{"meta":{"query_hash":"6e64975e1554","filters":{"venue":"Research in Transportation Economics"},"cohort_total":29,"direct_labels_cover":0,"predictions_cover":29,"exported":29,"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/6e64975e1554","api":"https://metacan.xera.ac/api/v1/cohort?venue=Research+in+Transportation+Economics"},"results":[{"id":"W1965567461","doi":"10.1016/j.retrec.2008.05.024","title":"Public transport policy in Canada and the United States: Developing political commitment from the federal government","year":2008,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":8,"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":"Government (linguistics); Politics; Context (archaeology); Public transport; Public administration; Investment (military); Public policy; Political science; Business; Economic policy; Economics; Economic growth; Law; Geography","score_opus":0.11407607957280465,"score_gpt":0.32722906626345677,"score_spread":0.21315298669065214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965567461","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":[0.49864376,0.0030699195,0.0025423577,0.23793146,0.00060554565,0.00021026211,0.00035866204,0.00004416786,0.25659394],"genre_scores_gemma":[0.98821324,0.0005041754,0.00037445183,0.00504855,0.00005445608,0.000040595805,0.00005733504,0.000009274991,0.0056979214],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.98090476,0.004380303,0.00022452442,0.00068571104,0.0035578597,0.010246939],"domain_scores_gemma":[0.97924244,0.007271467,0.001273793,0.0003889583,0.005995089,0.005828304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013926966,0.00045556464,0.00077096844,0.0023518766,0.016756045,0.016546316,0.0022339139,0.006853631,0.005305588],"category_scores_gemma":[0.042266484,0.000459549,0.00057922513,0.004017688,0.010450445,0.004559755,0.0055911206,0.007763488,0.00022856028],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068016973,0.0005958632,0.042172555,0.0002063501,0.00015754651,0.00032619623,0.017862242,0.011658149,0.0005301731,0.829226,0.043069307,0.05351534],"study_design_scores_gemma":[0.0006251262,0.0003838124,0.26474082,0.0013545818,0.0006444825,0.000090536334,0.18554157,0.025374912,0.0022910729,0.2591352,0.25952947,0.00028838275],"about_ca_topic_score_codex":0.9638607,"about_ca_topic_score_gemma":0.9792326,"teacher_disagreement_score":0.16877723,"about_ca_system_score_codex":0.16877723,"about_ca_system_score_gemma":0.4107643,"threshold_uncertainty_score":0.9641006},"labels":[],"label_agreement":null},{"id":"W1976232131","doi":"10.1016/j.retrec.2012.02.001","title":"Part 1. National road safety performance: Data, the emergence of two single-outcome modeling streams and public health","year":2012,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Traffic and Road Safety","field":"Engineering","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":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Poisson regression; Context (archaeology); Public health; Population; Econometrics; Multivariate statistics; Poison control; Occupational safety and health; Case fatality rate; Environmental health; Statistics; Geography; Actuarial science; Economics; Political science; Medicine; Mathematics","score_opus":0.30169041691636206,"score_gpt":0.3763164332970253,"score_spread":0.07462601638066324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976232131","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":[0.30726632,0.038348023,0.1680695,0.099274956,0.0060659726,0.0027301116,0.30841735,0.0011414342,0.068686366],"genre_scores_gemma":[0.73822325,0.024631258,0.051349245,0.011461827,0.0060805455,0.004844748,0.13596731,0.00052277616,0.026919028],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99584407,0.0023181539,0.00028726962,0.00068509864,0.000724429,0.00014099153],"domain_scores_gemma":[0.96842456,0.021141574,0.0037150523,0.0042620553,0.0021121865,0.0003445318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010421952,0.0008998056,0.0009749226,0.001993938,0.0006963823,0.002190881,0.0015303501,0.0018445791,0.016006617],"category_scores_gemma":[0.04575442,0.00060589577,0.001525795,0.0050215335,0.0012514384,0.0029817245,0.0017273377,0.0023515185,0.002343238],"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":[0.00092113356,0.00096483534,0.2838504,0.0028769604,0.0013843765,0.00031833767,0.0014161873,0.041173656,0.0011201513,0.113040954,0.27962422,0.27330878],"study_design_scores_gemma":[0.00024159087,0.0005949688,0.53908587,0.0022035092,0.00071737234,0.00057839905,0.0012585475,0.06657891,0.0031626485,0.22176124,0.16356517,0.00025180506],"about_ca_topic_score_codex":0.016239982,"about_ca_topic_score_gemma":0.0135668395,"teacher_disagreement_score":0.016239982,"about_ca_system_score_codex":0.00227132,"about_ca_system_score_gemma":0.0032624416,"threshold_uncertainty_score":0.05511719},"labels":[],"label_agreement":null},{"id":"W2005637730","doi":"10.1016/j.retrec.2011.08.010","title":"DRAG-ALZ-1, a first model of monthly total road demand, accident frequency, severity and victims by category, and of mean speed on highways, Algeria 1970–2007","year":2011,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Traffic and Road Safety","field":"Engineering","cited_by":13,"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 de Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Transport engineering; Estimation; Quality (philosophy); Road accident; Accident (philosophy); Construct (python library); Drag; Regression analysis; Econometrics; Computer science; Statistics; Engineering; Economics; Mathematics","score_opus":0.03760604664686629,"score_gpt":0.24416595756478315,"score_spread":0.20655991091791687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005637730","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":[0.78001404,0.002775326,0.10139491,0.0070666242,0.0007373908,0.00024103139,0.056031283,0.0016200225,0.05011944],"genre_scores_gemma":[0.92974246,0.0008650355,0.009519462,0.00033859306,0.00023265016,0.0002948581,0.009254303,0.00017455926,0.049578134],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995023,0.00014597319,0.0000182245,0.00012222062,0.000037154623,0.0001740596],"domain_scores_gemma":[0.99889153,0.00046225195,0.00018290535,0.000059665923,0.00026557708,0.0001381269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010628919,0.0012966526,0.0021400545,0.0011911755,0.0008421824,0.0024090712,0.0037263334,0.0025063858,0.008147273],"category_scores_gemma":[0.0029221214,0.0011281123,0.0015821168,0.0013954013,0.0011028602,0.0013936018,0.0008634116,0.0017761379,0.0011874122],"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":[0.00022074654,0.00011386783,0.00786662,0.000088519315,0.00013751622,0.0001392737,0.000096502255,0.96071976,0.00020050709,0.019744957,0.007368549,0.003303181],"study_design_scores_gemma":[0.00012932553,0.000046614372,0.0034865756,0.000015548998,0.00008371372,0.00005454046,0.00006039992,0.987849,0.0001007024,0.004566142,0.0035731737,0.000034271055],"about_ca_topic_score_codex":0.24801871,"about_ca_topic_score_gemma":0.14633262,"teacher_disagreement_score":0.24801871,"about_ca_system_score_codex":0.004062238,"about_ca_system_score_gemma":0.0029641236,"threshold_uncertainty_score":0.49315017},"labels":[],"label_agreement":null},{"id":"W2015389350","doi":"10.1016/j.retrec.2009.12.007","title":"The