029785],"study_design_scores_gemma":[0.0003730969,0.00036481244,0.06657911,0.00008052002,0.00041471262,0.00086709,0.004781797,0.2930839,0.0011199879,0.6289503,0.0033000817,0.000084647974],"about_ca_topic_score_codex":0.008022096,"about_ca_topic_score_gemma":0.008652726,"teacher_disagreement_score":0.008662221,"about_ca_system_score_codex":0.001918034,"about_ca_system_score_gemma":0.0010337938,"threshold_uncertainty_score":0.02897805},"labels":[],"label_agreement":null},{"id":"W2020745513","doi":"10.1016/j.jue.2004.12.002","title":"From sectoral to functional urban specialisation","year":2005,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":606,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto; Connaught Fund; London School of Economics and Political Science","keywords":"Economic geography; Variety (cybernetics); Transformation (genetics); Function (biology); Business; Production (economics); Economics; Industrial organization; Natural resource economics; Biology; Microeconomics","score_opus":0.03726369293485314,"score_gpt":0.2006445675835155,"score_spread":0.16338087464866236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020745513","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":[0.76648253,0.0027817925,0.025579678,0.0072144964,0.00018350415,0.000038059166,0.0007348749,0.00010927635,0.19687581],"genre_scores_gemma":[0.9967186,0.00026421555,0.0005578902,0.00006547345,0.000050844512,0.0000041347394,0.00006566567,0.000008762932,0.0022644482],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.999403,0.0001829533,0.00002725402,0.00010559331,0.00006586928,0.00021523601],"domain_scores_gemma":[0.99643046,0.0012811279,0.00057088654,0.00042420923,0.0006255425,0.0006678736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007160914,0.00021844318,0.00030762603,0.0015357104,0.0006841273,0.0020650947,0.0005407912,0.0005064235,0.019897418],"category_scores_gemma":[0.004153523,0.00017010079,0.00041358097,0.0020255945,0.003148579,0.0034789415,0.0024459788,0.00084393925,0.00069502747],"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":[0.000114308765,0.00005626279,0.07675087,0.00014598134,0.00003671232,0.00030746608,0.0026535,0.0036728997,0.00043781227,0.8675057,0.0046227137,0.04369575],"study_design_scores_gemma":[0.000023371898,0.0001387893,0.10918892,0.00014390943,0.00005505656,0.0009397974,0.012853332,0.0063305544,0.0003663543,0.842419,0.02751773,0.000023197803],"about_ca_topic_score_codex":0.0047386647,"about_ca_topic_score_gemma":0.007370935,"teacher_disagreement_score":0.019897418,"about_ca_system_score_codex":0.0009983638,"about_ca_system_score_gemma":0.0006190145,"threshold_uncertainty_score":0.06656355},"labels":[],"label_agreement":null},{"id":"W2030702499","doi":"10.1006/juec.2001.2227","title":"Stolen Gun Control","year":2001,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Gun Ownership and Violence Research","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Externality; Gun control; Gun violence; Business; Control (management); Law and economics; Economics; Poison control; Microeconomics; Market economy; Suicide prevention","score_opus":0.037003252745081636,"score_gpt":0.3180661021266157,"score_spread":0.28106284938153403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030702499","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":[0.603031,0.0021705602,0.002237669,0.0024911729,0.00029788728,0.0001425129,0.0023793618,0.00006749717,0.38718233],"genre_scores_gemma":[0.95214933,0.00043771006,0.00021032666,0.00022607126,0.000049630824,0.00002052675,0.00049930596,0.0000056128843,0.046401527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99861276,0.00015589698,0.00006881603,0.00019312013,0.0005675504,0.00040182116],"domain_scores_gemma":[0.9972363,0.0005768899,0.00073754735,0.0004162369,0.0006362387,0.00039687424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072307786,0.00025091798,0.00023363273,0.0020604804,0.0010768273,0.0027738975,0.0007427768,0.00078170124,0.035070114],"category_scores_gemma":[0.007471286,0.00018556463,0.0003819546,0.0010647157,0.000888247,0.0010598504,0.0013012004,0.0010895806,0.0021958253],"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":[0.0006624725,0.0013484113,0.43112418,0.00030154287,0.0003408562,0.00094431086,0.0036685183,0.0037555897,0.0015147106,0.17068493,0.032149766,0.35350466],"study_design_scores_gemma":[0.000093869196,0.0009795827,0.81109303,0.0005232791,0.00034716207,0.0020965892,0.007677113,0.0070750043,0.0042504915,0.03682131,0.1289387,0.00010395308],"about_ca_topic_score_codex":0.015044147,"about_ca_topic_score_gemma":0.022126094,"teacher_disagreement_score":0.035070114,"about_ca_system_score_codex":0.0015884407,"about_ca_system_score_gemma":0.001213952,"threshold_uncertainty_score":0.11732125},"labels":[],"label_agreement":null},{"id":"W2033491347","doi":"10.1016/j.jue.2010.08.004","title":"Is the division of labour limited by the extent of the market? Evidence from French cities","year":2010,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":97,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Census; Division of labour; Division (mathematics); Economics; Empirical evidence; Economic geography; Labour economics; Sociology; Market economy; Population; Demography","score_opus":0.0242264611246015,"score_gpt":0.20024265019298326,"score_spread":0.17601618906838176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033491347","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":[0.9840449,0.0027538722,0.00019268351,0.0022511233,0.000009870462,0.0000067846972,0.00061429257,0.0000042295896,0.010122218],"genre_scores_gemma":[0.99847203,0.00058375444,0.000032169817,0.00014677369,0.00002005811,0.00000513627,0.00025879996,0.0000031089717,0.0004780016],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99613804,0.0015380629,0.00017356871,0.00054995355,0.00062602217,0.00097428425],"domain_scores_gemma":[0.956935,0.025362309,0.00909857,0.0023988711,0.0045102113,0.0016950319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039662374,0.0003158019,0.0011263159,0.0028902558,0.0017829058,0.0032077362,0.001638254,0.0012621911,0.009085531],"category_scores_gemma":[0.015930181,0.00041615992,0.00069506356,0.0051482054,0.003936912,0.0024713695,0.0022074296,0.00074216933,0.0007449353],"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":[0.0021145104,0.00028007958,0.9258375,0.0004997222,0.0007531334,0.0010578665,0.013261882,0.0026262195,0.0010262296,0.016912775,0.005665589,0.029964488],"study_design_scores_gemma":[0.00007341195,0.00009000524,0.97953826,0.00013371701,0.00015026524,0.00008274348,0.011934133,0.00048324018,0.00015772523,0.0020243814,0.005299809,0.00003227501],"about_ca_topic_score_codex":0.32706827,"about_ca_topic_score_gemma":0.35620737,"teacher_disagreement_score":0.32706827,"about_ca_system_score_codex":0.0044966373,"about_ca_system_score_gemma":0.0021361266,"threshold_uncertainty_score":0.65032905},"labels":[],"label_agreement":null},{"id":"W2035225386","doi":"10.1016/j.jue.2008.02.005","title":"The merits of separating cars and trucks","year":2008,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Truck; Toll; Transport engineering; Traffic congestion; Vehicle type; Toll road; Road pricing; Computer science; Business; Automotive engineering; Engineering","score_opus":0.0190642222393632,"score_gpt":0.25196140005925827,"score_spread":0.23289717781989505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035225386","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":[0.67804044,0.010524353,0.041919596,0.037400737,0.0011810795,0.000073103,0.00038585573,0.00011536428,0.23035948],"genre_scores_gemma":[0.98645616,0.0011265246,0.0030294547,0.0007110917,0.0005040307,0.000013225295,0.000056626497,0.000036711994,0.008066263],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99742186,0.0012746995,0.00010266659,0.00024023115,0.0006395335,0.00032107017],"domain_scores_gemma":[0.9753087,0.019731337,0.0014536622,0.0012548716,0.0013486142,0.000902821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006159011,0.0005279364,0.0009884844,0.00091665256,0.0013666527,0.00426878,0.0016612096,0.0033314829,0.0143019445],"category_scores_gemma":[0.039383415,0.00060108927,0.000576136,0.001109788,0.0036620465,0.0063602943,0.0014144481,0.0021446683,0.0011837053],"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":[0.0041328156,0.00027406527,0.008785202,0.00028986967,0.00016216171,0.00023880553,0.000601369,0.048021484,0.0017752115,0.79665005,0.012478916,0.12658998],"study_design_scores_gemma":[0.00042127472,0.00025510308,0.0073429756,0.00007553132,0.00027960763,0.00022479495,0.0018997289,0.057740416,0.0012721753,0.9139817,0.016449181,0.0000576542],"about_ca_topic_score_codex":0.0038067356,"about_ca_topic_score_gemma":0.0049113706,"teacher_disagreement_score":0.0143019445,"about_ca_system_score_codex":0.0017528732,"about_ca_system_score_gemma":0.0015229196,"threshold_uncertainty_score":0.047844827},"labels":[],"label_agreement":null},{"id":"W2042026627","doi":"10.1016/j.jue.2009.09.011","title":"Overlapping soft budget constraints","year":2009,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Local Government Finance and Decentralization","field":"Social Sciences","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bishop's University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Decentralization; Budget constraint; Competition (biology); Constraint (computer-aided design); Set (abstract data type); Equalization (audio); Economics; Public economics; Microeconomics; Computer science; Engineering; Market economy; Telecommunications","score_opus":0.013655544775002844,"score_gpt":0.2507031188610934,"score_spread":0.2370475740860906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042026627","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":[0.33614793,0.002635221,0.33463016,0.015207156,0.0010887058,0.000563109,0.003508955,0.0003946394,0.30582407],"genre_scores_gemma":[0.94046015,0.00064697367,0.014325205,0.0006377316,0.00038408802,0.00023530688,0.0004515874,0.00007451374,0.0427845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99670815,0.0012008138,0.0002121979,0.0004995636,0.0004672844,0.00091193453],"domain_scores_gemma":[0.987379,0.008538025,0.001317802,0.0010810671,0.0007425365,0.0009415998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032585755,0.0010177463,0.0024258648,0.0012765311,0.0010005592,0.004437524,0.0019624468,0.0024815684,0.047134478],"category_scores_gemma":[0.0215121,0.0012358769,0.0011560863,0.0015742958,0.0019115065,0.0045995363,0.0029398634,0.0036631306,0.0015756073],"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":[0.00031212112,0.00014456159,0.0017951194,0.00028230486,0.00015942911,0.00074681843,0.00027345258,0.06567105,0.00057426805,0.88829494,0.012886097,0.028859742],"study_design_scores_gemma":[0.00017933575,0.000067102796,0.0016124173,0.00010225165,0.00007136437,0.00034123694,0.00037173074,0.097863324,0.00036531012,0.88853043,0.010458319,0.000037007605],"about_ca_topic_score_codex":0.0026717072,"about_ca_topic_score_gemma":0.002429811,"teacher_disagreement_score":0.047134478,"about_ca_system_score_codex":0.0017959516,"about_ca_system_score_gemma":0.0013923123,"threshold_uncertainty_score":0.15768057},"labels":[],"label_agreement":null},{"id":"W2045697832","doi":"10.1016/j.jue.2007.12.002","title":"Fat city: Questioning the relationship between urban sprawl and obesity","year":2008,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":230,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Urban sprawl; Obesity; Environmental health; Geography; Demographic economics; Economic geography; Demography; Urban planning; Medicine; Economics; Biology; Sociology; Endocrinology; Ecology","score_opus":0.0700124846701822,"score_gpt":0.2895022262124455,"score_spread":0.21948974154226328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045697832","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":[0.8823683,0.014851284,0.0011210919,0.091348715,0.0008940967,0.00002236293,0.00036392134,0.000006823294,0.009023308],"genre_scores_gemma":[0.9948959,0.0018286477,0.00022697891,0.0020535495,0.0005684092,0.000009503156,0.000054093343,0.0000031377738,0.0003597215],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99799097,0.0013682687,0.000097340264,0.00025226167,0.00014098898,0.00015020758],"domain_scores_gemma":[0.97268236,0.019834202,0.0035012716,0.0010327206,0.001590027,0.0013594023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006707293,0.0004647685,0.00043080506,0.0015793014,0.0011164725,0.0022163624,0.0015511623,0.0028622728,0.0051034],"category_scores_gemma":[0.03140156,0.00025416535,0.0006163979,0.0020189919,0.004690788,0.0031633677,0.0021259906,0.0031495988,0.00029186773],"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":[0.00045720555,0.0003354571,0.9397301,0.00027457892,0.0006456775,0.00031090793,0.004846012,0.0004818238,0.00013832447,0.022775196,0.00405332,0.02595151],"study_design_scores_gemma":[0.00014567244,0.0006419014,0.83333445,0.000904289,0.0012155472,0.00088998664,0.055060517,0.004899943,0.000446357,0.088292725,0.014064691,0.000103789476],"about_ca_topic_score_codex":0.0162685,"about_ca_topic_score_gemma":0.01802479,"teacher_disagreement_score":0.0162685,"about_ca_system_score_codex":0.0007469972,"about_ca_system_score_gemma":0.0015331762,"threshold_uncertainty_score":0.035471976},"labels":[],"label_agreement":null},{"id":"W2048850264","doi":"10.1016/j.jue.2004.04.003","title":"Knowledge barter in cities","year":2004,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Barter; Economics; Microeconomics; Value (mathematics); Computer science; Market economy","score_opus":0.02787820702998596,"score_gpt":0.2040009922586256,"score_spread":0.17612278522863967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048850264","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":[0.75254965,0.0042732893,0.023423757,0.04045681,0.00025348333,0.00006214732,0.001229706,0.00017255147,0.17757857],"genre_scores_gemma":[0.98961115,0.00057230255,0.00039981096,0.00016899704,0.0000911057,0.000007476343,0.0000677164,0.000008182523,0.009073412],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992092,0.00031552784,0.000044840734,0.0001341363,0.00011460599,0.00018180026],"domain_scores_gemma":[0.9901724,0.0056820805,0.0018887336,0.0007695835,0.0007174764,0.0007697945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013727681,0.00016626946,0.0008750924,0.0014828616,0.0017437645,0.005939242,0.0008143589,0.0029004356,0.021775575],"category_scores_gemma":[0.0107620545,0.0003131408,0.000396961,0.0024168128,0.0029845766,0.006866821,0.0018613896,0.0016218262,0.00087993365],"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":[0.00026080056,0.00012685203,0.009214151,0.00010202203,0.00007473137,0.0004984539,0.0011976757,0.027036352,0.00017665069,0.92844135,0.014693604,0.018177258],"study_design_scores_gemma":[0.000073046256,0.000031182426,0.007108311,0.000047698028,0.000053777323,0.00013858464,0.0023654082,0.035061184,0.00018398132,0.94403946,0.010861832,0.000035596746],"about_ca_topic_score_codex":0.018614667,"about_ca_topic_score_gemma":0.014816356,"teacher_disagreement_score":0.021775575,"about_ca_system_score_codex":0.0028477125,"about_ca_system_score_gemma":0.0015735128,"threshold_uncertainty_score":0.07284653},"labels":[],"label_agreement":null},{"id":"W2050408251","doi":"10.1006/juec.2000.2200","title":"Site