{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":10,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":10,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"query_hash":"8e8cb61cdc27","filters":{"venue":"Economics of Transportation"}},"results":[{"id":"W2058287092","doi":"10.1016/j.ecotra.2012.08.001","title":"Airports and airlines economics and policy: An interpretive review of recent research","year":2012,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":181,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Alliance; Economics; Aviation; Management science; Marketing; Operations research; Industrial organization; Business; Regional science; Engineering; Sociology; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.08690949260604881,"gpt":0.332991247931408,"spread":0.2460817553253592,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001178104,0.0001024592,0.0004303139,0.0003134486,0.00004604685,0.0000114527,0.00008189639,0.00009107767,0.0001881328],"category_scores_gemma":[0.00005798998,0.000124375,0.00006109929,0.0001483915,0.000119374,0.0005714106,0.000009025905,0.0001016797,0.000004239057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005669078,"about_ca_system_score_gemma":0.00003970168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002473461,"about_ca_topic_score_gemma":0.0001228373,"domain_scores_codex":[0.9986653,0.00002195112,0.0008918206,0.000234533,0.0000177349,0.0001686544],"domain_scores_gemma":[0.9989522,0.00005724818,0.0005935538,0.000203342,0.00008401037,0.0001096992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004252198,0.0001978715,0.3846523,0.0007970098,0.0001666649,1.93513e-7,0.00276569,0.0002613889,0.000005886831,0.5914428,0.0001082488,0.01955938],"study_design_scores_gemma":[0.0007420095,0.0002868747,0.9075661,0.0006554729,0.00009223058,0.000004186133,0.0009007397,0.001728864,0.0007752859,0.02797629,0.05874238,0.0005295181],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831855,0.01122546,0.0001550101,0.001333567,0.0001006222,0.0001568403,0.0004674128,0.000005875398,0.003369732],"genre_scores_gemma":[0.8815285,0.1176399,0.0004524836,0.0001031246,0.00007517346,0.00001074361,0.0001374042,0.00001201754,0.00004066909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5634665,"threshold_uncertainty_score":0.5071867,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2158313237","doi":"10.1016/j.ecotra.2012.07.001","title":"Road pricing and investment","year":2012,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":48,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Toll; Singapore Area Licensing Scheme; Road pricing; Congestion pricing; Traffic congestion; Toll road; Investment (military); Marginal cost; Business; Economics; Transport engineering; Microeconomics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01783797694041126,"gpt":0.2537334758896698,"spread":0.2358954989492586,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002368341,0.00003894325,0.0000672395,0.00004359855,0.00008294621,0.000007761741,0.00002760427,0.00003832481,0.00002550327],"category_scores_gemma":[0.000005858513,0.00004591842,0.00001748044,0.00004303744,0.0000492976,0.0003527643,2.815974e-7,0.00002330489,0.000001873142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001741993,"about_ca_system_score_gemma":0.0000282749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005422072,"about_ca_topic_score_gemma":0.0007300546,"domain_scores_codex":[0.9996202,0.00001379023,0.0001648177,0.0000609725,0.00004049641,0.00009971081],"domain_scores_gemma":[0.9997694,0.00002004561,0.00009157081,0.00003507864,0.00002120527,0.00006268309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000020453,0.00005778722,0.5406675,0.00002836976,0.00002356204,1.437325e-7,0.08173784,0.006524013,0.00007893967,0.3625004,0.00006339778,0.008297585],"study_design_scores_gemma":[0.0002247655,0.00001260524,0.9883252,0.0000116412,0.00002545935,6.694535e-8,0.002195146,0.0001634229,0.0003412589,0.0005773403,0.008032081,0.00009100501],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994058,0.0001234098,0.0009740854,0.0001703716,0.0001339742,0.00008563756,0.00001337752,0.00002146851,0.00441966],"genre_scores_gemma":[0.9957597,0.0001908729,0.003776669,0.00007028217,0.00004374975,0.000003635782,0.00007357082,0.000004422287,0.00007710725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4476577,"threshold_uncertainty_score":0.1872499,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2308782428","doi":"10.1016/j.ecotra.2016.02.001","title":"Hub