international legal instruments in addressing piracy and maritime terrorism: A critical review","year":2010,"lang":"en","type":"review","venue":"Research in Transportation Economics","topic":"Maritime Security and History","field":"Social Sciences","cited_by":51,"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":"Terrorism; Political science; Maritime security; Politics; Constructive; International trade; Law; Computer security; Business; Computer science","score_opus":0.22818330042156657,"score_gpt":0.4794094160186292,"score_spread":0.25122611559706265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015389350","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003983488,0.99886405,0.000032538024,0.00062387186,0.00010470929,0.0000034231894,0.000007791473,6.077483e-7,0.00032324818],"genre_scores_gemma":[0.0008032911,0.99859244,0.000067159606,0.0003321655,0.0001411489,0.000005248406,0.0000066265125,5.699457e-7,0.00005135682],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983789,0.00046795927,0.00029962286,0.00023113727,0.0005159044,0.00010657738],"domain_scores_gemma":[0.9859849,0.010820212,0.0013412115,0.0001647354,0.0015092919,0.00017961743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005994747,0.0012420233,0.0034873844,0.0071837753,0.00071337476,0.0033063046,0.0018441578,0.004457562,0.0048341104],"category_scores_gemma":[0.01312599,0.0008221231,0.0013873277,0.008985356,0.003017492,0.0051383316,0.0016754757,0.0028552671,0.00074308476],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017595499,0.00010839974,0.00068408827,0.13769642,0.0007866257,0.00021935892,0.0003263246,0.00048133108,0.00028651813,0.019024817,0.037334383,0.80287576],"study_design_scores_gemma":[0.00009878212,0.00015958636,0.0034532545,0.1967586,0.0028241414,0.0005592686,0.0008147058,0.00019250046,0.00039615776,0.011888646,0.7827863,0.000068082576],"about_ca_topic_score_codex":0.006208446,"about_ca_topic_score_gemma":0.013651935,"teacher_disagreement_score":0.0071837753,"about_ca_system_score_codex":0.0029698221,"about_ca_system_score_gemma":0.010016918,"threshold_uncertainty_score":0.03170365},"labels":[],"label_agreement":null},{"id":"W2069134760","doi":"10.1016/j.retrec.2011.11.005","title":"Port competitiveness from the users' perspective: An analysis of major container ports in China and its neighboring countries","year":2011,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":178,"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":"Chinese University of Hong Kong; University of Hong Kong","keywords":"Analytic hierarchy process; Port (circuit theory); Competitor analysis; Mainland China; Business; Sample (material); China; Container (type theory); Beijing; Benchmark (surveying); Perspective (graphical); Industrial organization; Hierarchy; Telecommunications; Transport engineering; Operations research; Computer science; Marketing; Engineering; Geography; Economics","score_opus":0.044784015966701216,"score_gpt":0.2923369810068704,"score_spread":0.24755296504016916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069134760","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":[0.9983877,0.000050598323,0.00003903758,0.000038045084,0.0000010481837,0.000003472089,0.0000630843,0.000001502869,0.0014154246],"genre_scores_gemma":[0.9995735,0.000043478467,0.000012875827,0.0000057218963,0.0000012319127,0.000002190489,0.00007543305,9.293539e-7,0.00028467973],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99945825,0.00011535594,0.00002715113,0.000060006925,0.000116936106,0.00022231264],"domain_scores_gemma":[0.99911016,0.00023696035,0.00021024559,0.000033896147,0.00020384291,0.00020492391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006739882,0.00036444917,0.0003822784,0.0029174057,0.0011617258,0.0023987952,0.0005829939,0.0004698683,0.002865861],"category_scores_gemma":[0.0009276677,0.00022509825,0.0009896726,0.005429085,0.0009540201,0.0017786658,0.0012420771,0.00044609825,0.0001754447],"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":[0.00016607491,0.00011128178,0.9832477,0.000036132762,0.00012795768,0.0010768553,0.003081367,0.002201636,0.000536282,0.0025847955,0.0005103962,0.006319519],"study_design_scores_gemma":[0.0000069440134,0.00009396124,0.97754765,0.000018190218,0.00007412601,0.00010075139,0.017310116,0.0033940212,0.00023820884,0.00021178571,0.0009849782,0.000019246938],"about_ca_topic_score_codex":0.1082933,"about_ca_topic_score_gemma":0.15765823,"teacher_disagreement_score":0.1082933,"about_ca_system_score_codex":0.0032333957,"about_ca_system_score_gemma":0.0021301403,"threshold_uncertainty_score":0.21532589},"labels":[],"label_agreement":null},{"id":"W2075414451","doi":"10.1016/j.retrec.2009.10.009","title":"Moving towards more eco-efficient tourist transportation to a resort destination: The case of Whistler, British Columbia","year":2009,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Diverse Aspects of Tourism Research","field":"Social Sciences","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University","keywords":"Visitor pattern; Tourism; Public transport; Business; Destinations; Transport engineering; Carbon footprint; Marketing; Sustainable transport; Environmental economics; Travel behavior; Economics; Computer science; Engineering; Geography; Sustainability; Greenhouse gas","score_opus":0.05615193362289717,"score_gpt":0.37316750367107165,"score_spread":0.3170155700481745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075414451","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":[0.9491668,0.0002198369,0.00023451111,0.007982162,0.00003138412,0.000055408076,0.00004878125,0.000007907983,0.042253178],"genre_scores_gemma":[0.97951746,0.00037136502,0.00041479702,0.0013056165,0.0000069663124,0.000017169214,0.000035042438,0.000011935865,0.01831962],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990885,0.00017185348,0.000013879561,0.0000545466,0.00008710963,0.00058412965],"domain_scores_gemma":[0.9989409,0.00012924454,0.000044841858,0.000028594757,0.00028240966,0.0005739553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057912717,0.0002779891,0.00027539383,0.00062594505,0.018064946,0.0063689514,0.0016542659,0.0033067665,0.007817642],"category_scores_gemma":[0.0016507007,0.0002850558,0.00033383272,0.001622855,0.0033078147,0.0010979297,0.0026372694,0.0041620345,0.00037394106],"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":[0.0008383641,0.001859468,0.25032896,0.0007252815,0.00034723486,0.12877707,0.20872006,0.017347254,0.015468673,0.17075555,0.080492884,0.12433932],"study_design_scores_gemma":[0.0001392987,0.00017324218,0.15335211,0.00042981168,0.00013554859,0.0032191225,0.71884775,0.00551585,0.001013962,0.005743615,0.11125067,0.0001790151],"about_ca_topic_score_codex":0.9796068,"about_ca_topic_score_gemma":0.99589515,"teacher_disagreement_score":0.032508932,"about_ca_system_score_codex":0.032508932,"about_ca_system_score_gemma":0.04086814,"threshold_uncertainty_score":0.23586994},"labels":[],"label_agreement":null},{"id":"W2079480154","doi":"10.1016/s0739-8859(04)12005-2","title":"5. THE FISCAL TREATMENT OF SHIPPING: A CANADIAN PERSPECTIVE ON SHIPPING POLICY","year":2004,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Taxation and Compliance Studies","field":"Economics, Econometrics and