Density Restrictions: Measurement and Empirical Analysis","year":2001,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Redevelopment; Floor area ratio; Real estate; Distortion (music); Space (punctuation); Measure (data warehouse); Incentive; Function (biology); Government (linguistics); Empirical research; Land use; Set (abstract data type); China; Econometrics; Business; Economics; Microeconomics; Computer science; Finance; Statistics; Geography; Mathematics; Civil engineering; Telecommunications; Engineering","score_opus":0.06499989825687523,"score_gpt":0.23163947679799834,"score_spread":0.1666395785411231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050408251","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":[0.8351947,0.0014019656,0.15204209,0.00090384984,0.000038527018,0.00021232989,0.0013698032,0.00028071576,0.008556038],"genre_scores_gemma":[0.98837215,0.000451985,0.009305008,0.000032485677,0.000048426602,0.000070415284,0.00096591236,0.000029772063,0.000723848],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9959204,0.0023208645,0.00025315513,0.0005365521,0.00068263133,0.0002863182],"domain_scores_gemma":[0.8590638,0.11229781,0.010970964,0.011367955,0.0050630746,0.0012363533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009075023,0.0006138307,0.0013246692,0.0032262497,0.0008642944,0.002256389,0.0026562863,0.0013877493,0.007314094],"category_scores_gemma":[0.08159493,0.00078111776,0.00086352683,0.0058311503,0.003944337,0.0033705686,0.0019461085,0.0017355855,0.00090218533],"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":[0.0004477911,0.0011892149,0.6475465,0.0003464979,0.00037834136,0.00033521073,0.00091938226,0.04701127,0.0019938387,0.20120695,0.0059534027,0.09267164],"study_design_scores_gemma":[0.00015820003,0.0003299567,0.34855902,0.00019668296,0.00037246707,0.0010788228,0.0017343849,0.45631668,0.0037666822,0.18243499,0.0048716795,0.00018044263],"about_ca_topic_score_codex":0.010342745,"about_ca_topic_score_gemma":0.0066355444,"teacher_disagreement_score":0.010342745,"about_ca_system_score_codex":0.001146841,"about_ca_system_score_gemma":0.0015032401,"threshold_uncertainty_score":0.0479939},"labels":[],"label_agreement":null},{"id":"W2055459527","doi":"10.1016/j.jue.2014.03.003","title":"Why are some regions more innovative than others? The role of small firms in the presence of large labs","year":2014,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":134,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Industrial organization; Spawn (biology); Population; Small business; Economics; Marketing","score_opus":0.024440352057740877,"score_gpt":0.21461439040196362,"score_spread":0.19017403834422275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055459527","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":[0.9827308,0.00067113916,0.000563033,0.005093395,0.000023233253,0.000012038353,0.000075664684,0.000013028225,0.010817648],"genre_scores_gemma":[0.9991431,0.00013934083,0.000072117546,0.0002123456,0.000025333775,0.0000027465858,0.000013894597,0.0000034556947,0.00038752265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972229,0.0011867044,0.000060040595,0.00032347196,0.00029521468,0.0009116883],"domain_scores_gemma":[0.960213,0.020448338,0.009183848,0.0010093537,0.0029512213,0.0061942576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003890361,0.0001632345,0.0005133721,0.0013803822,0.0015249185,0.0046648635,0.00082914194,0.0018967567,0.0068784202],"category_scores_gemma":[0.017391685,0.00021885343,0.00044092978,0.001801611,0.0055314596,0.003934484,0.0024936087,0.0013665896,0.0007281056],"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":[0.0008814763,0.00043712,0.8997295,0.00021355256,0.0003816694,0.0011152365,0.008862464,0.0026670077,0.0035872138,0.031325318,0.004562014,0.04623744],"study_design_scores_gemma":[0.00012462483,0.00044524018,0.9178988,0.00014544396,0.0003410407,0.0005734963,0.04439504,0.002189537,0.00173204,0.023579782,0.0084887175,0.00008617376],"about_ca_topic_score_codex":0.008907552,"about_ca_topic_score_gemma":0.01775013,"teacher_disagreement_score":0.008907552,"about_ca_system_score_codex":0.001664635,"about_ca_system_score_gemma":0.0015006235,"threshold_uncertainty_score":0.023010552},"labels":[],"label_agreement":null},{"id":"W2065360030","doi":"10.1016/j.jue.2013.05.001","title":"Uneven landscapes and city size distributions","year":2013,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Zipf's law; Distribution (mathematics); Product (mathematics); Econometrics; Feature (linguistics); Key (lock); Statistical physics; Economics; Economic geography; Computer science; Mathematics; Statistics; Geometry; Physics","score_opus":0.015678052794801632,"score_gpt":0.18236758285769128,"score_spread":0.16668953006288964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065360030","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":[0.96047753,0.0012147066,0.015202526,0.0020055873,0.00001881161,0.000012138902,0.00030808462,0.000028682036,0.020732],"genre_scores_gemma":[0.9981128,0.00022126363,0.00055589824,0.000021655576,0.000015200477,0.00000453335,0.000056699937,0.000007963139,0.0010038139],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99968135,0.00013704647,0.000014519627,0.00005455373,0.00004726124,0.00006527296],"domain_scores_gemma":[0.9899803,0.007379372,0.001091193,0.00044277436,0.00053097797,0.0005754648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080267614,0.00012461367,0.00030176496,0.0014338414,0.00050653185,0.0025738373,0.00043862328,0.00045846472,0.0087531125],"category_scores_gemma":[0.011536755,0.00026951052,0.00022276165,0.0019800165,0.00214073,0.0027792302,0.001089823,0.00060510286,0.00028496858],"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":[0.0001949882,0.00008969802,0.21619466,0.00006390079,0.00011543627,0.00037675787,0.0014391541,0.042102385,0.0005110141,0.700242,0.0039028411,0.03476717],"study_design_scores_gemma":[0.000034434317,0.000028818868,0.1521553,0.00002956913,0.00005257767,0.00041113907,0.003378202,0.054714818,0.00019486446,0.7821987,0.0067783115,0.000023248907],"about_ca_topic_score_codex":0.006058564,"about_ca_topic_score_gemma":0.008730937,"teacher_disagreement_score":0.0087531125,"about_ca_system_score_codex":0.0008891247,"about_ca_system_score_gemma":0.0002534544,"threshold_uncertainty_score":0.029282093},"labels":[],"label_agreement":null},{"id":"W2071857272","doi":"10.1016/j.jue.2006.05.006","title":"Agglomeration, opportunism, and the organization of production","year":2007,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of British Columbia","funders":"Connaught Fund","keywords":"Economies of agglomeration; Outsourcing; Opportunism; Industrial organization; Production (economics); Vertical integration; Globalization; Business; Economic geography; Dimension (graph theory); Economics; Commerce; Economic system; Microeconomics; Market economy; Marketing","score_opus":0.0341348887078499,"score_gpt":0.18672977700060184,"score_spread":0.15259488829275195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071857272","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":[0.9538294,0.0017846159,0.014461258,0.0017098697,0.00001407886,0.00002940853,0.0001645233,0.000034210112,0.027972681],"genre_scores_gemma":[0.99819666,0.00024354723,0.0007025209,0.000013353046,0.000012212482,0.000005627584,0.000022832333,0.0000036539502,0.00079946854],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99897754,0.0004427369,0.00004902434,0.00014223349,0.000114632974,0.00027375048],"domain_scores_gemma":[0.98952544,0.0058181286,0.0028203002,0.00067635323,0.00039599207,0.0007637986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014795222,0.00017330353,0.0005407061,0.0011585762,0.0013834469,0.0033345276,0.0004466135,0.001056249,0.0050620753],"category_scores_gemma":[0.005647406,0.0003674494,0.00043454906,0.0016034945,0.0035256594,0.0027776475,0.0017476277,0.00061131874,0.0003984728],"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":[0.0010463337,0.0003793898,0.29123434,0.00028703304,0.00051236706,0.0010714288,0.005479334,0.09306816,0.0033864842,0.54036844,0.0051983795,0.057968333],"study_design_scores_gemma":[0.0001052116,0.0001666644,0.20947233,0.000079116784,0.00013519464,0.00048223135,0.007246458,0.04942532,0.0009692505,0.72109735,0.010747545,0.00007331335],"about_ca_topic_score_codex":0.0058162254,"about_ca_topic_score_gemma":0.01326946,"teacher_disagreement_score":0.0058162254,"about_ca_system_score_codex":0.0019047327,"about_ca_system_score_gemma":0.0009258558,"threshold_uncertainty_score":0.016934335},"labels":[],"label_agreement":null},{"id":"W2074757957","doi":"10.1016/j.jue.2004.06.002","title":"What drives racial segregation? New evidence using Census microdata","year":2004,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":233,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Johns Hopkins University; Yale University","keywords":"Microdata (statistics); Census; American Community Survey; Race (biology); Geography; Demographic economics; Demography; Sociology; Economics; Population; Gender studies","score_opus":0.10129845005547308,"score_gpt":0.34034625736801666,"score_spread":0.23904780731254358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074757957","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":[0.9642455,0.0076833973,0.0029662745,0.007462112,0.00027885562,0.000053716773,0.0059185233,0.000029706667,0.011361771],"genre_scores_gemma":[0.99393976,0.0015998335,0.000993515,0.00041225593,0.00013403597,0.000026069296,0.0022063747,0.000019277273,0.00066892395],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99038154,0.0050205234,0.0010772384,0.001426932,0.0015155566,0.00057817844],"domain_scores_gemma":[0.8377775,0.10268457,0.02858089,0.015827285,0.012561023,0.0025688002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012469813,0.00052232883,0.00087357574,0.0037637309,0.0014715574,0.00444828,0.0018521292,0.001508889,0.005986978],"category_scores_gemma":[0.08795505,0.0008263431,0.0011917686,0.00800869,0.0016955723,0.003010704,0.0018829269,0.0015928388,0.001004949],"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":[0.000088702116,0.00007670666,0.9878023,0.000088119916,0.0005394462,0.000050143037,0.0007394755,0.00026765853,0.000046512523,0.0014670836,0.0016788001,0.0071549737],"study_design_scores_gemma":[0.000047836544,0.000052060703,0.97756654,0.00038939028,0.001270883,0.000088892724,0.0051867804,0.0033059733,0.00035493463,0.0032145877,0.008485836,0.00003632271],"about_ca_topic_score_codex":0.08443194,"about_ca_topic_score_gemma":0.12028077,"teacher_disagreement_score":0.08443194,"about_ca_system_score_codex":0.0012493893,"about_ca_system_score_gemma":0.0014836517,"threshold_uncertainty_score":0.16788101},"labels":[],"label_agreement":null},{"id":"W2102654225","doi":"10.1006/juec.2000.2178","title":"Externalities, Indivisibility, Nonreplicability, and Agglomeration","year":2000,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Diseconomies of scale; Externality; Economies of agglomeration; Economics; Economies of scale; Subsidy; Scale (ratio); Population; Microeconomics; Market economy; Geography","score_opus":0.024147547286138688,"score_gpt":0.20639696550672734,"score_spread":0.18224941822058865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102654225","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":[0.9499607,0.0007399348,0.013800651,0.0018399394,0.000019680983,0.000043512107,0.00040914203,0.00007555486,0.033110864],"genre_scores_gemma":[0.9951108,0.0002846428,0.0011281738,0.000045018307,0.00003957356,0.00002222807,0.000148777,0.000030248517,0.0031906024],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99764735,0.0010747311,0.00020162639,0.0003962512,0.0003240757,0.00035595195],"domain_scores_gemma":[0.9453276,0.029881189,0.01262743,0.0079679135,0.0023961142,0.0017997175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004378801,0.00033369812,0.0011922818,0.002226819,0.0021785705,0.005158857,0.0018230669,0.001750011,0.015809389],"category_scores_gemma":[0.034945145,0.0005080703,0.0007689939,0.005247083,0.0074658007,0.0070753973,0.004315032,0.0014938369,0.000992634],"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":[0.00064401247,0.0003446746,0.13012739,0.00021245341,0.00019237693,0.000861132,0.004727754,0.022829315,0.00078399153,0.7984164,0.0034084118,0.03745208],"study_design_scores_gemma":[0.00009103176,0.000085910586,0.03568966,0.000064863925,0.00013511302,0.00073562906,0.0037748746,0.013620799,0.0006932758,0.93842286,0.006638257,0.000047707304],"about_ca_topic_score_codex":0.004454328,"about_ca_topic_score_gemma":0.004274773,"teacher_disagreement_score":0.015809389,"about_ca_system_score_codex":0.0020874518,"about_ca_system_score_gemma":0.0010600645,"threshold_uncertainty_score":0.05288768},"labels":[],"label_agreement":null},{"id":"W2105999699","doi":"10.1016/j.jue.2008.12.004","title":"City size and the Henry George Theorem under monopolistic competition","year":2008,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"European Commission; Université du Québec à Montréal","keywords":"Monopolistic competition; Elasticity of substitution; Economics; Free entry; Constant elasticity of substitution; Elasticity (physics); General equilibrium theory; Microeconomics; Competition (biology); Variable (mathematics); Mathematical economics; Price elasticity of demand; Mathematics; Monopoly; Ecology; Production (economics)","score_opus":0.030329160101427912,"score_gpt":0.19719660917270557,"score_spread":0.16686744907127765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105999699","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":[0.4438844,0.006994862,0.19548674,0.038138915,0.0007792025,0.00016133359,0.001594382,0.00045444194,0.31250572],"genre_scores_gemma":[0.96233976,0.002554325,0.00867892,0.001400857,0.0010936464,0.000105341926,0.0002288873,0.00016526274,0.023433069],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99824333,0.0006209803,0.000059759906,0.00032501388,0.00030646933,0.0004445613],"domain_scores_gemma":[0.97142416,0.02163631,0.0022899199,0.0017507632,0.0012620272,0.0016368341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042407434,0.00063351716,0.003034407,0.002237276,0.0027457518,0.004260411,0.0025279664,0.0036835314,0.021105543],"category_scores_gemma":[0.022360386,0.00084606814,0.00181846,0.0022889562,0.008465044,0.009280764,0.0039159153,0.004879822,0.0014754856],"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":[0.000039652932,0.000022769871,0.00077693595,0.000036336634,0.000018480694,0.000060620143,0.0000879967,0.00444672,0.0001179549,0.98776245,0.0037398578,0.0028902867],"study_design_scores_gemma":[0.00006423005,0.000016383903,0.0008284359,0.000020304695,0.000019048066,0.00011714001,0.00009129853,0.015758192,0.00010604104,0.98011655,0.0028403685,0.000022007436],"about_ca_topic_score_codex":0.012452567,"about_ca_topic_score_gemma":0.0072568804,"teacher_disagreement_score":0.021105543,"about_ca_system_score_codex":0.0033188108,"about_ca_system_score_gemma":0.002655987,"threshold_uncertainty_score":0.0706051},"labels":[],"label_agreement":null},{"id":"W2129122815","doi":"10.1016/j.jue.2012.04.001","title":"Are compact cities environmentally friendly?","year":2012,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":230,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Environmentally friendly; Relocation; Economic rent; Compact city; Compact space; Population; Natural resource economics; Economics; Business; Environmental economics; Urban planning; Microeconomics; Ecology; Civil engineering; Engineering; Computer science; Mathematics","score_opus":0.030154963166942297,"score_gpt":0.19395186194819036,"score_spread":0.16379689878124806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129122815","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":[0.9425419,0.0023824393,0.0026483417,0.02187417,0.00016403156,0.000015876627,0.00027522355,0.000021298994,0.030076722],"genre_scores_gemma":[0.997122,0.0007993389,0.00014774526,0.0003958679,0.00011954922,0.0000035434841,0.000044127926,0.0000065222903,0.0013612062],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99930847,0.00019530086,0.000028755328,0.00010999271,0.00016894452,0.00018865213],"domain_scores_gemma":[0.99057907,0.0032334065,0.004186818,0.0004210231,0.0009496203,0.00062992563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008906137,0.00023342767,0.0004675007,0.000706618,0.00065086986,0.0031238354,0.00046512575,0.0015755165,0.0093362965],"category_scores_gemma":[0.009394759,0.00024890623,0.00024296006,0.0012060801,0.003031185,0.0042843614,0.0011003835,0.0008189584,0.0005084312],"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":[0.001371782,0.00048946316,0.40743992,0.00069260213,0.00071032887,0.00144594,0.006728684,0.010705831,0.0034300715,0.39025846,0.023744427,0.15298249],"study_design_scores_gemma":[0.00012368646,0.0003316978,0.45953855,0.00028189446,0.00041756805,0.0009393498,0.03383256,0.0040222863,0.0021613012,0.44232,0.05595025,0.00008086084],"about_ca_topic_score_codex":0.003960528,"about_ca_topic_score_gemma":0.009106504,"teacher_disagreement_score":0.0093362965,"about_ca_system_score_codex":0.000853464,"about_ca_system_score_gemma":0.00046178166,"threshold_uncertainty_score":0.031233013},"labels":[],"label_agreement":null},{"id":"W2129858953","doi":"10.1016/j.jue.2005.05.004","title":"How did location affect adoption of the commercial Internet? Global village vs. urban leadership","year":2005,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"ICT Impact and Policies","field":"Engineering","cited_by":270,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"U.S. Department of Commerce; National Science Foundation","keywords":"The Internet; Frontier; Affect (linguistics); Business; Rural area; Marketing; Geography; Political science; Sociology; Computer science","score_opus":0.024469567590180378,"score_gpt":0.21682383576796146,"score_spread":0.1923542681777811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129858953","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":[0.9943592,0.00009063339,0.00008917874,0.0007336833,0.000009122728,0.000008460937,0.000084239306,0.0000027144715,0.0046227635],"genre_scores_gemma":[0.9994486,0.00003172116,0.000010270753,0.00003098838,0.0000056551366,0.0000020738457,0.0000204595,0.0000016277322,0.00044870944],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989711,0.0005263356,0.000028689423,0.0000803224,0.00008371475,0.00030982096],"domain_scores_gemma":[0.9852905,0.00805025,0.00301436,0.00044291557,0.0011070244,0.0020949075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013581767,0.00010829175,0.00024412386,0.0004933583,0.0004931382,0.0017267853,0.00040783567,0.000720405,0.009413083],"category_scores_gemma":[0.0104371,0.00010699709,0.00029463504,0.00094052707,0.0009335975,0.0010088831,0.0007371602,0.0007820723,0.0007466908],"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":[0.0005835506,0.00052249455,0.9819763,0.00003276272,0.000100538666,0.0003267493,0.0020774629,0.0006751472,0.0004203041,0.0021698505,0.001070275,0.010044576],"study_design_scores_gemma":[0.000032466316,0.00029521773,0.9850551,0.000031780026,0.00009172191,0.00010031603,0.010281447,0.0010482551,0.00033779856,0.00096160633,0.0017502311,0.0000140518105],"about_ca_topic_score_codex":0.013342676,"about_ca_topic_score_gemma":0.021632519,"teacher_disagreement_score":0.013342676,"about_ca_system_score_codex":0.000715441,"about_ca_system_score_gemma":0.0006622394,"threshold_uncertainty_score":0.03148991},"labels":[],"label_agreement":null},{"id":"W2133685987","doi":"10.1016/j.jue.2008.03.001","title":"Ownership forms matter for airport efficiency: A stochastic frontier investigation of worldwide airports","year":2008,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; Washington State University","keywords":"Frontier; Business; Government (linguistics); Panel data; Stochastic frontier analysis; Port (circuit theory); Car ownership; Finance; Public ownership; Private sector; Aviation; Industrial organization; Public economics; Public transport; Economics; Transport engineering; Economic growth; Geography; Microeconomics; Engineering; Econometrics","score_opus":0.03781558285726603,"score_gpt":0.20831259018636875,"score_spread":0.17049700732910272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133685987","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":[0.9975291,0.00007617317,0.0015584725,0.00007922297,0.000001680155,0.0000048724123,0.000071905655,0.000004900503,0.00067372323],"genre_scores_gemma":[0.99935013,0.000047552785,0.00013929939,0.0000047393664,0.0000031000943,0.0000018665381,0.000069911934,0.0000049958394,0.00037839907],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996482,0.00010324962,0.000020383399,0.000052512827,0.00003746314,0.0001382273],"domain_scores_gemma":[0.99089736,0.005954539,0.0015653127,0.00047944268,0.00047955857,0.0006238708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015554375,0.00044858598,0.0008190196,0.00075936044,0.00045315092,0.0027081757,0.00061231764,0.00093519513,0.00563709],"category_scores_gemma":[0.008908925,0.0003696122,0.0012131382,0.0012324009,0.0009144137,0.0027563376,0.0008779253,0.0012233322,0.0003262208],"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":[0.00067917205,0.00046079498,0.6460297,0.0000866312,0.0006534709,0.0010050214,0.0010544927,0.2782098,0.0035747234,0.04721338,0.0016022174,0.019430598],"study_design_scores_gemma":[0.000105366926,0.00058592024,0.52257264,0.00006367654,0.0006909486,0.00044591364,0.004989038,0.42579016,0.0015489982,0.04117441,0.0019255701,0.00010735139],"about_ca_topic_score_codex":0.013254116,"about_ca_topic_score_gemma":0.013303688,"teacher_disagreement_score":0.013254116,"about_ca_system_score_codex":0.0009551758,"about_ca_system_score_gemma":0.00062570564,"threshold_uncertainty_score":0.026353896},"labels":[],"label_agreement":null},{"id":"W2139950021","doi":"10.1016/j.jue.2012.02.001","title":"Step tolling with bottleneck queuing congestion","year":2012,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":101,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"European Research Council; Social Sciences and Humanities Research Council of Canada","keywords":"Toll; Bottleneck; Queueing theory; Interval (graph theory); Computer science; Congestion pricing; Limit (mathematics); Limiting; Queue; Road pricing; Scheme (mathematics); Mathematical optimization; Traffic congestion; Economics; Transport engineering; Mathematics; Engineering; Computer network","score_opus":0.01857008569657123,"score_gpt":0.24787972982835682,"score_spread":0.2293096441317856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139950021","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":[0.5754566,0.00052212697,0.37956128,0.0024979115,0.0005978915,0.00024324418,0.00091037503,0.00079012587,0.039420474],"genre_scores_gemma":[0.98091185,0.000100499434,0.008139507,0.000058603753,0.00005957041,0.00003345848,0.00010182607,0.000037605394,0.010557145],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986628,0.00056217035,0.000038888687,0.00014501647,0.00014662517,0.00044438898],"domain_scores_gemma":[0.994212,0.003965626,0.00029396906,0.00035263822,0.00061693846,0.0005589149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001913334,0.0008082954,0.0019214044,0.0010524642,0.0010120316,0.0020181464,0.0025757758,0.0019063478,0.01946592],"category_scores_gemma":[0.011368936,0.00085871766,0.001077887,0.0013931991,0.0013308827,0.0029396426,0.00199801,0.0018135002,0.0006327339],"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":[0.0007448471,0.00032887128,0.0027401666,0.00017169164,0.00012983842,0.00066752604,0.000098377546,0.84846723,0.0008540658,0.115708224,0.007388748,0.022700388],"study_design_scores_gemma":[0.000057339148,0.00013114614,0.0006722232,0.000009572358,0.000055229724,0.00009682484,0.00010235357,0.9362177,0.00027657402,0.061725207,0.0006307637,0.000025032805],"about_ca_topic_score_codex":0.008050522,"about_ca_topic_score_gemma":0.0063086976,"teacher_disagreement_score":0.01946592,"about_ca_system_score_codex":0.0015708341,"about_ca_system_score_gemma":0.0017814373,"threshold_uncertainty_score":0.06511998},"labels":[],"label_agreement":null},{"id":"W2143311496","doi":"10.1016/j.jue.2008.09.003","title":"Skills in the city","year":2008,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":354,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Economies of agglomeration; Wage; Urbanization; Productivity; Estimation; Economics; Quality (philosophy); Variety (cybernetics); Cognitive skill; Demographic economics; Control (management); Labour economics; Cognition; Microeconomics; Psychology; Economic growth","score_opus":0.0335167053594244,"score_gpt":0.1966425002583556,"score_spread":0.1631257948989312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143311496","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":[0.54114765,0.0020068455,0.00092947186,0.06981019,0.00022273863,0.000029638104,0.00090779865,0.000026211119,0.3849195],"genre_scores_gemma":[0.9802846,0.00050587853,0.000057938523,0.00084535824,0.00009924604,0.0000071537665,0.00010479172,0.0000066109305,0.018088428],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9994634,0.000099973964,0.000011674309,0.00006699017,0.000061174374,0.00029683605],"domain_scores_gemma":[0.9977562,0.00047135667,0.00022322059,0.00008061163,0.00028151603,0.001187134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037778355,0.00012454632,0.00027258543,0.0013880864,0.0026135338,0.0035897882,0.00040917058,0.0010880076,0.025402717],"category_scores_gemma":[0.0026509583,0.00013758679,0.00018717085,0.0020897426,0.0032814806,0.0024912804,0.0023761776,0.0016791215,0.0010716603],"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":[0.000098775236,0.00026177164,0.14159013,0.00009946197,0.00005523188,0.00064040173,0.02052759,0.0018113103,0.00024308823,0.72282887,0.060211055,0.05163236],"study_design_scores_gemma":[0.000063779145,0.000096981144,0.27833858,0.0003465584,0.00005798591,0.00032481286,0.060296983,0.0021181449,0.00031327727,0.26075932,0.39724013,0.000043412212],"about_ca_topic_score_codex":0.10977069,"about_ca_topic_score_gemma":0.16111287,"teacher_disagreement_score":0.10977069,"about_ca_system_score_codex":0.0032921985,"about_ca_system_score_gemma":0.0034988553,"threshold_uncertainty_score":0.2182635},"labels":[],"label_agreement":null},{"id":"W2151423604","doi":"10.1016/j.jue.2011.12.004","title":"Do city climate plans reduce emissions?","year":2011,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Greenhouse gas; Business; Climate change; Environmental planning; Natural resource economics; Climate change mitigation; Environmental resource management; Environmental science; Economics","score_opus":0.17463935632957886,"score_gpt":0.2276967664832074,"score_spread":0.053057410153628554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151423604","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":[0.8447702,0.005283535,0.0022985612,0.09941283,0.0008064185,0.000040671282,0.0019663936,0.000055061526,0.045366313],"genre_scores_gemma":[0.9959934,0.0010759138,0.00014977317,0.0009243626,0.00015044858,0.00000820156,0.0001787688,0.0000059456597,0.0015132015],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993728,0.00031306333,0.000015752166,0.000057167472,0.00008726797,0.00015398608],"domain_scores_gemma":[0.9947962,0.0029168094,0.0013387,0.0001663501,0.0004510933,0.00033082417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012451386,0.00026253,0.0003412139,0.00038355403,0.0003489138,0.0017460556,0.00049078674,0.0014954247,0.0075519104],"category_scores_gemma":[0.008997309,0.00023526498,0.00049694104,0.0010150399,0.0009491538,0.0017053109,0.00041788904,0.0011490262,0.00032597178],"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":[0.005754078,0.0024292744,0.5415673,0.00083058287,0.003037614,0.00063956995,0.0014505459,0.085693434,0.0015174875,0.14225423,0.08090326,0.13392268],"study_design_scores_gemma":[0.0011354525,0.000658067,0.6763665,0.00022926109,0.0020613752,0.00011869025,0.010911498,0.061416212,0.0021982875,0.19385819,0.050937973,0.00010851692],"about_ca_topic_score_codex":0.022688556,"about_ca_topic_score_gemma":0.053302217,"teacher_disagreement_score":0.022688556,"about_ca_system_score_codex":0.0013887031,"about_ca_system_score_gemma":0.0018375497,"threshold_uncertainty_score":0.045113027},"labels":[],"label_agreement":null},{"id":"W2343659739","doi":"10.1016/j.jue.2016.03.008","title":"What is the role of the asking price for a house?","year":2016,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":133,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Economics; Notice; Microeconomics; Bust; Mid price; Factor price; Empirical evidence; Price level; Monetary