congestion pricing: Discriminatory passenger charges","year":2016,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":32,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Charge (physics); Transport engineering; Passenger transport; Profit (economics); Congestion pricing; Fixed charge; Automotive engineering; Passenger train; Business; Traffic congestion; Economics; Engineering; Microeconomics; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.03197656314062398,"gpt":0.2100998343295485,"spread":0.1781232711889245,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002428463,0.0001107559,0.0002866333,0.0001887942,0.00004471668,0.00001246406,0.0001049067,0.0001062702,0.000722787],"category_scores_gemma":[0.00001763922,0.0001060412,0.000130813,0.00008352561,0.00004899054,0.0004161902,0.000002476743,0.0000517204,0.0001246562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005796779,"about_ca_system_score_gemma":0.000013592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004389256,"about_ca_topic_score_gemma":0.0000641708,"domain_scores_codex":[0.998857,0.000006757254,0.0007063086,0.0002744784,0.00001872367,0.0001367148],"domain_scores_gemma":[0.9990951,0.0000429644,0.0005774791,0.0001964974,0.00003588016,0.00005209355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001924871,0.00007754267,0.3537462,0.0000287057,0.00008134502,6.265067e-7,0.0003496662,0.0002629611,0.0002421714,0.6393749,0.000203375,0.005613293],"study_design_scores_gemma":[0.0007040489,0.00004578618,0.9668555,0.00002701938,0.00003162421,3.38667e-7,0.00006559865,0.0001504898,0.002819198,0.01982912,0.009226402,0.0002448356],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884869,0.000174786,0.0047869,0.001563638,0.0002578498,0.00007680097,0.0004295364,0.00002510755,0.004198516],"genre_scores_gemma":[0.9983954,0.0002550184,0.0002204811,0.0000383841,0.00006357702,0.00001421168,0.00009846465,0.00001585935,0.0008986264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6195457,"threshold_uncertainty_score":0.7914011,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3001784808","doi":"10.1016/j.ecotra.2019.100149","title":"Tradable permit schemes for congestible facilities with uncertain supply and demand","year":2020,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Pontificia Universidad Católica de Chile; University of British Columbia; Hong Kong Polytechnic University; Agence Nationale de la Recherche; Social Sciences and Humanities Research Council of Canada; Université Laval; Rensselaer Polytechnic Institute","keywords":"Allocative efficiency; Economics; Price elasticity of demand; Microeconomics; Multiplicative function; Econometrics; Demand shock; Demand curve; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.08429229356195837,"gpt":0.2275766939565311,"spread":0.1432844003945727,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001431308,0.0001443324,0.0004149702,0.0000750785,0.00006310555,0.00003559781,0.00009256011,0.00007444349,0.0001542542],"category_scores_gemma":[0.00002035851,0.0001734948,0.0000686284,0.00004468108,0.00008562507,0.0003419825,0.000003358781,0.0000524426,0.00001028299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002728589,"about_ca_system_score_gemma":0.00002622727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002150127,"about_ca_topic_score_gemma":0.0004379198,"domain_scores_codex":[0.998953,0.000002466486,0.0005176311,0.0003228993,0.000009105303,0.0001948491],"domain_scores_gemma":[0.9994149,0.00006783678,0.0002721653,0.000105605,0.00002062856,0.0001188167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008675085,0.00009349029,0.2562057,0.001565971,0.000320635,0.000001660296,0.01575277,0.006079822,0.0001381948,0.7161825,0.000612863,0.002178874],"study_design_scores_gemma":[0.01774947,0.003345737,0.111902,0.0001831402,0.0002482801,0.00001324633,0.01062183,0.0931388,0.01614141,0.1189389,0.6243196,0.003397585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877152,0.0008040262,0.003123463,0.002475584,0.0000532873,0.000331188,0.004595067,0.00002210989,0.0008800785],"genre_scores_gemma":[0.9940412,0.0008932183,0.004132292,0.0003300813,0.0000587978,0.00004862678,0.0003229707,0.00002572775,0.0001470979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6237068,"threshold_uncertainty_score":0.7074913,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2078067655","doi":"10.1016/j.ecotra.2014.01.004","title":"Cost