Finance","cited_by":6,"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":"Perspective (graphical); Business; Finance; Computer science","score_opus":0.15295699065749174,"score_gpt":0.3549742312810704,"score_spread":0.20201724062357868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079480154","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":[0.037220106,0.018321058,0.013203832,0.104663044,0.0013747927,0.00013413244,0.0055637066,0.0001140754,0.81940544],"genre_scores_gemma":[0.6744427,0.024577081,0.01024556,0.022681618,0.0013029607,0.00016504528,0.0012455509,0.00010468969,0.2652347],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.997677,0.00035140704,0.000079767495,0.00012938087,0.00087836053,0.00088413083],"domain_scores_gemma":[0.99726933,0.00039103357,0.0002960952,0.00008583905,0.001747614,0.00021001218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001132447,0.000893538,0.00064310833,0.0040105465,0.0064214454,0.0059503326,0.0015949423,0.0046688463,0.014691825],"category_scores_gemma":[0.004254825,0.0003083066,0.0012699164,0.0064155036,0.0029450578,0.0028044772,0.0010919715,0.0032779162,0.0006610155],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001215734,0.000021879394,0.0011992063,0.00007548251,0.000013080392,0.000057539786,0.00035197442,0.0019094407,0.000058888014,0.9685689,0.021990404,0.005741106],"study_design_scores_gemma":[0.00004434491,0.000056106852,0.019793022,0.000770577,0.00018389852,0.00012966387,0.0022815706,0.005552264,0.0008521338,0.3595775,0.6106167,0.00014224013],"about_ca_topic_score_codex":0.9741979,"about_ca_topic_score_gemma":0.9801276,"teacher_disagreement_score":0.04443528,"about_ca_system_score_codex":0.04443528,"about_ca_system_score_gemma":0.060336087,"threshold_uncertainty_score":0.322402},"labels":[],"label_agreement":null},{"id":"W2092494727","doi":"10.1016/j.retrec.2011.08.009","title":"A disaggregated tool for evaluation of road safety policies","year":2011,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":5,"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":"Transport engineering; Poison control; Occupational safety and health; Business; Risk analysis (engineering); Engineering; Environmental health; Political science; Medicine","score_opus":0.23768235496419532,"score_gpt":0.4390780681236602,"score_spread":0.20139571315946486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092494727","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43030617,0.00042543994,0.3468634,0.0003341785,0.00014310458,0.0019032503,0.15959266,0.0054996926,0.054932017],"genre_scores_gemma":[0.7039697,0.00016215135,0.23723187,0.00013318771,0.000028321167,0.00200714,0.05188994,0.00035096513,0.004226662],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9946306,0.0025836986,0.0005256519,0.0004585287,0.0016037815,0.00019785264],"domain_scores_gemma":[0.984404,0.008620263,0.0011764448,0.0026356266,0.0027963913,0.00036731918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004804734,0.0010528057,0.0019260636,0.008481521,0.00055184815,0.0029779943,0.00090739276,0.0010214102,0.020212946],"category_scores_gemma":[0.022282936,0.0004364983,0.0014692253,0.007712875,0.00032568103,0.003115534,0.0021575256,0.00091615174,0.0029654712],"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":[0.0034812505,0.0020500757,0.13080466,0.0017749906,0.0034385505,0.0005901873,0.0017913065,0.35623926,0.0125726545,0.04982252,0.040181957,0.3972526],"study_design_scores_gemma":[0.0006092186,0.0025239924,0.20684086,0.00036340862,0.0009283257,0.0003499379,0.0022635951,0.6480113,0.011236679,0.056941137,0.069583245,0.00034826828],"about_ca_topic_score_codex":0.010755417,"about_ca_topic_score_gemma":0.008967087,"teacher_disagreement_score":0.020212946,"about_ca_system_score_codex":0.001848067,"about_ca_system_score_gemma":0.0015481646,"threshold_uncertainty_score":0.067619026},"labels":[],"label_agreement":null},{"id":"W2102256777","doi":"10.1016/s0739-8859(04)08014-x","title":"TECHNOLOGY CONSIDERATIONS FOR THE IMPLEMENTATION OF A STATEWIDE ROAD USER FEE SYSTEM","year":2004,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":9,"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":"Oregon Department of Transportation; McGill University","keywords":"Toll; Road pricing; Transport engineering; Toll road; User fee; State (computer science); Computer science; Data collection; Risk analysis (engineering); Business; Engineering; Traffic congestion","score_opus":0.08116379517197826,"score_gpt":0.40245337409991305,"score_spread":0.3212895789279348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102256777","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":[0.47719216,0.0010537643,0.20549674,0.043884445,0.00069748866,0.0016002588,0.00072027266,0.0011207503,0.26823407],"genre_scores_gemma":[0.9572071,0.00020456921,0.029556494,0.0011745965,0.00015796672,0.0002304007,0.000119341916,0.000056722798,0.011292786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9941958,0.002387597,0.00021245885,0.00047417803,0.0017051698,0.0010245997],"domain_scores_gemma":[0.9866774,0.008743803,0.00062633096,0.00058597984,0.0027249749,0.00064158527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006160175,0.00045868463,0.00051980803,0.0011112002,0.0022022151,0.0061179544,0.0020556834,0.004894822,0.017814165],"category_scores_gemma":[0.023721352,0.00066941645,0.00097431155,0.00094975583,0.0010813588,0.00482727,0.0013856111,0.0030620524,0.00138074],"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":[0.0009564738,0.0010951749,0.01569648,0.00025507438,0.00017768724,0.0014853249,0.0008021405,0.31898656,0.015589706,0.4978425,0.018942429,0.12817052],"study_design_scores_gemma":[0.0007528642,0.004372546,0.05177297,0.00039290625,0.00086745416,0.001360433,0.004534526,0.6652811,0.017393503,0.14073911,0.11209046,0.00044212767],"about_ca_topic_score_codex":0.019481657,"about_ca_topic_score_gemma":0.030108398,"teacher_disagreement_score":0.019481657,"about_ca_system_score_codex":0.005026959,"about_ca_system_score_gemma":0.011243988,"threshold_uncertainty_score":0.059594274},"labels":[],"label_agreement":null},{"id":"W2521578301","doi":"10.1016/j.retrec.2016.07.027","title":"Riding tandem: Does cycling infrastructure investment mirror gentrification and privilege in Portland, OR and Chicago, IL?","year":2016,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":101,"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; McGill University","funders":"","keywords":"Investment (military); Cycling; Gentrification; Privilege (computing); Walkability; Business; Socioeconomic status; Population; Economic growth; Economics; Built environment; Geography; Environmental health; Engineering; Computer security; Civil engineering; Political