economics; Boom","score_opus":0.017725815619121225,"score_gpt":0.18955181478803193,"score_spread":0.1718259991689107,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2343659739","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":[0.38691,0.020735776,0.021959914,0.26692963,0.0034904664,0.00008512574,0.0012852018,0.000118873795,0.29848495],"genre_scores_gemma":[0.9841553,0.0017928199,0.0010068073,0.002744206,0.0008984036,0.000014122891,0.00009305609,0.00005005973,0.009245194],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.998579,0.0008302834,0.000041692274,0.00019180567,0.00016587101,0.00019136771],"domain_scores_gemma":[0.98625934,0.008815129,0.0012583794,0.0003754184,0.0018534169,0.0014384014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026920547,0.0002898086,0.0009091629,0.00074085785,0.0013226181,0.005472598,0.0013558213,0.0029948654,0.033618942],"category_scores_gemma":[0.026743308,0.00035107342,0.00043604398,0.0008833005,0.004782731,0.008784293,0.00071324216,0.0024829663,0.0025916314],"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":[0.0004387629,0.00047446604,0.038576834,0.0004261273,0.000108288375,0.0005011807,0.0034909942,0.0015271276,0.0010982445,0.84112597,0.04682209,0.065409966],"study_design_scores_gemma":[0.0001366047,0.00014109781,0.04573491,0.00044259036,0.0002035311,0.0007225142,0.0119282175,0.012155351,0.0011815593,0.85459876,0.07264735,0.000107574495],"about_ca_topic_score_codex":0.013672169,"about_ca_topic_score_gemma":0.010188765,"teacher_disagreement_score":0.033618942,"about_ca_system_score_codex":0.0018455198,"about_ca_system_score_gemma":0.0019086702,"threshold_uncertainty_score":0.11246663},"labels":[],"label_agreement":null},{"id":"W2593858816","doi":"10.1016/j.jue.2018.01.003","title":"When Hotelling Meets Vickrey: Service Timing and Spatial Asymmetry in the Airline Industry","year":2017,"lang":"en","type":"preprint","venue":"Journal of Urban Economics","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Université Laval","funders":"Swenson College of Science and Engineering, University of Minnesota Duluth; Agence Nationale de la Recherche; ITEA; Université Laval","keywords":"Service (business); Economics; Asymmetry; Industrial organization; Business; Microeconomics; Marketing; Physics; Particle physics","score_opus":0.07348268154185647,"score_gpt":0.25815649648313876,"score_spread":0.1846738149412823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593858816","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":[0.9895942,0.0006162801,0.003387332,0.0013188705,0.00003404047,0.0000072158537,0.00031047108,0.000028852048,0.004702576],"genre_scores_gemma":[0.9987192,0.00010513003,0.00018855184,0.000031387895,0.00002074746,0.0000014613645,0.000084444066,0.000008812869,0.00084024377],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961984,0.00009090346,0.00002629106,0.00009185088,0.00007026773,0.000100702266],"domain_scores_gemma":[0.99184376,0.0040054736,0.0023180563,0.0003907084,0.00069418113,0.0007478853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016193743,0.00016055838,0.00062143017,0.0009755777,0.00047045117,0.002921727,0.00065067166,0.0011702675,0.008039806],"category_scores_gemma":[0.014211379,0.00028258152,0.00033819024,0.0013873798,0.0008561351,0.0029021793,0.000734139,0.0012176544,0.0006794177],"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":[0.0025586928,0.00030098108,0.6118244,0.0002819079,0.00033877665,0.001323515,0.003398181,0.035254154,0.009520596,0.22342321,0.014648344,0.09712719],"study_design_scores_gemma":[0.00019643463,0.0002849955,0.52223486,0.0001413819,0.0003983532,0.00096358464,0.011100707,0.16205472,0.0027518133,0.29081398,0.008876035,0.00018316829],"about_ca_topic_score_codex":0.018523399,"about_ca_topic_score_gemma":0.017531916,"teacher_disagreement_score":0.018523399,"about_ca_system_score_codex":0.0010018923,"about_ca_system_score_gemma":0.00068244763,"threshold_uncertainty_score":0.03683114},"labels":[],"label_agreement":null},{"id":"W2732631104","doi":"10.1016/j.jue.2017.06.003","title":"The economics of crowding in rail transit","year":2017,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":93,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; KU Leuven; Agence Nationale de la Recherche","keywords":"Train; Revenue; Marginal cost; Crowding; Transit (satellite); Economics; Microeconomics; Transit system; Welfare; Transport engineering; Crowding out; Public transport; Finance; Monetary economics; Engineering","score_opus":0.024367542496637796,"score_gpt":0.2720718657428885,"score_spread":0.2477043232462507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732631104","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":[0.8671242,0.0055123386,0.04034446,0.022108264,0.00046739305,0.000093614704,0.0008724066,0.00007167619,0.06340571],"genre_scores_gemma":[0.99143136,0.00078882714,0.0005153913,0.00012973834,0.00014848934,0.000012132569,0.000037888636,0.0000101151145,0.0069261817],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99920255,0.00035741102,0.000022647222,0.000069668604,0.000089966605,0.00025786078],"domain_scores_gemma":[0.9957801,0.0027721466,0.0005404044,0.000093804825,0.00025670102,0.0005569462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012730374,0.00044404334,0.00091567874,0.0010605449,0.0012353637,0.003171941,0.00092210417,0.0022068636,0.008479244],"category_scores_gemma":[0.005055101,0.0005607861,0.0006158143,0.0012420813,0.0026885427,0.0030183296,0.0012351667,0.0014107709,0.00032931092],"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":[0.00042729767,0.00022174265,0.011579934,0.00017035202,0.00011683418,0.00072061835,0.00074975874,0.40120414,0.0010170841,0.5539073,0.01446504,0.0154198995],"study_design_scores_gemma":[0.00010144222,0.00015345523,0.015086168,0.00010310261,0.00009132696,0.00022153101,0.0040377644,0.33397496,0.00031619857,0.6356963,0.010115314,0.00010244036],"about_ca_topic_score_codex":0.023550421,"about_ca_topic_score_gemma":0.021255476,"teacher_disagreement_score":0.023550421,"about_ca_system_score_codex":0.003802682,"about_ca_system_score_gemma":0.0011451511,"threshold_uncertainty_score":0.04682666},"labels":[],"label_agreement":null},{"id":"W2802021639","doi":"10.1016/j.jue.2018.04.001","title":"The vertical city: Rent gradients, spatial structure, and agglomeration economies","year":2018,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":86,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Economies of agglomeration; Productivity; Real estate; Horizontal and vertical; Gentrification; Economic rent; Economic geography; Business; Estate; Residential real estate; Economics; Market economy; Geography; Microeconomics; Finance; Economic growth","score_opus":0.017980581053394947,"score_gpt":0.1986546528351268,"score_spread":0.18067407178173184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802021639","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":[0.9829737,0.0016383157,0.0047512534,0.0020081452,0.000016631333,0.000010466148,0.0002959354,0.000012520392,0.0082930215],"genre_scores_gemma":[0.9989588,0.00022287006,0.00023032112,0.000016950056,0.000011278472,0.0000018961169,0.000040801224,0.0000026280452,0.0005142888],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99977475,0.00008359573,0.00000995823,0.000033136224,0.000035207726,0.00006330728],"domain_scores_gemma":[0.99836427,0.00076082104,0.00035892654,0.00009615431,0.00017576813,0.0002440797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003571315,0.00016328087,0.00032885568,0.0009797865,0.00064145005,0.001916158,0.00044497784,0.0005154779,0.0042969557],"category_scores_gemma":[0.003339747,0.00017709873,0.00028248777,0.0021907652,0.0018477311,0.0022601248,0.0013152574,0.0004208337,0.0001497577],"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":[0.00035586586,0.00010008323,0.40847263,0.000089002286,0.00018617457,0.00027366428,0.0012812436,0.021619722,0.0005346808,0.535079,0.0041346354,0.027873334],"study_design_scores_gemma":[0.000102338934,0.0001117295,0.41104206,0.00011078212,0.0002850472,0.00042830338,0.0068760673,0.07005611,0.0004033815,0.49975538,0.010772568,0.000056346977],"about_ca_topic_score_codex":0.036296137,"about_ca_topic_score_gemma":0.051906258,"teacher_disagreement_score":0.036296137,"about_ca_system_score_codex":0.0011659063,"about_ca_system_score_gemma":0.0006229298,"threshold_uncertainty_score":0.07216972},"labels":[],"label_agreement":null},{"id":"W2905151575","doi":"10.1016/j.jue.2021.103394","title":"Who lives where in the city? Amenities, commuting and income sorting","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Institut Universitaire de France; National Research University Higher School of Economics; Agence Nationale de la Recherche","keywords":"Amenity; Sorting; Homothetic transformation; Economics; Geography; News aggregator; Econometrics; Mathematics; Computer science","score_opus":0.03051017279306667,"score_gpt":0.20773546521676067,"score_spread":0.177225292423694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905151575","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":[0.9931837,0.00094226847,0.00021208958,0.002658566,0.00002576698,0.000007067441,0.00025093622,0.0000030456865,0.0027164791],"genre_scores_gemma":[0.9983374,0.00029587396,0.00005369507,0.00007890254,0.00003312928,0.0000033257218,0.000092227245,0.0000022291756,0.0011032542],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948597,0.00018316472,0.000031100768,0.000059771846,0.00004920549,0.0001907211],"domain_scores_gemma":[0.9933662,0.0029881832,0.0015756811,0.00026007494,0.00038496454,0.0014248504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009717668,0.00017600802,0.0005650411,0.0011518954,0.0010009296,0.0019759443,0.0007398433,0.0013770425,0.01034441],"category_scores_gemma":[0.005605609,0.00022775191,0.000669066,0.0029085362,0.0016467927,0.0020653356,0.0010667442,0.0011011264,0.00079379114],"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":[0.00029099203,0.0003071806,0.9803357,0.0000395098,0.00020007943,0.0001942031,0.0010467968,0.0009679136,0.00009595797,0.0045030694,0.0016939866,0.010324721],"study_design_scores_gemma":[0.0000368754,0.00016158746,0.9590099,0.00008836581,0.00025146827,0.00018707238,0.019876754,0.0033245245,0.000079208025,0.014610467,0.0023401852,0.000033622506],"about_ca_topic_score_codex":0.06903718,"about_ca_topic_score_gemma":0.11527921,"teacher_disagreement_score":0.06903718,"about_ca_system_score_codex":0.00076394214,"about_ca_system_score_gemma":0.00094973587,"threshold_uncertainty_score":0.13727063},"labels":[],"label_agreement":null},{"id":"W2916744130","doi":"10.1016/j.jue.2020.103266","title":"On the economic impacts of constraining second home investments","year":2020,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Economic and Social Research Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Amenity; Backlash; Inequality; Economics; Tourism; Unemployment; Exploit; Natural experiment; Labour economics; Economic growth; Geography; Finance","score_opus":0.029474466087398617,"score_gpt":0.2517363679970561,"score_spread":0.2222619019096575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916744130","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":[0.9271351,0.0009559192,0.00061272195,0.0059947968,0.00007936969,0.000025838264,0.0006588408,0.000014404221,0.064523116],"genre_scores_gemma":[0.9973686,0.00031603576,0.000039831415,0.00015877158,0.000020298936,0.000006085164,0.000062415325,0.0000035356472,0.0020244285],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99914527,0.00024243096,0.000023839048,0.00003966634,0.00006413864,0.00048474103],"domain_scores_gemma":[0.9908174,0.006194034,0.0011604564,0.00022181816,0.0006445631,0.0009616743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016050594,0.00032868673,0.00057437405,0.00065780256,0.0009808793,0.0038630243,0.0006556638,0.001997094,0.019620834],"category_scores_gemma":[0.009362663,0.0002700097,0.000516119,0.0012422587,0.0013904393,0.0015246556,0.0015445991,0.0020748165,0.0004625604],"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":[0.004254051,0.0026733177,0.22222267,0.00056231127,0.0004988864,0.0050913137,0.0021671972,0.25991476,0.0037892465,0.40624842,0.027054928,0.06552288],"study_design_scores_gemma":[0.00062241824,0.0018906584,0.48448545,0.0007577116,0.0011373279,0.0006698033,0.040758733,0.10771558,0.0039473516,0.29248512,0.06525998,0.00026986265],"about_ca_topic_score_codex":0.03242487,"about_ca_topic_score_gemma":0.057887107,"teacher_disagreement_score":0.03242487,"about_ca_system_score_codex":0.0029366098,"about_ca_system_score_gemma":0.0019561204,"threshold_uncertainty_score":0.065638244},"labels":[],"label_agreement":null},{"id":"W2939107364","doi":"10.1016/j.jue.2021.103405","title":"Not in my neighbour’s back yard? Laneway homes and neighbours’ property values","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; National University of Singapore","keywords":"Zoning; Renting; Neighbourhood (mathematics); Externality; Spillover effect; Yard; Single family; Exploit; Business; Residential property; Property value; Property (philosophy); Demographic economics; Economic geography; Economics; Microeconomics; Finance; Computer science; Political science; Law; Mathematics","score_opus":0.02783945539509908,"score_gpt":0.20362251267992232,"score_spread":0.17578305728482324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2939107364","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":[0.98078704,0.00048324847,0.00007869203,0.003495278,0.000032487995,0.0000019257284,0.00015029819,0.0000014441098,0.014969476],"genre_scores_gemma":[0.9981698,0.00009203097,0.000014698773,0.00006943033,0.000013886159,0.0000010889132,0.000048525315,0.0000017501989,0.0015887124],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995548,0.00017315695,0.000016728944,0.000045435576,0.000077815406,0.00013202641],"domain_scores_gemma":[0.9937827,0.0015977343,0.0020757737,0.00021774293,0.0005910149,0.0017349562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061170076,0.00009100143,0.0001904353,0.0006503385,0.000983418,0.0024178063,0.00053733523,0.0007213806,0.009778957],"category_scores_gemma":[0.0063871946,0.00017321647,0.00024566115,0.0014897742,0.001675992,0.0021584702,0.00091744977,0.0015301097,0.0006376642],"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":[0.00014271475,0.00021978226,0.96610886,0.00001974947,0.00012330855,0.00030467976,0.007966837,0.00031332503,0.000056527177,0.009212074,0.004425579,0.0111064995],"study_design_scores_gemma":[0.00001238912,0.00005780373,0.9339559,0.000052671414,0.00004824434,0.0002444782,0.051445223,0.0003942537,0.000051122795,0.006355115,0.007357113,0.000025622694],"about_ca_topic_score_codex":0.06427256,"about_ca_topic_score_gemma":0.14485225,"teacher_disagreement_score":0.06427256,"about_ca_system_score_codex":0.0012204662,"about_ca_system_score_gemma":0.00048022834,"threshold_uncertainty_score":0.12779689},"labels":[],"label_agreement":null},{"id":"W2967245124","doi":"10.1016/j.jue.2021.103366","title":"The