recovery from congestion tolls with long-run uncertainty","year":2014,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Toll; Marginal cost; Economics; Investment (military); Microeconomics; Revenue; Constant (computer programming); Variable cost; Economies of scale; Finance; Computer science","retraction":null,"screen_n_in":null,"score":{"opus":0.01677056426139053,"gpt":0.2437552441834967,"spread":0.2269846799221062,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002864586,0.00009139656,0.0001662447,0.0000651419,0.0001293078,0.00003001355,0.00009513663,0.00009833297,0.0001233391],"category_scores_gemma":[0.00001834915,0.00009893441,0.00004538059,0.00009354406,0.0001017017,0.000376791,3.759399e-7,0.0000600865,0.000009054475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004957611,"about_ca_system_score_gemma":0.0001057789,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004310977,"about_ca_topic_score_gemma":0.04827091,"domain_scores_codex":[0.9992161,0.00004922484,0.0003020807,0.000199174,0.0001017238,0.0001316988],"domain_scores_gemma":[0.9993032,0.0001593238,0.0002483009,0.0001095285,0.0001095222,0.00007012044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003111499,0.00005472961,0.1359981,0.00001570825,0.00005854362,7.973312e-7,0.009579336,0.8215517,0.00002351845,0.01480719,0.00009412198,0.0175051],"study_design_scores_gemma":[0.001534733,0.0001583713,0.9792992,0.00009510924,0.0001369408,1.254123e-7,0.001845752,0.00368178,0.0004915354,0.002299941,0.01009296,0.0003635148],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9538199,0.00001773671,0.04277229,0.0003451385,0.0002330635,0.000228637,0.0001995615,0.00005983515,0.002323816],"genre_scores_gemma":[0.9939874,0.0001573711,0.003874701,0.00007632729,0.0000795954,0.00001319086,0.001659772,0.00001222652,0.0001394298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8433012,"threshold_uncertainty_score":0.9690956,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4322624955","doi":"10.1016/j.ecotra.2023.100301","title":"How should ports share risk of natural and climate change disasters? Analytical modelling and implications for adaptation investments","year":2023,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Tropical and Extratropical Cyclones Research","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Japan Society for the Promotion of Science; Hong Kong Polytechnic University","keywords":"Port (circuit theory); Damages; Natural disaster; Business; Risk management; Adaptation (eye); Independence (probability theory); Investment (military); Natural hazard; Natural resource economics; Economics; Finance; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.09452350908897379,"gpt":0.2715118596710352,"spread":0.1769883505820614,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006484315,0.00005682791,0.0001189554,0.00006231437,0.00005295697,0.0000199625,0.00003815549,0.00003786209,0.000005276935],"category_scores_gemma":[0.000006730856,0.00005009552,0.00003416765,0.00006578786,0.0000543446,0.000251627,0.000001598862,0.00004419723,5.369986e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001637218,"about_ca_system_score_gemma":0.000006221239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003707759,"about_ca_topic_score_gemma":0.003371507,"domain_scores_codex":[0.9995137,0.000007612857,0.0001715692,0.000146639,0.0000388209,0.0001216084],"domain_scores_gemma":[0.9996992,0.00008060453,0.00007893379,0.00005187843,0.00002685443,0.00006255744],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007392059,0.00000665432,0.9533554,0.0001067308,0.00001903448,1.822317e-7,0.0004471658,0.01198563,0.000007815217,0.002871006,0.000003195727,0.03112327],"study_design_scores_gemma":[0.000146146,0.00004635976,0.7245102,0.000006352111,0.00001888645,1.398279e-7,0.0001421187,0.2723152,0.00001318022,0.002739003,0.00002499505,0.00003743618],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966422,0.0001633587,0.0007622763,0.0006719131,0.00002945642,0.0002079098,0.001505624,0.000008536397,0.000008723007],"genre_scores_gemma":[0.9962658,0.00120065,0.001331495,0.00001388486,0.0000215327,0.000006218694,0.001153879,0.000002528151,0.000004039406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2603295,"threshold_uncertainty_score":0.2042836,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406833693","doi":"10.1016/j.ecotra.2025.100396","title":"Oil