science","score_opus":0.06682692022406804,"score_gpt":0.3632216167204136,"score_spread":0.29639469649634553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521578301","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":[0.9961455,0.00004584718,0.000041340707,0.00070303737,0.0000066962493,0.0000029780526,0.00018087437,0.0000032072503,0.002870654],"genre_scores_gemma":[0.99884605,0.000028729719,0.00001360478,0.00004333105,0.0000056182,0.0000028320974,0.00015061138,0.000003044851,0.00090610265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996025,0.0000655629,0.000012702519,0.000058096364,0.000044263106,0.00021687392],"domain_scores_gemma":[0.9973144,0.00041009457,0.0007535201,0.000118374934,0.00029451566,0.0011091424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048084764,0.00012422714,0.00022647044,0.0008747039,0.000717934,0.0021458054,0.0009810653,0.0007685057,0.008725429],"category_scores_gemma":[0.0033812115,0.00016096828,0.00035636642,0.0016250522,0.0016027754,0.0020521102,0.0017151266,0.0013481323,0.00050506985],"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":[0.00017850685,0.00014785872,0.98782825,0.000007508978,0.000050045415,0.0000761036,0.0023103037,0.0004899909,0.00015104093,0.0031829693,0.0015600388,0.004017454],"study_design_scores_gemma":[0.00001205609,0.000039412764,0.97862774,0.000032089658,0.00003473924,0.000027304928,0.01664804,0.0010953255,0.00009591199,0.0012129149,0.0021617864,0.000012742262],"about_ca_topic_score_codex":0.22784385,"about_ca_topic_score_gemma":0.4736964,"teacher_disagreement_score":0.22784385,"about_ca_system_score_codex":0.0014619282,"about_ca_system_score_gemma":0.0015249366,"threshold_uncertainty_score":0.4530353},"labels":[],"label_agreement":null},{"id":"W2521723155","doi":"10.1016/j.retrec.2016.05.011","title":"Transportation costs and urban sprawl in Canadian metropolitan areas","year":2016,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Université du Québec à Montréal","funders":"","keywords":"Urban sprawl; Metropolitan area; Transport engineering; Environmental planning; Business; Geography; Urban planning; Engineering; Civil engineering","score_opus":0.053210462727959,"score_gpt":0.3595307000526648,"score_spread":0.3063202373247058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521723155","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":[0.9875422,0.0019511923,0.000118411386,0.0016822278,0.00004501059,0.000028061619,0.0035501656,0.0000144573,0.0050684176],"genre_scores_gemma":[0.9961085,0.0007905785,0.00011311739,0.00007898712,0.000013165048,0.000013118011,0.00097336713,0.000006871836,0.0019023092],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982583,0.0001462657,0.00010243422,0.00017442153,0.0004801927,0.0008383303],"domain_scores_gemma":[0.99502856,0.00048580253,0.0007190255,0.0001389516,0.0020665687,0.0015611273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012115926,0.00046527426,0.00058246625,0.0042531085,0.0052804747,0.0032253482,0.002374399,0.0010108063,0.0044985805],"category_scores_gemma":[0.0052924575,0.0004922454,0.0014557441,0.011833538,0.0013608173,0.0012932973,0.0017224008,0.0018124784,0.00024779522],"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":[0.00018466242,0.00015600862,0.97862625,0.00006715813,0.00019881928,0.00020616049,0.0026567602,0.0019910636,0.00008927877,0.0024519025,0.0038207502,0.009551224],"study_design_scores_gemma":[0.000009302538,0.000013186491,0.98953336,0.000051331408,0.000064572356,0.00003170514,0.005895255,0.0016767118,0.000031585932,0.00027614622,0.0023857055,0.00003122774],"about_ca_topic_score_codex":0.9987143,"about_ca_topic_score_gemma":0.99938965,"teacher_disagreement_score":0.06899997,"about_ca_system_score_codex":0.06899997,"about_ca_system_score_gemma":0.050700743,"threshold_uncertainty_score":0.50063217},"labels":[],"label_agreement":null},{"id":"W2561601373","doi":"10.1016/j.retrec.2016.11.006","title":"Preference stability in household location choice: Using cross-sectional data from three censuses","year":2016,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Microdata (statistics); Autocorrelation; Econometrics; Spatial analysis; Context (archaeology); Geography; Point estimation; Statistics; Cross-sectional data; Discrete choice; Point (geometry); Preference; Computer science; Economics; Mathematics; Census; Population; Demography","score_opus":0.5835830470459433,"score_gpt":0.46361559993930807,"score_spread":0.11996744710663526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2561601373","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":[0.99857175,0.000052874253,0.00028729215,0.000029139068,0.0000027055314,0.000008005628,0.00087294786,0.000002990552,0.00017221614],"genre_scores_gemma":[0.9975592,0.00004295238,0.00021945304,0.000013124018,0.0000035418716,0.000016005299,0.001963506,0.000003468166,0.00017878658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998116,0.0010587684,0.0001783945,0.00029636238,0.00018287006,0.00016758885],"domain_scores_gemma":[0.985704,0.007399568,0.003254877,0.0017819162,0.001109533,0.00075021584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035578776,0.0002993314,0.0004418658,0.001152246,0.0006596089,0.001410288,0.0007172163,0.00064420386,0.0024507258],"category_scores_gemma":[0.016073173,0.000472737,0.0011491845,0.0029182532,0.0004913932,0.0013747952,0.0010900389,0.00084247853,0.0005288659],"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":[0.00017891171,0.00009338571,0.997072,0.000009433691,0.00020539852,0.000022521735,0.0003680772,0.00050830125,0.000079301164,0.00009918197,0.00019254524,0.0011709629],"study_design_scores_gemma":[0.000013299533,0.00007726012,0.99523133,0.0000063516177,0.00007488379,0.0000463256,0.0009804866,0.003020947,0.000095994554,0.00015231692,0.00028811154,0.000012844259],"about_ca_topic_score_codex":0.07793767,"about_ca_topic_score_gemma":0.10027777,"teacher_disagreement_score":0.07793767,"about_ca_system_score_codex":0.0007390818,"about_ca_system_score_gemma":0.00059728016,"threshold_uncertainty_score":0.15496802},"labels":[],"label_agreement":null},{"id":"W2808030106","doi":"10.1016/j.retrec.2018.06.004","title":"The usage of location based big data and trip planning services for the estimation of a long-distance travel demand model. Predicting the impacts of a new high speed rail corridor","year":2018,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Seventh Framework Programme; Technische Universität München; European Commission","keywords":"Transport engineering; TRIPS architecture; Multinomial logistic regression; Destinations; Trip generation; Travel survey; Modal; Mode choice; Estimation; Travel behavior; Service (business); Level of service; Computer science; Public transport; Business; Geography; Engineering; Tourism; Marketing","score_opus":0.133145669900912,"score_gpt":0.38219448582511867,"score_spread":0.24904881592420666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808030106","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13504724,0.0013460953,0.5611955,0.0018786688,0.00031981242,0.0009937934,0.26132333,0.013147911,0.02474755],"genre_scores_gemma":[0.5826401,0.0015175391,0.23883803,0.00023583467,0.00010502422,0.0006594534,0.16887671,0.00044927135,0.0066780997],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931526,0.00013651673,0.00006566593,0.00018760795,0.0002467636,0.000048229933],"domain_scores_gemma":[0.99653107,0.001098665,0.000417217,0.0009163167,0.0008704369,0.0001663144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010632784,0.0013307382,0.000744706,0.0032040956,0.00061259896,0.0016082006,0.0013966823,0.00077419827,0.0060141985],"category_scores_gemma":[0.0052333307,0.0007032808,0.0012827807,0.006217255,0.00030452618,0.0013996863,0.0009148381,0.0009853006,0.002984124],"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":[0.0001580135,0.00037999937,0.06890129,0.0011768683,0.00065613847,0.000383902,0.00038247206,0.64773345,0.0037769037,0.00938757,0.04543222,0.22163114],"study_design_scores_gemma":[0.000025621108,0.000053627093,0.020099029,0.00012461896,0.00008033461,0.000100049394,0.00045229227,0.9464433,0.0016817651,0.006208006,0.024655469,0.00007596781],"about_ca_topic_score_codex":0.36789283,"about_ca_topic_score_gemma":0.4492974,"teacher_disagreement_score":0.36789283,"about_ca_system_score_codex":0.0028235444,"about_ca_system_score_gemma":0.003940596,"threshold_uncertainty_score":0.7315029},"labels":[],"label_agreement":null},{"id":"W2902480336","doi":"10.1016/j.retrec.2018.11.005","title":"Journal