internal spatial organization of firms: Evidence from Denmark","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":20,"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":"Rotman School of Management, University of Toronto","keywords":"Business; Production (economics); Danish; Fragmentation (computing); Industrial organization; Labour economics; Economics","score_opus":0.02194795830376564,"score_gpt":0.19736045594321736,"score_spread":0.17541249763945171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967245124","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":[0.99333787,0.0008306017,0.0003018209,0.00011184735,0.000004702298,0.000007082385,0.0009928064,0.000005195721,0.004407985],"genre_scores_gemma":[0.99830437,0.0003473255,0.00012025757,0.000011662239,0.0000022834004,0.000002326867,0.0007482356,0.0000027212911,0.00046075307],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99874854,0.00024426493,0.00013493361,0.00028739916,0.00024641844,0.00033837688],"domain_scores_gemma":[0.9912649,0.0036622062,0.0026860817,0.00069306314,0.0011485517,0.00054513034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012228313,0.00021334454,0.00048651037,0.0018849676,0.0008964182,0.0024704481,0.000671851,0.0005628762,0.0024370898],"category_scores_gemma":[0.005437614,0.0003857553,0.00048046943,0.0035935391,0.0014900289,0.0009957895,0.0017955996,0.00036046683,0.00034706478],"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":[0.00050835335,0.00014481507,0.96613955,0.00032910713,0.00042553007,0.000560025,0.0049391855,0.0049412274,0.000874466,0.008202584,0.0015374024,0.0113977175],"study_design_scores_gemma":[0.000021523721,0.000062617335,0.9823846,0.00011264167,0.00017701581,0.00010306754,0.009732723,0.0012922107,0.00061629346,0.0011270427,0.00434449,0.000025733512],"about_ca_topic_score_codex":0.16781357,"about_ca_topic_score_gemma":0.19841851,"teacher_disagreement_score":0.16781357,"about_ca_system_score_codex":0.0021957846,"about_ca_system_score_gemma":0.0016016893,"threshold_uncertainty_score":0.3336736},"labels":[],"label_agreement":null},{"id":"W2967972676","doi":"10.1016/j.jue.2019.103189","title":"Using purchase restrictions to cool housing markets: A within-market analysis","year":2019,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Real estate; Exploit; Common value auction; Business; Database transaction; Government (linguistics); Supply and demand; Economics; Relative price; Public economics; Microeconomics; Finance","score_opus":0.03203783843746191,"score_gpt":0.2296764367029736,"score_spread":0.1976385982655117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967972676","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":[0.9555843,0.0007472297,0.02751718,0.0009598669,0.00008435397,0.00015812479,0.000667348,0.00013427685,0.014147273],"genre_scores_gemma":[0.9920139,0.00029252935,0.0018843784,0.000088239685,0.00013986901,0.000053728265,0.0005172635,0.00006566071,0.004944417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99675316,0.0017239545,0.0001260895,0.00032983773,0.00034658628,0.0007203837],"domain_scores_gemma":[0.9239359,0.06101887,0.007397078,0.0035121443,0.002210708,0.0019252738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006797496,0.0008515457,0.0024965792,0.0016342261,0.0009881712,0.0048313285,0.0029700468,0.0015927713,0.02413565],"category_scores_gemma":[0.037026472,0.00096449204,0.0026991372,0.0016835027,0.003614955,0.0075239004,0.0029896477,0.003888931,0.0006407342],"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":[0.0034540135,0.003915717,0.2470276,0.0007875483,0.002470608,0.002149059,0.0020758945,0.27577126,0.0030541008,0.39241138,0.012310569,0.05457215],"study_design_scores_gemma":[0.00052565784,0.0015683982,0.113596976,0.000121406556,0.0013677556,0.00033103916,0.0037962645,0.7262479,0.0024024989,0.14107452,0.008701089,0.0002664608],"about_ca_topic_score_codex":0.019468162,"about_ca_topic_score_gemma":0.015134659,"teacher_disagreement_score":0.02413565,"about_ca_system_score_codex":0.0014904907,"about_ca_system_score_gemma":0.0015775873,"threshold_uncertainty_score":0.08074176},"labels":[],"label_agreement":null},{"id":"W2973202589","doi":"10.1016/j.jue.2021.103370","title":"The amplifying effect of capitalization rates on housing supply","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":24,"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 Laval","funders":"Economic and Social Research Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Capitalization; Subsidy; Renting; Differential (mechanical device); Rental housing; Economics; Price elasticity of supply; Labour economics; Business; Monetary economics; Microeconomics; Price elasticity of demand; Market economy","score_opus":0.016643971714225637,"score_gpt":0.21395538979623083,"score_spread":0.1973114180820052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973202589","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":[0.9855611,0.00017040255,0.0050101294,0.00020018542,0.000012547411,0.0000199629,0.00015897282,0.000058632497,0.008808129],"genre_scores_gemma":[0.9991002,0.00004318574,0.0002785024,0.000020793215,0.000011027103,0.000003814217,0.000029009216,0.0000046742616,0.0005088599],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994783,0.00011295411,0.000035415094,0.00014672194,0.00013082629,0.000095813644],"domain_scores_gemma":[0.9944174,0.0025726634,0.0016612819,0.0006855677,0.00044894475,0.00021410592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005831623,0.0002261058,0.00029389438,0.00034734828,0.00020520441,0.00083827256,0.00031137723,0.00040195743,0.0053723566],"category_scores_gemma":[0.005801988,0.00023999235,0.00036130525,0.00026498133,0.0006595599,0.00060673314,0.0008650986,0.000535402,0.000513096],"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":[0.0015378711,0.0005076669,0.60458493,0.0004388562,0.00030287096,0.0017781679,0.0021897887,0.036738597,0.22593927,0.027957652,0.0021492268,0.095875174],"study_design_scores_gemma":[0.00002665621,0.00035671837,0.94898254,0.00002715128,0.00007616835,0.00036302969,0.00052047777,0.015816147,0.021419138,0.009374627,0.0029920647,0.00004526584],"about_ca_topic_score_codex":0.0017550905,"about_ca_topic_score_gemma":0.0012215531,"teacher_disagreement_score":0.0053723566,"about_ca_system_score_codex":0.0005066557,"about_ca_system_score_gemma":0.0001994897,"threshold_uncertainty_score":0.01797229},"labels":[],"label_agreement":null},{"id":"W2989665068","doi":"10.1016/j.jue.2019.103214","title":"Transition to the property tax in China: A dynamic general equilibrium analysis","year":2019,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Economics; Tax reform; Tax credit; Ad valorem tax; Value-added tax; Microeconomics; Tax revenue; Indirect tax; Property tax; Public economics; Revenue; Counterfactual thinking; Finance","score_opus":0.010259463844115782,"score_gpt":0.19024131204620992,"score_spread":0.17998184820209415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989665068","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":[0.96706575,0.00062609516,0.014908617,0.00347462,0.00009335376,0.00012129997,0.00110965,0.00013503912,0.01246554],"genre_scores_gemma":[0.98820275,0.0004205951,0.0006358772,0.00012517092,0.000063490676,0.000031641197,0.0003413266,0.00004087017,0.010138413],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99946195,0.00009322069,0.000016736452,0.0001039827,0.000043810487,0.00028035865],"domain_scores_gemma":[0.9988317,0.00042808117,0.0001733708,0.00005678787,0.00022377298,0.00028635468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013845111,0.0007761277,0.0027003144,0.0014597852,0.0015169544,0.0032372738,0.0022898274,0.0025072775,0.011030739],"category_scores_gemma":[0.003139111,0.00080937444,0.0021667434,0.0013247442,0.0017183217,0.003272707,0.0014678604,0.001983709,0.00044723912],"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":[0.00039976582,0.00039530665,0.020893617,0.00013867929,0.00023427511,0.0014536945,0.00045814694,0.7631711,0.0011865349,0.19521089,0.009089947,0.007368037],"study_design_scores_gemma":[0.00010406378,0.00006607301,0.0070326244,0.000015181134,0.00012297522,0.00004853031,0.00026690654,0.9656028,0.00012716984,0.02569874,0.00087471475,0.000040213476],"about_ca_topic_score_codex":0.2521982,"about_ca_topic_score_gemma":0.122024015,"teacher_disagreement_score":0.2521982,"about_ca_system_score_codex":0.0053368127,"about_ca_system_score_gemma":0.0062281713,"threshold_uncertainty_score":0.50146043},"labels":[],"label_agreement":null},{"id":"W2989833147","doi":"10.1016/j.jue.2019.103227","title":"Cities in China","year":2019,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Economic Zones and Regional Development","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"China; Economics; Economic geography; Geography; Archaeology","score_opus":0.014719443709844298,"score_gpt":0.17270070514177302,"score_spread":0.15798126143192873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989833147","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":[0.96866333,0.0015950076,0.00025097787,0.0018996305,0.000068938345,0.000040892515,0.004300225,0.000048344715,0.023132775],"genre_scores_gemma":[0.9915558,0.00042818292,0.0000864837,0.0000747357,0.000020051637,0.000017195802,0.0015220261,0.000004245816,0.0062911813],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995659,0.000039902578,0.000030438086,0.0000911138,0.000078708166,0.00019386901],"domain_scores_gemma":[0.99965465,0.000016952708,0.00007708291,0.000018308585,0.00010556693,0.00012739062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021021396,0.00032757493,0.00031959123,0.0027525732,0.0019703459,0.0015869281,0.0004254577,0.0002789031,0.0068148444],"category_scores_gemma":[0.00037824412,0.00023011542,0.00036991076,0.0061337883,0.0005715028,0.0007306423,0.0012982999,0.0003143837,0.0003844467],"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":[0.00016156268,0.0001069198,0.9147108,0.00023401479,0.00018097338,0.0009711722,0.002855286,0.0028578877,0.0006419715,0.022197114,0.021935927,0.0331464],"study_design_scores_gemma":[0.000023008011,0.00002476605,0.97494614,0.000025366735,0.00006480081,0.00007264119,0.0026766346,0.0020036134,0.0001048296,0.0012190457,0.018819883,0.00001927458],"about_ca_topic_score_codex":0.2965157,"about_ca_topic_score_gemma":0.4587895,"teacher_disagreement_score":0.2965157,"about_ca_system_score_codex":0.0051290477,"about_ca_system_score_gemma":0.00886832,"threshold_uncertainty_score":0.5895796},"labels":[],"label_agreement":null},{"id":"W2989900365","doi":"10.1016/j.jue.2021.103329","title":"Water purification efforts and the black‐white infant mortality gap, 1906–1938","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Novo Nordisk Fonden; Danmarks Grundforskningsfond; Eunice Kennedy Shriver National Institute of Child Health and Human Development; University of Washington","keywords":"Infant mortality; White (mutation); Census; Demography; Water supply; Environmental health; Diarrhea; Black women; Geography; Medicine; Environmental science; Environmental engineering; Population; Chemistry; Sociology","score_opus":0.030860525347996385,"score_gpt":0.2661545493075222,"score_spread":0.2352940239595258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989900365","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":[0.990261,0.0013125914,0.00009198865,0.0017718252,0.00006126345,0.0000048778934,0.00089252164,0.000003132182,0.005600825],"genre_scores_gemma":[0.99657565,0.00064207544,0.000032842265,0.00010441392,0.000039698803,0.000007116551,0.000300094,0.0000027844058,0.0022953677],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999747,0.00004150889,0.000013209243,0.000035198922,0.000025049865,0.0001380202],"domain_scores_gemma":[0.9995196,0.00006417308,0.0001803641,0.000018558392,0.00010375749,0.00011356431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004996939,0.00013915663,0.00016771237,0.0006810575,0.0009864146,0.00050546526,0.00037607944,0.0005498257,0.0019164189],"category_scores_gemma":[0.001421891,0.00013317927,0.0002278047,0.0011243819,0.00050788437,0.00054292835,0.0008630842,0.0011470966,0.00020901837],"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":[0.00072737626,0.00035369012,0.91294926,0.00012063587,0.0001477395,0.00068129547,0.0144398175,0.00040010732,0.0010965533,0.014756498,0.0060255015,0.048301503],"study_design_scores_gemma":[0.0000058576798,0.000088489716,0.9856156,0.00004177547,0.00002550889,0.00007522598,0.0032651676,0.00016815009,0.00030120768,0.00022205764,0.010183492,0.000007380774],"about_ca_topic_score_codex":0.14824755,"about_ca_topic_score_gemma":0.29845816,"teacher_disagreement_score":0.14824755,"about_ca_system_score_codex":0.0011227749,"about_ca_system_score_gemma":0.0009436808,"threshold_uncertainty_score":0.2947693},"labels":[],"label_agreement":null},{"id":"W3107305927","doi":"10.1016/j.jue.2020.103300","title":"Commuting and innovation: Are closer inventors more productive?","year":2020,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"Wharton School, University of Pennsylvania; Harvard Business School","keywords":"Telecommuting; Productivity; Exploit; Identification (biology); Coronavirus disease 2019 (COVID-19); Labour economics; Demographic economics; Work (physics); Quality (philosophy); Construct (python library); Social distance; Economic geography; Economics; Business; Economic growth; Engineering; Computer science; Computer security","score_opus":0.0758971078806034,"score_gpt":0.23564652712705939,"score_spread":0.15974941924645597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107305927","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":[0.95925105,0.007761945,0.0010447748,0.009140142,0.00014833157,0.000022119882,0.0002966904,0.000012101292,0.022322904],"genre_scores_gemma":[0.9953838,0.0014434981,0.00010926605,0.0003884146,0.00024195263,0.0000050748804,0.0000516156,0.0000050392014,0.002371241],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904746,0.00026486625,0.00006353578,0.00022929304,0.00013400693,0.00026095644],"domain_scores_gemma":[0.9687506,0.015474566,0.008529616,0.0015387533,0.001572057,0.004134344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025175535,0.0002034002,0.00070727116,0.001236113,0.0008579714,0.0036296176,0.00073089544,0.0023015998,0.024218509],"category_scores_gemma":[0.015946373,0.00018250699,0.0005779832,0.0018266514,0.0024631722,0.0048049325,0.00090083247,0.0012232898,0.0010326471],"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":[0.00068866456,0.0008342415,0.8272042,0.00033440237,0.0003567826,0.00061208266,0.0046653403,0.0012069537,0.00073291705,0.051870145,0.0046541304,0.10684013],"study_design_scores_gemma":[0.000111487185,0.00033669715,0.89515793,0.00031726158,0.0003643789,0.00048206764,0.017622722,0.0012589466,0.0003716374,0.070882134,0.013047543,0.000047173387],"about_ca_topic_score_codex":0.0064111645,"about_ca_topic_score_gemma":0.008270753,"teacher_disagreement_score":0.024218509,"about_ca_system_score_codex":0.00080607133,"about_ca_system_score_gemma":0.00080594345,"threshold_uncertainty_score":0.081018925},"labels":[],"label_agreement":null},{"id":"W3118170049","doi":"10.1016/j.jue.2020.103313","title":"Market