price shocks and airlines stock return and volatility – A GFEVD analysis","year":2025,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Economics; Oil price; Volatility (finance); Stock (firearms); Financial economics; Monetary economics; Stock price; Econometrics; Business; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01140137173507434,"gpt":0.2155898037260861,"spread":0.2041884319910118,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005367455,0.0001329726,0.0004907164,0.0003231785,0.00006364771,0.00003400135,0.00008922,0.0001101012,0.00007057335],"category_scores_gemma":[0.00003213048,0.0001680491,0.0001179076,0.000266302,0.00007178148,0.0002128554,0.000009664501,0.00008856924,3.563525e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003726976,"about_ca_system_score_gemma":0.00002106168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004756334,"about_ca_topic_score_gemma":0.002176525,"domain_scores_codex":[0.9986632,0.000009927588,0.000769301,0.0004120498,0.00001362511,0.0001318234],"domain_scores_gemma":[0.9992307,0.00008198661,0.0003405432,0.0002525616,0.0000415149,0.00005273537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005327162,0.00003540016,0.9769787,0.0001293375,0.0002697627,1.576937e-7,0.000243727,0.00008510859,0.000003883633,0.01844731,0.00001143284,0.003741908],"study_design_scores_gemma":[0.0002801293,0.00001289873,0.6329573,0.000006451193,0.00007378299,7.034962e-8,0.00002439007,0.3550662,0.000007754661,0.01037548,0.00109405,0.0001015611],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9867217,0.0008498728,0.006715145,0.0003155883,0.00009666237,0.00007087189,0.000569533,0.00001419301,0.004646416],"genre_scores_gemma":[0.997238,0.0006903873,0.001258975,0.00005883718,0.00001086686,0.000009690637,0.000126262,0.000007433505,0.0005995856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3549811,"threshold_uncertainty_score":0.6852842,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4319315351","doi":"10.1016/j.ecotra.2022.100299","title":"Single-till regulation, dual-till regulation, and regulatory capture: When does a regulatory authority favor single-till regulation over dual-till regulation?","year":2023,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"ICT Impact and Policies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Japan Society for the Promotion of Science; Social Sciences and Humanities Research Council of Canada","keywords":"Monopoly; Profit (economics); Regulator; Business; Service provider; Industrial organization; Economics; Service (business); Microeconomics; Marketing","retraction":null,"screen_n_in":null,"score":{"opus":0.01244250846402927,"gpt":0.208822157940818,"spread":0.1963796494767887,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000975649,0.0008808346,0.001028037,0.001020943,0.0003831272,0.0001989408,0.0002693596,0.0008127618,0.0003384846],"category_scores_gemma":[0.0000884966,0.0009623502,0.0003652827,0.0007029951,0.0003842666,0.002125453,0.00003278461,0.0003599383,0.00004205441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005524903,"about_ca_system_score_gemma":0.0001367182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001990768,"about_ca_topic_score_gemma":0.001344852,"domain_scores_codex":[0.9955354,0.0001396811,0.002126757,0.0007441773,0.0005688923,0.0008850921],"domain_scores_gemma":[0.9968225,0.0002968854,0.0009158956,0.001164867,0.000427645,0.0003721684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000873264,0.000471352,0.03031287,0.002259914,0.001193642,0.00001402832,0.06195393,0.5761304,0.2012578,0.08287182,0.03089947,0.01176159],"study_design_scores_gemma":[0.001850824,0.0001372009,0.8881851,0.0002595168,0.0003138534,0.00001601887,0.0006671661,0.03404417,0.03489333,0.02399755,0.01429753,0.001337689],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918874,0.0003404973,0.001120602,0.0008085265,0.001560484,0.001025836,0.0006879173,0.001045862,0.001522904],"genre_scores_gemma":[0.9918626,0.0001451394,0.001320649,0.00009379436,0.0006657748,0.00005582426,0.002628561,0.0002693339,0.002958344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8578723,"threshold_uncertainty_score":0.9992827,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3154408997","doi":"10.1016/j.ecotra.2021.100208","title":"Optimization