of the Transportation Research Forum (JTRF) / Research in Transportation Economics (RETREC)","year":2018,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","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 Saskatchewan","funders":"","keywords":"Transport engineering; Regional science; Business; Engineering; Geography","score_opus":0.16526978082326296,"score_gpt":0.4314651904232614,"score_spread":0.26619540959999843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902480336","genre_codex":"editorial","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":[0.006827323,0.062244985,0.0033202565,0.30661362,0.33436948,0.00037170196,0.015666671,0.0010571987,0.26952875],"genre_scores_gemma":[0.05482803,0.048463587,0.007651125,0.021360084,0.1200653,0.0004626139,0.014242067,0.0021153688,0.73081183],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9944278,0.000883029,0.0005600015,0.00059954444,0.0027791348,0.0007504215],"domain_scores_gemma":[0.96602017,0.004975828,0.002775343,0.0028521123,0.017040268,0.006336347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0135814855,0.0013171134,0.0014987777,0.0061980397,0.0024142861,0.009765234,0.0019242842,0.006340186,0.15149476],"category_scores_gemma":[0.03637615,0.00058939133,0.0006994295,0.0043044165,0.0015799941,0.004710165,0.0034698828,0.0046471762,0.053428102],"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":[0.00008388371,0.00008832155,0.0006909637,0.00024160037,0.00001297513,0.000052050957,0.000043578548,0.00007773163,0.00032767773,0.006299341,0.9549328,0.037149083],"study_design_scores_gemma":[0.000015823163,0.000022962551,0.0017436849,0.0002794713,0.000010809103,0.000043995085,0.00006204485,0.00013235427,0.00022391546,0.0016865009,0.99576664,0.000011797619],"about_ca_topic_score_codex":0.0067203436,"about_ca_topic_score_gemma":0.007717873,"teacher_disagreement_score":0.15149476,"about_ca_system_score_codex":0.0032604234,"about_ca_system_score_gemma":0.014693109,"threshold_uncertainty_score":0.5068004},"labels":[],"label_agreement":null},{"id":"W2905917171","doi":"10.1016/j.retrec.2018.12.002","title":"Effects of Beijing-Shanghai high-speed rail on air travel: Passenger types, airline groups and tacit collusion","year":2018,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":57,"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":"National Social Science Fund of China; National Natural Science Foundation of China","keywords":"Beijing; Air travel; Business; Tacit collusion; Aviation; China; Air transport; Transport engineering; Collusion; Industrial organization; Engineering; Geography","score_opus":0.047428617345527925,"score_gpt":0.28504036625187124,"score_spread":0.23761174890634332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905917171","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":[0.99897873,0.00011776166,0.000059181646,0.00015260375,0.000007026952,0.0000028027173,0.00012338127,0.000005250566,0.00055325555],"genre_scores_gemma":[0.9992447,0.00004229724,0.000011159306,0.000012832308,0.0000044435837,0.0000018870503,0.000096177544,0.0000016233653,0.00058503996],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991456,0.0002584256,0.0000401859,0.00012025817,0.00007509068,0.00036047515],"domain_scores_gemma":[0.9940017,0.001894367,0.0014744722,0.00027681602,0.000352324,0.0020003724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008068133,0.00036900313,0.00043371564,0.0007264273,0.0006792409,0.0018511693,0.0005922624,0.0010448019,0.009358777],"category_scores_gemma":[0.0025750066,0.00029331216,0.0010393749,0.0012807181,0.0010785968,0.0011333752,0.0016770646,0.0009824848,0.00066934444],"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":[0.00095152867,0.0001762657,0.98890746,0.000026529155,0.00039932475,0.000611833,0.000699875,0.0032713339,0.0008411132,0.001129184,0.00052109687,0.0024644425],"study_design_scores_gemma":[0.00003350285,0.00019852743,0.9899379,0.000012210694,0.00028711255,0.00006028948,0.0032562846,0.004886521,0.00029390806,0.00050354126,0.00050958095,0.000020695992],"about_ca_topic_score_codex":0.1188794,"about_ca_topic_score_gemma":0.13658169,"teacher_disagreement_score":0.1188794,"about_ca_system_score_codex":0.0018544331,"about_ca_system_score_gemma":0.001418395,"threshold_uncertainty_score":0.23637491},"labels":[],"label_agreement":null},{"id":"W3007181818","doi":"10.1016/j.retrec.2020.100828","title":"Analysis of consumer attitudes towards autonomous, connected, and electric vehicles: A survey in China","year":2020,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":121,"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 Ottawa; University of Toronto","funders":"National Key Research and Development Program of China; Beijing Municipal Commission of Education; National Natural Science Foundation of China","keywords":"Business; China; Service (business); Liability; Transport engineering; Marketing; Electric vehicle; Environmental economics; Engineering; Finance; Economics","score_opus":0.07464968264254536,"score_gpt":0.3192091382952694,"score_spread":0.24455945565272408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007181818","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":[0.99961734,0.000022273525,0.000014357791,0.000030692612,0.0000011675412,0.000002552137,0.00005483921,5.345847e-7,0.00025623335],"genre_scores_gemma":[0.99934024,0.000058265698,0.000021633256,0.000034324185,0.0000018247987,0.0000034011161,0.00010990099,5.6799604e-7,0.00042979626],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996338,0.000055528682,0.000038046164,0.00006529414,0.000106076994,0.00010131315],"domain_scores_gemma":[0.9990497,0.00014610036,0.00026209303,0.00004051995,0.00019053061,0.00031092932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051347347,0.00023582418,0.00021293486,0.0009208509,0.0007284599,0.00052515464,0.00027442328,0.0004771984,0.002097067],"category_scores_gemma":[0.00071917207,0.00030163093,0.0005003218,0.0015535894,0.00039943733,0.00054558285,0.00034795052,0.00042951197,0.00021590762],"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":[0.000029891906,0.00009389366,0.9957141,0.000013978424,0.00003295289,0.00010561098,0.0016386647,0.000054442735,0.00033724812,0.00006268921,0.000121004865,0.0017955621],"study_design_scores_gemma":[0.0000019395561,0.00004548318,0.99749315,0.0000036924507,0.000009153609,0.000043205226,0.0020115734,0.00016654977,0.000039039143,0.000014006725,0.00016792008,0.000004215837],"about_ca_topic_score_codex":0.07240764,"about_ca_topic_score_gemma":0.087248586,"teacher_disagreement_score":0.07240764,"about_ca_system_score_codex":0.0010728483,"about_ca_system_score_gemma":0.00094055705,"threshold_uncertainty_score":0.14397234},"labels":[],"label_agreement":null},{"id":"W3108306469","doi":"10.1016/j.retrec.2020.101005","title":"2020 