tremors: Shale gas exploration, earthquakes, and their impact on house prices","year":2020,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":20,"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":"Smithsonian Environmental Research Center; Economic and Social Research Council; University of Bristol","keywords":"Shale gas; House price; Oil shale; Hydraulic fracturing; Economics; Petroleum engineering; Geology; Natural resource economics; Monetary economics; Paleontology","score_opus":0.03758102429846,"score_gpt":0.20362638740140732,"score_spread":0.16604536310294732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118170049","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":[0.99089867,0.0007018944,0.0002064113,0.0021972056,0.000033027256,0.000005636691,0.0002574051,0.000009479539,0.0056902054],"genre_scores_gemma":[0.9986547,0.00017613663,0.000016506023,0.00006719314,0.00003530771,0.0000016415499,0.0001024024,0.0000022016488,0.0009437666],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996836,0.00010186239,0.000015447138,0.000034939247,0.00008162619,0.00008252231],"domain_scores_gemma":[0.9947654,0.0017526327,0.0024819942,0.00010075351,0.0002953236,0.0006039079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038593682,0.00016651681,0.00021064814,0.00040425386,0.0003170581,0.001374542,0.0002327556,0.0007803652,0.008237858],"category_scores_gemma":[0.003998772,0.000112901645,0.00047054084,0.00071080786,0.00065371307,0.0009860665,0.00060535525,0.0010520557,0.00048794382],"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":[0.00034866165,0.0003360244,0.9772768,0.000055824927,0.0002470439,0.00064748566,0.0005775671,0.002024385,0.00057505316,0.0034192626,0.0031903735,0.011301541],"study_design_scores_gemma":[0.000011258619,0.00012441429,0.99394,0.000011972959,0.00005311857,0.000053045926,0.0011876591,0.002067534,0.000234209,0.00095413445,0.0013529311,0.000009768634],"about_ca_topic_score_codex":0.018085409,"about_ca_topic_score_gemma":0.020826884,"teacher_disagreement_score":0.018085409,"about_ca_system_score_codex":0.00080630794,"about_ca_system_score_gemma":0.00034848414,"threshold_uncertainty_score":0.035960317},"labels":[],"label_agreement":null},{"id":"W3123073499","doi":"10.1016/j.jue.2010.07.003","title":"Competition in law enforcement and capital allocation","year":2010,"lang":"en","type":"preprint","venue":"Journal of Urban Economics","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Université du Québec à Montréal","funders":"Universitat de Barcelona; Brock University; Queen's University; Universitat de Girona","keywords":"Capital allocation line; Jurisdiction; Capital (architecture); Investment (military); Competition (biology); Law enforcement; Economics; Microeconomics; Business; Monetary economics; Law; Political science","score_opus":0.019679151105593068,"score_gpt":0.20225015408337155,"score_spread":0.18257100297777848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123073499","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":[0.72537845,0.00965242,0.052306693,0.053359505,0.00054640713,0.00010132053,0.0005393907,0.00010627661,0.1580096],"genre_scores_gemma":[0.98728997,0.001215018,0.00067718903,0.00036126873,0.00022541085,0.000014497397,0.00005116592,0.000011405038,0.010154067],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988368,0.00048382208,0.000049666418,0.00014102037,0.0001225573,0.00036620273],"domain_scores_gemma":[0.98876977,0.008080815,0.0013574115,0.00028961588,0.00072193856,0.00078041933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022991323,0.00035794114,0.0013141969,0.0012501285,0.0014768682,0.004928393,0.00094550324,0.003271617,0.017249485],"category_scores_gemma":[0.011700028,0.0005089282,0.0005118755,0.0017699964,0.0039171525,0.00415561,0.0012999821,0.00228319,0.0005765093],"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":[0.00012769981,0.00022421249,0.008945935,0.000080981496,0.00006283168,0.0002601342,0.00029082235,0.03353677,0.00023830269,0.9367557,0.009199193,0.010277504],"study_design_scores_gemma":[0.000087129614,0.000029369432,0.0066386345,0.000041159823,0.000033959623,0.00006275806,0.00065750536,0.059191506,0.00010861328,0.9293725,0.0037506605,0.000026230404],"about_ca_topic_score_codex":0.02405049,"about_ca_topic_score_gemma":0.023122173,"teacher_disagreement_score":0.02405049,"about_ca_system_score_codex":0.004149482,"about_ca_system_score_gemma":0.0034858184,"threshold_uncertainty_score":0.057705283},"labels":[],"label_agreement":null},{"id":"W3123207136","doi":"10.1016/j.jue.2010.06.002","title":"Thieves, thugs, and neighborhood poverty","year":2010,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":31,"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; York University","funders":"Social Sciences and Humanities Research Council of Canada; Rheinische Friedrich-Wilhelms-Universität Bonn","keywords":"Poverty; Economics; Economic growth","score_opus":0.016219175661438993,"score_gpt":0.2806458556390312,"score_spread":0.2644266799775922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123207136","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":[0.9347987,0.0018811724,0.00038501594,0.014994324,0.00015775696,0.0000224549,0.00022745704,0.000012432745,0.04752057],"genre_scores_gemma":[0.9951657,0.0006011675,0.00013042362,0.00022588113,0.000022935108,0.0000070275755,0.00003352675,0.000003065106,0.0038102472],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993298,0.00029974472,0.000022657108,0.00004532098,0.00009494219,0.0002075683],"domain_scores_gemma":[0.9980762,0.00044137854,0.000409025,0.00013994792,0.0002455961,0.0006878559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014051775,0.00014653255,0.0002688999,0.0008522751,0.0024306492,0.001782966,0.00043598327,0.0007373991,0.01164375],"category_scores_gemma":[0.007133911,0.00012538629,0.00017332255,0.0007078282,0.0019366052,0.0011834984,0.001631444,0.0010260146,0.00039920682],"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":[0.00070081535,0.0014517243,0.5991463,0.00015655805,0.00014693095,0.0009691748,0.023733523,0.0016986837,0.00048558647,0.2333588,0.028783562,0.109368354],"study_design_scores_gemma":[0.00014098322,0.00054548524,0.6671394,0.0005174574,0.0001514693,0.0010400276,0.096458815,0.003998107,0.00063873635,0.12274063,0.10657034,0.00005856711],"about_ca_topic_score_codex":0.031186657,"about_ca_topic_score_gemma":0.054918617,"teacher_disagreement_score":0.031186657,"about_ca_system_score_codex":0.0014305325,"about_ca_system_score_gemma":0.0010031535,"threshold_uncertainty_score":0.06201029},"labels":[],"label_agreement":null},{"id":"W3134339146","doi":"10.1016/j.jue.2021.103328","title":"JUE Insight: Measuring movement and social contact with smartphone data: a real-time application to COVID-19","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":95,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Division of Social and Economic Sciences","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Index (typography); Movement (music); Tracking (education); Scale (ratio); Computer science; Cover (algebra); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Population; Social contact; Geography; Cartography; Engineering; Psychology; World Wide Web; Medicine; Environmental health","score_opus":0.20573786505393757,"score_gpt":0.3599804081407099,"score_spread":0.15424254308677235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134339146","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":[0.28214896,0.0011951025,0.11360762,0.001994623,0.00083741883,0.0028146014,0.51592183,0.048579972,0.03289986],"genre_scores_gemma":[0.5786719,0.00069750997,0.21918452,0.00074471516,0.00033907924,0.0035429741,0.16808333,0.0022201953,0.026515858],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9992592,0.00024609105,0.00007905362,0.00014795466,0.00020269441,0.00006495633],"domain_scores_gemma":[0.99767345,0.00094946136,0.00031873977,0.00042587833,0.00033814253,0.0002943549],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001139363,0.0008393748,0.0008066772,0.0022107752,0.00033793916,0.0011443812,0.0008946328,0.0008293956,0.01846008],"category_scores_gemma":[0.0074059716,0.00040865198,0.0005646723,0.0019269822,0.00020488085,0.0009396958,0.0022347355,0.0005439026,0.00593207],"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":[0.004452711,0.001511374,0.30455178,0.0025408797,0.0013181256,0.0009837002,0.0031778512,0.010092358,0.013554997,0.013134515,0.31331953,0.33136228],"study_design_scores_gemma":[0.0013144235,0.0012736063,0.5752248,0.0005511942,0.0006102327,0.0014578016,0.0026582133,0.19422191,0.014023714,0.019122751,0.1889027,0.0006386553],"about_ca_topic_score_codex":0.008105652,"about_ca_topic_score_gemma":0.01630491,"teacher_disagreement_score":0.01846008,"about_ca_system_score_codex":0.00033284345,"about_ca_system_score_gemma":0.0005550676,"threshold_uncertainty_score":0.06175506},"labels":[],"label_agreement":null},{"id":"W3179103999","doi":"10.1016/j.jue.2021.103373","title":"JUE Insight: The geography of pandemic containment","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Toll; Welfare; Pandemic; Containment (computer programming); Economics; Coronavirus disease 2019 (COVID-19); State (computer science); Public economics; Market economy; Computer science","score_opus":0.15693168797861812,"score_gpt":0.35125416366283924,"score_spread":0.19432247568422112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179103999","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":[0.093896665,0.011199932,0.15523726,0.21476275,0.0016977937,0.000094484196,0.0022266642,0.00038280958,0.5205017],"genre_scores_gemma":[0.9535013,0.004042065,0.01224551,0.002743955,0.00091690745,0.00005529657,0.0002701152,0.00015454373,0.026070217],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.999166,0.00040880794,0.000023346025,0.0001417868,0.00014720735,0.000112812144],"domain_scores_gemma":[0.9968495,0.001737814,0.00039960688,0.0004378159,0.00035023165,0.00022505537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011646476,0.00042795137,0.00083931553,0.0021179214,0.0016580587,0.006479021,0.000996004,0.0025299138,0.023660209],"category_scores_gemma":[0.012799294,0.0003501659,0.0005700845,0.0025798266,0.0056079114,0.012424048,0.0029669448,0.0028993934,0.0013693379],"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":[0.000010656953,0.0000059467347,0.0003431921,0.000015433898,0.0000050617073,0.000027336358,0.00015173454,0.0010193976,0.00003218394,0.991742,0.0037954515,0.0028517216],"study_design_scores_gemma":[0.0000071548493,0.000004503878,0.00040332385,0.00001905187,0.0000044319086,0.0000417855,0.00033262972,0.00189239,0.00002628368,0.98458374,0.012679771,0.000004972637],"about_ca_topic_score_codex":0.009760234,"about_ca_topic_score_gemma":0.0061065992,"teacher_disagreement_score":0.023660209,"about_ca_system_score_codex":0.002967619,"about_ca_system_score_gemma":0.0015399422,"threshold_uncertainty_score":0.07915127},"labels":[],"label_agreement":null},{"id":"W3182639363","doi":"10.1016/j.jue.2021.103381","title":"JUE insight: Are city centers losing their appeal? Commercial real estate, urban spatial structure, and COVID-19","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":168,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Real estate; Land Values; Transit (satellite); Business; Economic rent; Mile; Shock (circulatory); Property value; Economic geography; Geography; Economics; Finance; Public transport; Land use; Transport engineering; Market economy","score_opus":0.035748043289114656,"score_gpt":0.22073417120321837,"score_spread":0.1849861279141037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3182639363","genre_codex":"commentary","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":[0.11587916,0.005796341,0.004733941,0.6439852,0.0017198898,0.000035156267,0.0015948256,0.00011832696,0.22613712],"genre_scores_gemma":[0.9433772,0.0017109,0.0005734602,0.021304814,0.0012700513,0.00001647729,0.00028443054,0.00006762192,0.031395186],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9988783,0.0003172836,0.000037451853,0.00020029918,0.00031639886,0.00025021762],"domain_scores_gemma":[0.9916082,0.003242942,0.0012414911,0.0006292825,0.002395858,0.00088216685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002386032,0.0002731721,0.0006331822,0.0020039226,0.0022260924,0.0076341745,0.0011929276,0.0035779355,0.04424085],"category_scores_gemma":[0.019626321,0.00018928286,0.00033108666,0.0021154548,0.0055618384,0.00990348,0.0021297096,0.0044829845,0.0026336436],"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":[0.00027849543,0.00018785824,0.05951155,0.000093614566,0.00009610878,0.0004058162,0.004858249,0.00065342843,0.00015508514,0.67645365,0.20006903,0.057237267],"study_design_scores_gemma":[0.00010920953,0.00006152317,0.08098781,0.00042215275,0.00013995326,0.00037785905,0.032961883,0.004227446,0.00027983164,0.63330173,0.24703507,0.00009556179],"about_ca_topic_score_codex":0.049522184,"about_ca_topic_score_gemma":0.06266548,"teacher_disagreement_score":0.049522184,"about_ca_system_score_codex":0.0035565642,"about_ca_system_score_gemma":0.0025071786,"threshold_uncertainty_score":0.14800042},"labels":[],"label_agreement":null},{"id":"W4214671596","doi":"10.1016/j.jue.2022.103428","title":"The Spread and Consequences of COVID-19 for Cities: An Introduction","year":2022,"lang":"en","type":"editorial","venue":"Journal of Urban Economics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Virology; Economic geography; Economics; Medicine; Outbreak; Infectious disease (medical