of the cost of urban traffic through an online bidding platform for commuters","year":2021,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Bidding; Computer science; Traffic congestion; Value of time; Nash equilibrium; Value (mathematics); Transport engineering; Operations research; Simulation; Microeconomics; Economics; Travel time; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.05050351424562764,"gpt":0.2882913342728664,"spread":0.2377878200272387,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001919287,0.00006345225,0.0001675206,0.00003783243,0.0001136364,0.000008025233,0.0001290556,0.00007690379,0.0000255727],"category_scores_gemma":[0.00002242111,0.00006586991,0.00009687794,0.0001600467,0.000106603,0.0004642593,7.932201e-7,0.00003936506,5.111968e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002591655,"about_ca_system_score_gemma":0.0001820501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001847069,"about_ca_topic_score_gemma":0.005677471,"domain_scores_codex":[0.9992246,0.0000256,0.0004640875,0.0001156089,0.00008080561,0.0000892872],"domain_scores_gemma":[0.9991311,0.00009346459,0.0004124074,0.0001252607,0.0002134613,0.00002431745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004050131,0.00009298648,0.004774517,0.00004473921,0.00002075623,5.269363e-8,0.01822919,0.9606804,0.00007826438,0.01497849,0.00001466671,0.001045427],"study_design_scores_gemma":[0.008123908,0.0005169195,0.2999032,0.000703755,0.0008467737,8.528764e-7,0.08019879,0.5525289,0.04351579,0.002372845,0.01019579,0.001092464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530362,0.00003501704,0.04524274,0.0002280492,0.0002196351,0.0002982957,0.0007216471,0.00001539625,0.0002030066],"genre_scores_gemma":[0.9661817,0.0002144792,0.03173023,0.00002912589,0.00002684507,0.000006621393,0.001773781,0.00001026342,0.00002697497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4081515,"threshold_uncertainty_score":0.3168162,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4401635949","doi":"10.1016/j.ecotra.2024.100371","title":"Microgeographic speed, reliability, and traffic externalities","year":2024,"lang":"en","type":"article","venue":"Economics of Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Western University","funders":"","keywords":"Externality; Reliability (semiconductor); Transport engineering; Environmental science; Computer science; Economics; Engineering; Microeconomics; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.004803136929475562,"gpt":0.1763129465350953,"spread":0.1715098096056198,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007079913,0.00006542398,0.00009191858,0.00007926603,0.000008208754,0.00002268178,0.00003554225,0.00002485733,0.0000175219],"category_scores_gemma":[3.816277e-7,0.00007221656,0.00004885811,0.00003200749,0.00002427856,0.0001146718,8.957077e-7,0.00003687852,0.000002886856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009644677,"about_ca_system_score_gemma":0.000004132254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001573439,"about_ca_topic_score_gemma":0.0001903542,"domain_scores_codex":[0.9996256,0.000002085965,0.0001839508,0.0001006766,0.00001903392,0.00006860316],"domain_scores_gemma":[0.9998819,0.0000179247,0.000009876178,0.00006399595,0.000005513445,0.00002081073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00001383355,0.00001564809,0.0008504554,0.0009931998,0.000135138,0.000004180868,0.001494483,0.8811899,0.0005270009,0.01287804,0.0001918543,0.1017062],"study_design_scores_gemma":[0.001732248,0.0001549552,0.4458582,0.0003455274,0.000431117,0.000006867744,0.0008074539,0.4457173,0.001764374,0.007890722,0.09436,0.0009312673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968892,0.001952357,0.0002278406,0.00008891131,0.0002771421,0.00008565572,0.00005297073,0.0001514187,0.0002745198],"genre_scores_gemma":[0.9984909,0.00119027,0.0002080763,0.000006132577,0.00002475808,0.00000376281,0.00002484692,0.00001195837,0.00003927977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4450077,"threshold_uncertainty_score":0.2944906,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}