editorial statement, Journal of the Transportation Research Forum (JTRF)","year":2020,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","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 Saskatchewan","funders":"","keywords":"Statement (logic); Transport engineering; Engineering; Library science; Business; Political science; Computer science; Law","score_opus":0.0941366642615359,"score_gpt":0.3523132654698264,"score_spread":0.2581766012082905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108306469","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":[0.000073011615,0.0018742293,0.00009175726,0.06039604,0.93554986,0.000028478336,0.0001508416,0.00004397782,0.0017918266],"genre_scores_gemma":[0.00114159,0.003202584,0.0002472247,0.040864542,0.92415506,0.00006214336,0.00018913987,0.000086780965,0.030050913],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9921808,0.0008037805,0.00094078307,0.0010574659,0.004284753,0.00073240453],"domain_scores_gemma":[0.9604772,0.008618233,0.0033668906,0.0010084267,0.020529041,0.006000237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011422571,0.0024356432,0.0025352596,0.004240842,0.0043651024,0.010460934,0.00297255,0.020247623,0.035831966],"category_scores_gemma":[0.050279845,0.0009823889,0.0021054407,0.0015008971,0.001865916,0.003920207,0.001901938,0.012612509,0.023532368],"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":[0.000033595894,0.000010952374,0.000043349963,0.00008231667,0.0000072441944,0.000042981734,0.000009185352,0.0000111264935,0.000077277226,0.00017024281,0.99686915,0.0026425915],"study_design_scores_gemma":[0.000065740736,0.000038624512,0.0008685929,0.00036727436,0.00004132747,0.00010916743,0.000082225706,0.00021900877,0.00024760352,0.00062381674,0.99731004,0.000026519996],"about_ca_topic_score_codex":0.0036043837,"about_ca_topic_score_gemma":0.0059516924,"teacher_disagreement_score":0.035831966,"about_ca_system_score_codex":0.0027877355,"about_ca_system_score_gemma":0.008168324,"threshold_uncertainty_score":0.11986983},"labels":[],"label_agreement":null},{"id":"W3153283491","doi":"10.1016/j.retrec.2021.101069","title":"A procurement policy-making pathway to future-proof large-scale transport infrastructure assets","year":2021,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Public-Private Partnership Projects","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"Australian Research Council; Government of Canada","keywords":"Procurement; Normative; Business; Risk analysis (engineering); Digitization; Economies of scale; Scale (ratio); Economics; Finance; Computer science; Marketing","score_opus":0.04603558719756837,"score_gpt":0.33310109954533285,"score_spread":0.28706551234776445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153283491","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":[0.044973176,0.0027515863,0.30931225,0.2912967,0.00078747486,0.001256447,0.00019024988,0.0003704176,0.34906173],"genre_scores_gemma":[0.85036266,0.003490796,0.111230284,0.0108345505,0.00039290206,0.0010123573,0.0001837426,0.00014045788,0.022352273],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9690966,0.017931929,0.001430586,0.0018212803,0.0068538133,0.002865813],"domain_scores_gemma":[0.9645944,0.015637832,0.0033564738,0.0033829715,0.008743811,0.0042844308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05386187,0.0007114473,0.0005654584,0.0035765995,0.0074579325,0.0233707,0.0035274003,0.010413296,0.008707185],"category_scores_gemma":[0.047112286,0.0009877279,0.00090031157,0.003575135,0.02294451,0.026545271,0.0114044165,0.010590736,0.0018653709],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005381742,0.000050939874,0.00026238099,0.00004488407,0.000003512137,0.000058301852,0.00071988575,0.0016431328,0.00011019037,0.98925436,0.00232137,0.0055257],"study_design_scores_gemma":[0.000022315524,0.000067770976,0.0007455408,0.000466479,0.000010324515,0.00011067649,0.0060488814,0.0033165258,0.00053751346,0.8941761,0.09444392,0.00005388517],"about_ca_topic_score_codex":0.0059368187,"about_ca_topic_score_gemma":0.0074408855,"teacher_disagreement_score":0.05386187,"about_ca_system_score_codex":0.0221358,"about_ca_system_score_gemma":0.06807602,"threshold_uncertainty_score":0.2848522},"labels":[],"label_agreement":null},{"id":"W4230753068","doi":"10.1016/s0739-8859(07)21014-5","title":"Acknowledgments","year":2007,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Human auditory perception and evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Dalhousie University","keywords":"Business; Political science","score_opus":0.1332119733087087,"score_gpt":0.3865923886683767,"score_spread":0.253380415359668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230753068","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018114451,0.004892747,0.05461154,0.15901686,0.08962932,0.0021418089,0.123786084,0.0055390084,0.5422683],"genre_scores_gemma":[0.09264181,0.0024652318,0.029282644,0.025469188,0.009706385,0.0014389973,0.032901965,0.0024172203,0.80367655],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99705803,0.0007960029,0.00016463289,0.0003910592,0.0013681224,0.00022217716],"domain_scores_gemma":[0.96944124,0.0047121597,0.00073243474,0.0017627537,0.018588167,0.0047631953],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003547538,0.0007424527,0.0009280209,0.0021582115,0.0012652315,0.0019578647,0.0018876565,0.00064900354,0.41294208],"category_scores_gemma":[0.029892666,0.00023291344,0.00055839424,0.0014203382,0.00058013597,0.0011072394,0.0027337668,0.0015480814,0.19000034],"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":[0.00019705124,0.00004064304,0.0015249487,0.0001641292,0.000014017503,0.00021191359,0.00025655172,0.0003179471,0.0015022784,0.011100112,0.9326597,0.05201083],"study_design_scores_gemma":[0.000055384735,0.000017448701,0.002016205,0.00013327287,0.00002317011,0.00024346959,0.0004684984,0.00050350575,0.00095631107,0.005015512,0.9905503,0.000016761025],"about_ca_topic_score_codex":0.009869999,"about_ca_topic_score_gemma":0.014269943,"teacher_disagreement_score":0.41294208,"about_ca_system_score_codex":0.002661557,"about_ca_system_score_gemma":0.0042744665,"threshold_uncertainty_score":0.8373669},"labels":[],"label_agreement":null},{"id":"W4304692135","doi":"10.1016/j.retrec.2022.101234","title":"Assessing the effects of input uncertainties on the outputs of a freight demand model","year":2022,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":6,"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 Waterloo","funders":"","keywords":"Robustness (evolution); Computer science; Econometrics; Aggregate (composite); Uncertainty analysis; Commodity; Sensitivity analysis; Economics; Operations