specialty); Disease","score_opus":0.13894904957037324,"score_gpt":0.39017145575368467,"score_spread":0.25122240618331143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214671596","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000032273172,0.029950557,0.00030174956,0.063058086,0.90462494,0.000011959002,0.00006201826,0.000018661864,0.001939745],"genre_scores_gemma":[0.00052327133,0.016183075,0.00020073536,0.013136968,0.96612877,0.000021917402,0.000023970419,0.000026161795,0.003755101],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99381375,0.0018664089,0.0010099771,0.0006267889,0.0023997617,0.00028325885],"domain_scores_gemma":[0.9562227,0.027867865,0.0015220464,0.00091408525,0.01146147,0.0020118863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012716826,0.0038708888,0.0027993757,0.008211666,0.0034413943,0.01153408,0.003486524,0.016385216,0.008962223],"category_scores_gemma":[0.044407427,0.00089816016,0.0026753193,0.0041558906,0.005536005,0.008418254,0.0027729466,0.020487685,0.0041125063],"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":[0.000013654895,0.0000097990205,0.000032062042,0.0003150477,0.000020322097,0.00006956273,0.00003416787,0.00007177918,0.000016352918,0.0052686003,0.9877615,0.0063872966],"study_design_scores_gemma":[0.00002190354,0.000015801374,0.00026988605,0.0010964448,0.000044000917,0.00022826843,0.000090498936,0.00025040944,0.00003861873,0.013557828,0.9843581,0.000028301854],"about_ca_topic_score_codex":0.004477642,"about_ca_topic_score_gemma":0.008198872,"teacher_disagreement_score":0.016385216,"about_ca_system_score_codex":0.0055662366,"about_ca_system_score_gemma":0.004160493,"threshold_uncertainty_score":0.06725383},"labels":[],"label_agreement":null},{"id":"W4316036267","doi":"10.1016/j.jue.2022.103529","title":"In the eye of the storm: Firms and capital destruction in India","year":2023,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":34,"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; Center for Interuniversity Research and Analysis on Organizations; Université de Sherbrooke","funders":"","keywords":"Cyclone (programming language); Capital (architecture); Storm; Business; Panel data; Tropical cyclone; Quality (philosophy); Tropical cyclone scales; Economics; Meteorology; Engineering; Geography","score_opus":0.00868400408690678,"score_gpt":0.19269832929238076,"score_spread":0.18401432520547398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4316036267","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":[0.99759644,0.0001790217,0.00006306352,0.00044739232,0.0000031310194,0.0000040499863,0.00020967596,0.000003778892,0.0014935686],"genre_scores_gemma":[0.99950624,0.00007987283,0.000013542578,0.000030028392,0.0000025783804,0.0000010008242,0.00008674745,5.3325186e-7,0.00027935606],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996705,0.000053308526,0.00001645915,0.00004059918,0.000052561747,0.00016657557],"domain_scores_gemma":[0.996872,0.0006968911,0.0016775065,0.00012531699,0.00019293687,0.0004352702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029486857,0.000107000866,0.00013175911,0.0008544632,0.00048496437,0.001363969,0.00037641983,0.00047249827,0.0015644766],"category_scores_gemma":[0.0019093306,0.00012920126,0.00024061213,0.0015699861,0.00071640103,0.00054589025,0.0008864521,0.00067018636,0.000205168],"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":[0.000053442054,0.000057033543,0.99175596,0.000015961874,0.000049357805,0.00041308108,0.0011249034,0.0020718316,0.000270309,0.0005586815,0.00079221645,0.0028372267],"study_design_scores_gemma":[0.0000026074192,0.000016544243,0.99614847,0.0000065842664,0.00001189219,0.000075145545,0.0021523081,0.0007118448,0.000109036126,0.00017695982,0.0005827099,0.0000059164972],"about_ca_topic_score_codex":0.124633394,"about_ca_topic_score_gemma":0.14915152,"teacher_disagreement_score":0.124633394,"about_ca_system_score_codex":0.0015911638,"about_ca_system_score_gemma":0.0006485837,"threshold_uncertainty_score":0.2478159},"labels":[],"label_agreement":null},{"id":"W4327654108","doi":"10.1016/j.jue.2022.103531","title":"In remembrance Edwin S. Mills (1928-2021)","year":2023,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"COVID-19 impact on air quality","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Fell; Electricity; Consumption (sociology); Coronavirus disease 2019 (COVID-19); Agricultural economics; Energy consumption; Electric energy consumption; Work (physics); Economics; Engineering; Geography; Electric energy; Power (physics)","score_opus":0.02155829915324382,"score_gpt":0.27471254269728296,"score_spread":0.25315424354403915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4327654108","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00059332344,0.4925911,0.0011667793,0.29615894,0.14436549,0.00003347391,0.0005821461,0.0000790013,0.064429685],"genre_scores_gemma":[0.01124616,0.18555118,0.0014348176,0.10741335,0.074242465,0.00010130071,0.0004991479,0.00023010376,0.6192815],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993303,0.00014470489,0.000054627744,0.0001693074,0.00022717366,0.00007388709],"domain_scores_gemma":[0.9991429,0.00034910574,0.00010686034,0.00003798225,0.00021326145,0.00014986741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013452831,0.001268034,0.0006204454,0.0017421957,0.0015533201,0.0037766942,0.00087209744,0.004344471,0.041643538],"category_scores_gemma":[0.0036797917,0.00040115355,0.00042759822,0.002191104,0.0013309467,0.0055969907,0.0024868185,0.0040801177,0.020377075],"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":[0.000025828382,0.000008674739,0.00018912953,0.00009508362,0.000003033002,0.000052303294,0.00013400528,0.000023866058,0.00004449863,0.0077303145,0.9559763,0.035716914],"study_design_scores_gemma":[0.0000023167302,0.0000033916208,0.0002893351,0.00014025491,0.0000012053324,0.000042619253,0.00009613928,0.000012694531,0.000029483568,0.0024143413,0.9969638,0.000004355575],"about_ca_topic_score_codex":0.00709042,"about_ca_topic_score_gemma":0.021339923,"teacher_disagreement_score":0.041643538,"about_ca_system_score_codex":0.0019631044,"about_ca_system_score_gemma":0.0013505188,"threshold_uncertainty_score":0.13931149},"labels":[],"label_agreement":null},{"id":"W4327654354","doi":"10.1016/j.jue.2022.103530","title":"Special Issue of JUE Insight Papers: Introduction","year":2023,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"COVID-19 impact on air quality","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Fell; Electricity; Consumption (sociology); Coronavirus disease 2019 (COVID-19); Agricultural economics; Energy consumption; Work (physics); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Mains electricity; Smart meter; Economics; Business; Engineering; Geography","score_opus":0.01863809908698754,"score_gpt":0.25431192846625933,"score_spread":0.23567382937927178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4327654354","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00048808203,0.011154537,0.00044387858,0.09049704,0.83695906,0.00019850161,0.0030903611,0.00044405536,0.056724448],"genre_scores_gemma":[0.003969888,0.008780899,0.0005208247,0.023823146,0.603512,0.00023627849,0.002795592,0.0007640165,0.3555973],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99493647,0.00047486805,0.0003926869,0.0007114712,0.0026237953,0.0008606852],"domain_scores_gemma":[0.9793562,0.0040786094,0.0021125989,0.0020429022,0.007973407,0.0044363],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0061948798,0.0031926637,0.0029911634,0.007894456,0.0030822926,0.018847572,0.00347774,0.014740811,0.20124969],"category_scores_gemma":[0.01982639,0.0011359683,0.0025063525,0.0060604224,0.0014582492,0.005889617,0.0034446977,0.007986854,0.10124385],"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":[0.000035052584,0.000022403956,0.00004794535,0.0000805585,0.000007733214,0.000028890418,0.0000047791023,0.000032936176,0.000045200817,0.00068696256,0.9946824,0.004325297],"study_design_scores_gemma":[0.00004745105,0.000031213378,0.0012259139,0.00021470847,0.00001318206,0.000043556738,0.000023294018,0.00011280005,0.00007686869,0.0022184192,0.9959747,0.00001799509],"about_ca_topic_score_codex":0.0025719774,"about_ca_topic_score_gemma":0.006704794,"teacher_disagreement_score":0.7987503,"about_ca_system_score_codex":0.004521447,"about_ca_system_score_gemma":0.005283371,"threshold_uncertainty_score":0.6732473},"labels":[],"label_agreement":null},{"id":"W4353048845","doi":"10.1016/j.jue.2023.103542","title":"The Problem Has Existed over Endless Years: Racialized Difference in Commuting, 1980–2019","year":2023,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Demographic economics; Quarter (Canadian coin); Differential (mechanical device); Significant difference; Population; Geography; Car ownership; Difference in differences; Demography; Spatial mismatch; Work (physics); Economics; Sociology; Transport engineering; Public transport; Engineering; Mathematics; Statistics; Econometrics","score_opus":0.04398259271333681,"score_gpt":0.300531761233708,"score_spread":0.2565491685203712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353048845","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":[0.98022604,0.003082233,0.00009658814,0.008877487,0.00026506413,0.000008964515,0.0037456022,0.000005456171,0.0036925257],"genre_scores_gemma":[0.9960007,0.00089916645,0.000057821373,0.0004436772,0.00013891835,0.000009387515,0.0012769102,0.000004394296,0.0011690023],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993711,0.000109850625,0.00006746468,0.00011799298,0.000063415886,0.0002703102],"domain_scores_gemma":[0.998522,0.00015477491,0.0005779588,0.0000748616,0.00033454347,0.00033592683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010593482,0.00014521573,0.00023104779,0.001053064,0.00097159046,0.0011613297,0.00072106713,0.0009688977,0.0035810596],"category_scores_gemma":[0.0026979616,0.00011537182,0.0004930233,0.0025894383,0.00056431396,0.0014035953,0.0012326919,0.0012665844,0.0003524275],"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":[0.00021302226,0.000100455545,0.97443277,0.00010940763,0.00010841385,0.00016229124,0.004352753,0.00013309137,0.00023595363,0.0026420364,0.004972638,0.01253716],"study_design_scores_gemma":[0.0000023337975,0.000015578476,0.992305,0.00005226785,0.000016656,0.000040276114,0.0041066515,0.000070094895,0.000035978024,0.00012748483,0.0032224269,0.00000532003],"about_ca_topic_score_codex":0.2528017,"about_ca_topic_score_gemma":0.40256464,"teacher_disagreement_score":0.2528017,"about_ca_system_score_codex":0.0014986792,"about_ca_system_score_gemma":0.0020291419,"threshold_uncertainty_score":0.5026604},"labels":[],"label_agreement":null},{"id":"W4388108664","doi":"10.1016/j.jue.2023.103608","title":"Homeowner politics and housing supply","year":2023,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","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":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Amenity; Opposition (politics); Politics; Business; Subdivision; Finance; Public housing; Neighbourhood (mathematics); Labour economics; Economic growth; Economics; Political science; Geography; Law","score_opus":0.02593243756321166,"score_gpt":0.20288927644185775,"score_spread":0.1769568388786461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388108664","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":[0.9860308,0.00036886672,0.0001362205,0.001039292,0.000011628339,0.000010732416,0.0008614813,0.0000039996594,0.011536995],"genre_scores_gemma":[0.9962876,0.00013164985,0.000020638407,0.000053688553,0.000011911047,0.0000042408624,0.00042994117,0.0000023237544,0.0030580477],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991541,0.00016295076,0.00004060724,0.00009973203,0.00023539005,0.00030728534],"domain_scores_gemma":[0.9943082,0.00086207525,0.002950906,0.00020648411,0.0005902541,0.0010820283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054522674,0.0000899873,0.00033872796,0.00083848706,0.0013546861,0.0019594755,0.00032641992,0.00046551955,0.0098700365],"category_scores_gemma":[0.0037517494,0.0001716455,0.00014043378,0.0019733075,0.0014001689,0.000617987,0.00089542114,0.0008497281,0.00074603036],"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":[0.00005598871,0.000048467547,0.9881414,0.000020703677,0.000037990583,0.00017406227,0.0015819973,0.00045107194,0.00016142498,0.003050229,0.0023663011,0.003910469],"study_design_scores_gemma":[0.000005611561,0.000012229047,0.9902333,0.000021751082,0.000006737997,0.000032055123,0.0031945475,0.00033162785,0.000051841645,0.0002475964,0.005856914,0.000005803063],"about_ca_topic_score_codex":0.47057122,"about_ca_topic_score_gemma":0.6903586,"teacher_disagreement_score":0.47057122,"about_ca_system_score_codex":0.0046437723,"about_ca_system_score_gemma":0.001746777,"threshold_uncertainty_score":0.93566436},"labels":[],"label_agreement":null},{"id":"W4391781907","doi":"10.1016/j.jue.2024.103631","title":"The effects of residential landlord–tenant laws: New evidence from Canadian reforms using census data","year":2024,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"York University","funders":"","keywords":"Landlord; Census; Business; Law; Economics; Labour economics; Demographic economics; Political science; Sociology; Demography; Population","score_opus":0.05382603427472478,"score_gpt":0.2420505900166776,"score_spread":0.18822455574195285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391781907","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":[0.9420256,0.0047243703,0.0004446833,0.0071747513,0.000085315136,0.00013181406,0.019396564,0.000032945125,0.025983907],"genre_scores_gemma":[0.9849835,0.0026662394,0.00026600182,0.0005918642,0.00004709278,0.000030191364,0.006643146,0.000015167625,0.00475679],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99443614,0.0008183124,0.00029322773,0.0004680915,0.0022623846,0.0017218507],"domain_scores_gemma":[0.9655746,0.008629309,0.008357222,0.0015317902,0.013018701,0.0028883924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034917735,0.0003223108,0.0006402004,0.003736973,0.0024714826,0.0030250826,0.0020564839,0.00079164805,0.0064055813],"category_scores_gemma":[0.026677495,0.00034674612,0.00077059824,0.012446124,0.0022423784,0.0016598578,0.0017309472,0.0017594453,0.00042650863],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002490617,0.00021661486,0.94987386,0.00018309818,0.00026123083,0.00018420508,0.0031827905,0.0015094959,0.00016707696,0.005823509,0.017315313,0.021033758],"study_design_scores_gemma":[0.000019644527,0.000022438715,0.98544586,0.00006633083,0.00012508711,0.000010127076,0.002894079,0.0006619942,0.000110732406,0.00021305835,0.010412888,0.000017640623],"about_ca_topic_score_codex":0.99616563,"about_ca_topic_score_gemma":0.9984993,"teacher_disagreement_score":0.04021068,"about_ca_system_score_codex":0.04021068,"about_ca_system_score_gemma":0.052631274,"threshold_uncertainty_score":0.29175025},"labels":[],"label_agreement":null},{"id":"W4398178235","doi":"10.1016/j.jue.2024.103655","title":"Agglomeration Economies and the Built