research; Simulation; Engineering","score_opus":0.08432069474559241,"score_gpt":0.29395411285567674,"score_spread":0.20963341811008435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304692135","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":[0.9761385,0.000062121726,0.020042377,0.0002724471,0.000026097054,0.000053981967,0.0005319087,0.00015397609,0.0027185911],"genre_scores_gemma":[0.9972389,0.000017839851,0.0022798043,0.000015853117,0.000003143886,0.000016706012,0.00014285355,0.000015074242,0.00026981687],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99826497,0.0009892071,0.00007770861,0.00018693526,0.00028153256,0.00019965533],"domain_scores_gemma":[0.9771976,0.020266972,0.0007791101,0.00050377595,0.0010471592,0.00020544806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047201407,0.0013388648,0.00075035513,0.00052413455,0.0005178583,0.0017549862,0.00085910276,0.0018923944,0.0015144706],"category_scores_gemma":[0.018900495,0.00083541544,0.0009933714,0.0007890828,0.00066959293,0.0015350671,0.00083103584,0.001691742,0.00016309417],"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":[0.00016456674,0.00004939201,0.0031890958,0.000022577,0.000030761195,0.000036831152,0.000016545906,0.99422705,0.00064558163,0.00035705336,0.00006220555,0.0011983485],"study_design_scores_gemma":[0.000018819146,0.00011292759,0.0015999096,0.0000041436724,0.00002515052,0.0000055753308,0.000031492527,0.9957106,0.0019142214,0.0005112775,0.00005383455,0.000012020443],"about_ca_topic_score_codex":0.02904112,"about_ca_topic_score_gemma":0.013046854,"teacher_disagreement_score":0.02904112,"about_ca_system_score_codex":0.0025118361,"about_ca_system_score_gemma":0.0016362102,"threshold_uncertainty_score":0.057744145},"labels":[],"label_agreement":null},{"id":"W4387427308","doi":"10.1016/j.retrec.2023.101358","title":"Online shopping, brick-and-mortar retailers and transit ridership in the U.S.","year":2023,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","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 Manitoba","funders":"","keywords":"Brick and mortar; Business; Public transport; Shopping mall; Advertising; Transit (satellite); Marketing; Probit; Transport engineering; The Internet; Economics; Engineering; Computer science","score_opus":0.21521593715364218,"score_gpt":0.3529258795452075,"score_spread":0.1377099423915653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387427308","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":[0.9914938,0.0011346122,0.000035660152,0.0020499846,0.00004229735,0.0000042284223,0.001077969,0.000005698571,0.0041556815],"genre_scores_gemma":[0.9950873,0.0011542083,0.000053015163,0.00027205015,0.0000429999,0.0000050287244,0.0006772209,0.000003470523,0.0027047298],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9998485,0.000048719234,0.000013227199,0.000024127155,0.000029244633,0.000036192632],"domain_scores_gemma":[0.9978934,0.00054397946,0.0007142501,0.000057855497,0.00027587212,0.0005146876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031536142,0.000119080694,0.0001263638,0.0008797709,0.00061061705,0.0010294792,0.0002555555,0.0005165051,0.007952453],"category_scores_gemma":[0.0014765784,0.00015398528,0.00027430375,0.0021198299,0.00044466407,0.0010591641,0.00058582326,0.00072048744,0.00074992084],"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":[0.000051118903,0.00016758557,0.9849427,0.000020094789,0.00003643686,0.00006575075,0.0009671437,0.00011361783,0.000032100146,0.0004631557,0.0057666805,0.007373601],"study_design_scores_gemma":[0.0000046496352,0.000036602047,0.9913952,0.000052436913,0.000026206946,0.000054061722,0.005340051,0.00029975874,0.000019262996,0.00014514905,0.002622306,0.0000044780822],"about_ca_topic_score_codex":0.25204355,"about_ca_topic_score_gemma":0.51273173,"teacher_disagreement_score":0.25204355,"about_ca_system_score_codex":0.0007754516,"about_ca_system_score_gemma":0.0010041365,"threshold_uncertainty_score":0.501153},"labels":[],"label_agreement":null},{"id":"W4387842703","doi":"10.1016/j.retrec.2023.101370","title":"The effect of bus rapid transit on local home prices","year":2023,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","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":"Acadia University","funders":"","keywords":"Bus rapid transit; Real estate; Amenity; Leverage (statistics); Business; Transport engineering; Local government; Residential real estate; Agricultural economics; Finance; Public transport; Economics; Computer science; Geography; Engineering","score_opus":0.0581733514719594,"score_gpt":0.2931962966442408,"score_spread":0.2350229451722814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387842703","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":[0.9967001,0.00010023841,0.00009019379,0.00032966762,0.000013499714,0.0000022303386,0.00018985351,0.000008202426,0.002565906],"genre_scores_gemma":[0.99841833,0.00006211167,0.000017441282,0.00001590813,0.000010675754,9.553274e-7,0.00007633522,0.000003760986,0.0013945064],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99980026,0.00008773908,0.000005749826,0.000022221158,0.000017373755,0.00006667775],"domain_scores_gemma":[0.99712163,0.0016307222,0.00045580158,0.00008388593,0.00025527546,0.00045256063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038467292,0.0001763899,0.00022629905,0.00034327366,0.0003765517,0.0013400327,0.00026418697,0.0004947607,0.0125762895],"category_scores_gemma":[0.0035026765,0.00018218916,0.00041905206,0.000655721,0.00048163894,0.0006297208,0.0003094359,0.0008831073,0.0006512834],"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":[0.008982205,0.0017504756,0.89966434,0.00018365176,0.00084351684,0.0017777287,0.00126693,0.032002322,0.009632755,0.0118648475,0.008894262,0.023136986],"study_design_scores_gemma":[0.00020610877,0.00061356096,0.963942,0.00001854717,0.000349178,0.0001591762,0.0028434128,0.025508178,0.0017890168,0.0022445826,0.0022960415,0.000030184723],"about_ca_topic_score_codex":0.067591436,"about_ca_topic_score_gemma":0.102389894,"teacher_disagreement_score":0.067591436,"about_ca_system_score_codex":0.0013851752,"about_ca_system_score_gemma":0.000534488,"threshold_uncertainty_score":0.13439602},"labels":[],"label_agreement":null},{"id":"W4399455994","doi":"10.1016/j.retrec.2024.101447","title":"Financial subsidy, government audit and new transportation technology: Evidence from the new energy vehicle pilot city program in China","year":2024,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":14,"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 Manitoba","funders":"","keywords":"Subsidy; China; Business; Audit; Finance; Government (linguistics); Transport engineering; Pilot program; Engineering; Economics; Accounting; Medicine; Political science","score_opus":0.02818607965943279,"score_gpt":0.27042164075849673,"score_spread":0.24223556109906394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399455994","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":[0.9984224,0.00012247398,0.000022164731,0.00046317105,0.0000063938423,0.000016065796,0.00011157606,0.0000022826491,0.0008333856],"genre_scores_gemma":[0.9991327,0.00011135131,0.000013963021,0.000109361215,0.000005388124,0.00000810246,0.0001308398,8.193401e-7,0.00048751818],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99762326,0.000561421,0.0001185949,0.0001598027,0.0005062841,0.0010306564],"domain_scores_gemma":[0.9813813,0.0039734133,0.008669079,0.00069527095,0.0023426982,0.0029382221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028272602,0.00021500373,0.00043602134,0.0018152031,0.0016610245,0.0013620089,0.001087605,0.0009638154,0.0030942247],"category_scores_gemma":[0.010612237,0.00028535927,0.00039730835,0.0031217677,0.0019925702,0.0011260944,0.0015989207,0.0012405295,0.00015302113],"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":[0.00020219336,0.00036844646,0.9919035,0.000025846142,0.00004478813,0.00017017248,0.00070757745,0.00015879891,0.000057762598,0.00052593625,0.0009514973,0.004883539],"study_design_scores_gemma":[0.00003807103,0.000084959895,0.99666107,0.0000164472,0.000052261723,0.000022126093,0.0021016144,0.00029902437,0.000060785023,0.000103107726,0.00055463775,0.0000058456353],"about_ca_topic_score_codex":0.29306176,"about_ca_topic_score_gemma":0.40279597,"teacher_disagreement_score":0.29306176,"about_ca_system_score_codex":0.0041379314,"about_ca_system_score_gemma":0.014453705,"threshold_uncertainty_score":0.58271194},"labels":[],"label_agreement":null},{"id":"W4401937015","doi":"10.1016/j.retrec.2024.101476","title":"Success