Environment: Evidence from Specialized Buildings and Anchor Tenants","year":2024,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Economies of agglomeration; Business; Economic geography; Economics; Economy; Economic growth","score_opus":0.027738999843694604,"score_gpt":0.2071702698149078,"score_spread":0.1794312699712132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398178235","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":[0.99792635,0.00012657134,0.00006213389,0.000055862427,0.0000012540336,0.0000036042238,0.00013725058,0.0000012826254,0.0016855461],"genre_scores_gemma":[0.9989089,0.00016396535,0.00004034928,0.000008828315,0.0000028062948,0.0000027654366,0.00028453898,0.0000014401318,0.000586453],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99939907,0.00024908877,0.00002659233,0.000073434,0.00009903362,0.00015278258],"domain_scores_gemma":[0.9922645,0.0030244032,0.00248767,0.00059334585,0.0006852444,0.00094482413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008571228,0.00030543742,0.0004114153,0.0011513272,0.0009849408,0.0012081803,0.00068322686,0.00047372153,0.0073317443],"category_scores_gemma":[0.0038156158,0.00020534788,0.0003985718,0.0039650714,0.0015817424,0.0011389225,0.0014355014,0.0006056631,0.000544296],"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":[0.0010263489,0.00051869603,0.97413886,0.00007471374,0.00026377177,0.00059733953,0.0057264995,0.0010524527,0.00030971027,0.002838831,0.00090829894,0.012544301],"study_design_scores_gemma":[0.000029363942,0.00016663419,0.9831344,0.000024200119,0.00010018557,0.000087975255,0.013559795,0.0004482602,0.00014297712,0.0007787444,0.0015144228,0.000013066556],"about_ca_topic_score_codex":0.081797436,"about_ca_topic_score_gemma":0.18069845,"teacher_disagreement_score":0.081797436,"about_ca_system_score_codex":0.0006114466,"about_ca_system_score_gemma":0.0004530611,"threshold_uncertainty_score":0.1626426},"labels":[],"label_agreement":null},{"id":"W4400874122","doi":"10.1016/j.jue.2024.103686","title":"JUE insight: Air pollution and student performance in the U.S.","year":2024,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Pollution; Air pollution; Electricity; Unit (ring theory); Test (biology); Natural resource economics; Standard deviation; Environmental science; Particulate pollution; Particulates; Fell; Economics; Agricultural economics; Econometrics; Environmental protection; Geography; Statistics; Mathematics; Engineering; Chemistry; Cartography; Ecology","score_opus":0.0475721869911739,"score_gpt":0.207920483421916,"score_spread":0.16034829643074208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400874122","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":[0.968218,0.00069699786,0.0006091644,0.006476883,0.00010239085,0.000011478002,0.013561048,0.000066602915,0.010257484],"genre_scores_gemma":[0.9910438,0.00022211441,0.00013463957,0.00035653063,0.00005385806,0.0000068488775,0.0037347525,0.000008773785,0.0044387463],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996594,0.00011031344,0.000018061197,0.00004749597,0.000106960455,0.000057622532],"domain_scores_gemma":[0.996403,0.001180715,0.0011376776,0.00017326523,0.0005559386,0.00054946856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006778965,0.00018449003,0.00019397849,0.00072080403,0.00025535192,0.00090156053,0.0002735062,0.00058399857,0.0070785233],"category_scores_gemma":[0.004428851,0.00008926367,0.00022446067,0.0012963895,0.0002250047,0.00060355605,0.00072457263,0.00064631907,0.001116655],"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":[0.000082180195,0.00015207831,0.97398484,0.000020569378,0.000077495686,0.000056835594,0.00018495748,0.0009828297,0.00009741862,0.0010051237,0.014848547,0.00850711],"study_design_scores_gemma":[0.00001327839,0.0000881227,0.9903701,0.00002275751,0.000039930845,0.00003210376,0.0005722624,0.0025848898,0.00016229128,0.00078051735,0.0053258575,0.000007950173],"about_ca_topic_score_codex":0.05077288,"about_ca_topic_score_gemma":0.080101274,"teacher_disagreement_score":0.05077288,"about_ca_system_score_codex":0.00037184992,"about_ca_system_score_gemma":0.0005811005,"threshold_uncertainty_score":0.10095471},"labels":[],"label_agreement":null},{"id":"W4401669127","doi":"10.1016/j.jue.2024.103691","title":"The spatial impacts of a massive rail disinvestment program: The Beeching Axe","year":2024,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":15,"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":"Economic and Social Research Council; University of Portsmouth; Institute for New Economic Thinking","keywords":"Disinvestment; Business; Economics; Macroeconomics","score_opus":0.011884638840196967,"score_gpt":0.2018646597243434,"score_spread":0.18998002088414642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401669127","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":[0.99773264,0.000053225183,0.000114272276,0.00015357613,0.000006607183,0.000009975244,0.00007780892,0.0000075553608,0.0018442472],"genre_scores_gemma":[0.9993761,0.00006401211,0.000064244254,0.000024889388,0.0000029419746,0.0000035037576,0.000052996744,0.0000011204621,0.00041016767],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995409,0.00014012416,0.000013751257,0.000059863614,0.00006918402,0.00017616067],"domain_scores_gemma":[0.99893314,0.00024952527,0.00042932117,0.00010036712,0.00015197229,0.00013570144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034145027,0.00022515364,0.00015090719,0.00053423486,0.00044601873,0.0005883331,0.00050616264,0.00039305928,0.0022362191],"category_scores_gemma":[0.0022856742,0.00011823197,0.00022474055,0.00051387394,0.0011890732,0.00037998703,0.0010177231,0.0003272163,0.00013227234],"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":[0.0035856313,0.0028435276,0.7696821,0.00028622802,0.000545091,0.0028934982,0.0019924499,0.0653506,0.02585044,0.0117938975,0.0038579938,0.11131857],"study_design_scores_gemma":[0.00012041114,0.0024438011,0.97776026,0.000036940644,0.00016359026,0.00016876256,0.003621793,0.0051669125,0.0043903175,0.0014270868,0.004670771,0.000029406408],"about_ca_topic_score_codex":0.057591025,"about_ca_topic_score_gemma":0.0973222,"teacher_disagreement_score":0.057591025,"about_ca_system_score_codex":0.0017994633,"about_ca_system_score_gemma":0.00086665543,"threshold_uncertainty_score":0.11451161},"labels":[],"label_agreement":null},{"id":"W4403690746","doi":"10.1016/j.jue.2024.103710","title":"Forward to the Special Issue “Celebrating the 50th Anniversary of the Journal of Urban Economics”","year":2024,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; University of Toronto","funders":"","keywords":"Economics; Regional science; Neoclassical economics; Law and economics; Sociology","score_opus":0.015252932329184747,"score_gpt":0.1957361031009416,"score_spread":0.18048317077175685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403690746","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014547435,0.005879212,0.0003234453,0.14844392,0.83707976,0.000019067893,0.00027416542,0.00013121197,0.0077037285],"genre_scores_gemma":[0.0018922593,0.0058494424,0.0003739386,0.064887874,0.8483682,0.000049210124,0.00035224998,0.00025954022,0.077967174],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99761766,0.0003424475,0.00015484089,0.00047696262,0.00097272167,0.00043533123],"domain_scores_gemma":[0.98532826,0.0025983131,0.001250862,0.0006058123,0.004537247,0.005679521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034557579,0.0021209528,0.0027765092,0.0030666017,0.0031565274,0.014591571,0.0025261801,0.009863314,0.07763541],"category_scores_gemma":[0.012822052,0.00058338745,0.0016996646,0.0022161903,0.0018471879,0.006527693,0.004032319,0.012444524,0.05269157],"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":[0.000015848458,0.00000854331,0.000055260087,0.000042364045,0.000004634117,0.000021278123,0.000007303502,0.000011213242,0.00003527446,0.001019443,0.99470645,0.0040723546],"study_design_scores_gemma":[0.00001027494,0.000015925207,0.00062018086,0.000115853196,0.000009542443,0.000030014618,0.000062933716,0.000066786546,0.00005922905,0.0026562917,0.99633896,0.000013940321],"about_ca_topic_score_codex":0.0015667776,"about_ca_topic_score_gemma":0.005734038,"teacher_disagreement_score":0.07763541,"about_ca_system_score_codex":0.0022632645,"about_ca_system_score_gemma":0.0031606907,"threshold_uncertainty_score":0.25971633},"labels":[],"label_agreement":null},{"id":"W4403984041","doi":"10.1016/j.jue.2024.103714","title":"The city-wide effects of tolling downtown drivers: Evidence from London’s congestion charge","year":2024,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Downtown; Congestion pricing; Transport engineering; Business; Traffic congestion; Geography; Engineering; Archaeology","score_opus":0.01674314867214784,"score_gpt":0.256945019863802,"score_spread":0.24020187119165418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403984041","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":[0.9946273,0.0005997105,0.000061025545,0.0007035288,0.000028255508,0.000010771188,0.0014486992,0.0000048841466,0.0025159097],"genre_scores_gemma":[0.9972752,0.00030680228,0.000019374585,0.0001003479,0.000018911016,0.0000086586715,0.0009080699,0.0000035153691,0.0013592032],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99835,0.0008281486,0.0001091669,0.00017127258,0.00021275858,0.00032859677],"domain_scores_gemma":[0.98557264,0.005822497,0.004795072,0.0009093735,0.0012973967,0.0016029148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078607036,0.00031806383,0.00043024673,0.0012730701,0.00071263645,0.002092407,0.0009471419,0.0013781978,0.0056549083],"category_scores_gemma":[0.008160277,0.00047394852,0.0008487061,0.003043902,0.0012781054,0.0011685515,0.0018677242,0.001256828,0.00068228313],"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":[0.0016911522,0.0003779467,0.9812402,0.00013929351,0.001055952,0.00070269394,0.0015070057,0.0028389345,0.00038471873,0.0012268963,0.004509528,0.0043256786],"study_design_scores_gemma":[0.00014031374,0.00021918234,0.99051356,0.000049689665,0.00042907865,0.000066260814,0.003978892,0.00094279804,0.0001926345,0.00028762274,0.0031374767,0.0000423861],"about_ca_topic_score_codex":0.3230015,"about_ca_topic_score_gemma":0.45529935,"teacher_disagreement_score":0.3230015,"about_ca_system_score_codex":0.002293399,"about_ca_system_score_gemma":0.0010221393,"threshold_uncertainty_score":0.64224285},"labels":[],"label_agreement":null},{"id":"W4412103966","doi":"10.1016/j.jue.2025.103783","title":"Rushing to opportunity: City growth and entrepreneurship","year":2025,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Entrepreneurship; Business; Economics; Finance","score_opus":0.0454593238783933,"score_gpt":0.2279152313372132,"score_spread":0.1824559074588199,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412103966","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":[0.9380714,0.001407184,0.010175629,0.0057621137,0.00004589687,0.000022800805,0.0004920237,0.000048116992,0.043974884],"genre_scores_gemma":[0.99554753,0.00044432434,0.0003624279,0.00005108765,0.000018564459,0.0000057497177,0.00006981362,0.000004980078,0.003495515],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99978524,0.00006186755,0.0000053993103,0.000029655963,0.000021417422,0.000096460004],"domain_scores_gemma":[0.9986552,0.00041075697,0.00033486006,0.00007302875,0.000096028896,0.00042999387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043918597,0.00018106712,0.00026722535,0.000651678,0.0006199722,0.0023909016,0.00036829725,0.00071591674,0.0059572896],"category_scores_gemma":[0.0022539245,0.00013963367,0.0003049114,0.0012732114,0.0016695927,0.0021354072,0.0016090538,0.0010057281,0.00046060066],"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":[0.0002725803,0.00020122572,0.18063633,0.00012853318,0.000078410565,0.0009592219,0.0017437055,0.092791855,0.0010056817,0.6686478,0.0077725695,0.045762096],"study_design_scores_gemma":[0.000110369605,0.00019537537,0.1661891,0.00019444241,0.00006769458,0.0005535793,0.0058418633,0.1709495,0.0008963458,0.61616355,0.03875856,0.00007959805],"about_ca_topic_score_codex":0.010410229,"about_ca_topic_score_gemma":0.013996603,"teacher_disagreement_score":0.010410229,"about_ca_system_score_codex":0.0013309821,"about_ca_system_score_gemma":0.0007018088,"threshold_uncertainty_score":0.020699263},"labels":[],"label_agreement":null},{"id":"W4413004472","doi":"10.1016/j.jue.2025.103784","title":"The effects of residential zoning in U.S. housing markets","year":2025,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":4,"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":"Harvard Kennedy School; Furman Center for Real Estate and Urban Policy, New York University; University of Colorado Boulder; University of British Columbia; University of Toronto; University of East Anglia; Seoul National University; Arizona State University; Syracuse University; Yale University","keywords":"Zoning; Business; Economics; Civil engineering; Engineering","score_opus":0.007404635119854543,"score_gpt":0.1953898983670726,"score_spread":0.18798526324721807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413004472","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":[0.98538315,0.0016986505,0.00018593903,0.003929374,0.00006337295,0.000017866434,0.00087478483,0.000018517057,0.007828437],"genre_scores_gemma":[0.99861443,0.00025935794,0.000022486216,0.000098388344,0.000025189323,0.0000023502632,0.00014515998,0.0000039966017,0.0008286884],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991015,0.0003159141,0.00003999053,0.000085131316,0.00008101114,0.00037649638],"domain_scores_gemma":[0.99441344,0.0020649917,0.0016116026,0.00015350245,0.0004924071,0.0012641195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001099098,0.00022032531,0.00042763512,0.0008166354,0.0010526824,0.003047361,0.00065130176,0.0012322342,0.013209775],"category_scores_gemma":[0.005889768,0.00022962884,0.0008682151,0.0015539718,0.0017988074,0.0020683727,0.0020291845,0.001474583,0.00051136],"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":[0.0023548736,0.0014001615,0.8691842,0.00016438137,0.0004194834,0.0007342324,0.0014614883,0.029327776,0.0015227895,0.053507734,0.01766279,0.02226016],"study_design_scores_gemma":[0.00014166588,0.00023705346,0.95485246,0.00008061777,0.0002085269,0.000082482125,0.0065616746,0.019680336,0.00061833224,0.01034286,0.0071454598,0.00004847861],"about_ca_topic_score_codex":0.15263586,"about_ca_topic_score_gemma":0.26109093,"teacher_disagreement_score":0.15263586,"about_ca_system_score_codex":0.0028920828,"about_ca_system_score_gemma":0.0017869014,"threshold_uncertainty_score":0.30349487},"labels":[],"label_agreement":null}]}