in tandem? The impact of the introduction of e-bike sharing on bike sharing usage","year":2024,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Bike sharing; Transport engineering; Car sharing; Tandem; Business; Computer science; Engineering","score_opus":0.058750155510847495,"score_gpt":0.3535912489129293,"score_spread":0.2948410934020818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401937015","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":[0.9821082,0.00024780375,0.0003131311,0.0031563353,0.00011207684,0.000027324402,0.00012999678,0.00003284271,0.01387233],"genre_scores_gemma":[0.9967174,0.00009951813,0.000118223885,0.00018418444,0.000044112705,0.000016156568,0.00006741361,0.000014331725,0.0027387945],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.995424,0.0011315028,0.00022675225,0.00054928265,0.0007505399,0.0019179228],"domain_scores_gemma":[0.9695454,0.009458583,0.0045599737,0.0014136429,0.0033085023,0.01171388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041683004,0.00040783273,0.00066336093,0.00068604626,0.0020949636,0.0056406646,0.0014338966,0.0026848095,0.024460552],"category_scores_gemma":[0.026850313,0.00042514227,0.000680544,0.0013370679,0.0015527059,0.0051705386,0.004370979,0.0031255363,0.0044262554],"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":[0.004289413,0.006310226,0.78015333,0.00029588636,0.00042240816,0.0010333824,0.012977447,0.0029694473,0.0033203785,0.013556404,0.007659522,0.1670122],"study_design_scores_gemma":[0.00019665984,0.002891796,0.8977757,0.0002927522,0.0003608525,0.00035566717,0.062354475,0.0037163687,0.002315292,0.006046293,0.023550203,0.00014385486],"about_ca_topic_score_codex":0.014111298,"about_ca_topic_score_gemma":0.018875165,"teacher_disagreement_score":0.024460552,"about_ca_system_score_codex":0.0014178933,"about_ca_system_score_gemma":0.0052177124,"threshold_uncertainty_score":0.08182871},"labels":[],"label_agreement":null},{"id":"W4403309774","doi":"10.1016/j.retrec.2024.101484","title":"Switch it: Canadian rail regulations, Ramsey pricing, and potential implications for U.S. rail policy","year":2024,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":1,"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 Saskatchewan","funders":"College of Agriculture and Bioresources, University of Saskatchewan","keywords":"Business; Economics; Transport engineering; Engineering","score_opus":0.05902119595072066,"score_gpt":0.32108782066347835,"score_spread":0.2620666247127577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403309774","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":[0.59969586,0.0034618936,0.016690513,0.03980023,0.0002941539,0.00018199289,0.0031634476,0.00036726796,0.33634466],"genre_scores_gemma":[0.99032587,0.0008031961,0.001873109,0.001019199,0.000017436232,0.000019283663,0.00023184589,0.00002359518,0.005686368],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99769247,0.0003656503,0.000046095505,0.0002261704,0.00085738616,0.0008122323],"domain_scores_gemma":[0.9944665,0.001670284,0.00067144755,0.00028693103,0.0024035752,0.0005012955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033535599,0.00026794712,0.00043054522,0.0010776448,0.0029886388,0.0046635866,0.001992925,0.0013211708,0.0071042543],"category_scores_gemma":[0.01792322,0.00021216029,0.0006647377,0.002548864,0.0025106848,0.0017502968,0.00082982675,0.0021911678,0.00020685929],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001692165,0.0001215334,0.027231086,0.00010920709,0.00007163547,0.00016417238,0.001096945,0.09401738,0.0006317731,0.80631244,0.03538056,0.034693997],"study_design_scores_gemma":[0.000289098,0.00023555494,0.12993062,0.0006510533,0.00047146832,0.00013201506,0.011987038,0.392789,0.0028437125,0.27806064,0.18213116,0.00047866552],"about_ca_topic_score_codex":0.97948486,"about_ca_topic_score_gemma":0.9807358,"teacher_disagreement_score":0.94193447,"about_ca_system_score_codex":0.058065522,"about_ca_system_score_gemma":0.074463,"threshold_uncertainty_score":0.42129678},"labels":[],"label_agreement":null},{"id":"W4406755942","doi":"10.1016/j.retrec.2025.101519","title":"An importance-performance analysis of public transport to the university campus based on best-worst scaling","year":2025,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Cambridge; University of Alberta","keywords":"Public transport; Scaling; Transport engineering; Computer science; Public university; Engineering; Political science; Mathematics; Public administration","score_opus":0.06098057230926785,"score_gpt":0.35291137348244067,"score_spread":0.2919308011731728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406755942","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":[0.9801383,0.0000524364,0.016152928,0.000078630976,0.0000263477,0.00026153872,0.00017389069,0.000035381443,0.0030805317],"genre_scores_gemma":[0.9953086,0.000023122586,0.0038690928,0.000009330598,0.000007116049,0.00017910256,0.00012757826,0.000009764162,0.0004662455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9903374,0.006712633,0.0003595121,0.0008399238,0.0011643651,0.0005862383],"domain_scores_gemma":[0.9609668,0.0300028,0.0029750713,0.002528057,0.0028079757,0.0007192854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012078471,0.0011073938,0.00073375116,0.0012466956,0.0005674736,0.002095209,0.0007512942,0.0007422836,0.0039719474],"category_scores_gemma":[0.03194962,0.00027775543,0.0016282093,0.0011657125,0.0011838935,0.001999828,0.0011541432,0.0010153818,0.00029830268],"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":[0.013766349,0.012848258,0.1774175,0.000959583,0.0011558112,0.00036769296,0.0016106368,0.6235697,0.024314487,0.025006605,0.0018850106,0.1170983],"study_design_scores_gemma":[0.00016182638,0.015485208,0.1626414,0.000046758163,0.00035017976,0.00007260427,0.0018475804,0.8006467,0.00923058,0.008014858,0.0013672299,0.0001349907],"about_ca_topic_score_codex":0.002864665,"about_ca_topic_score_gemma":0.0012707212,"teacher_disagreement_score":0.012078471,"about_ca_system_score_codex":0.0020762554,"about_ca_system_score_gemma":0.0010744213,"threshold_uncertainty_score":0.06387776},"labels":[],"label_agreement":null},{"id":"W4411047196","doi":"10.1016/j.retrec.2025.101583","title":"Establishing a framework of support to scale in mobility as a Service: Consolidated insights from the literature on potential governance frameworks","year":2025,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transportation and Mobility Innovations","field":"Engineering","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":"Crohn's and Colitis Canada; Canadian Foundation for Pharmacy; Cooperative Research Centres, Australian Government Department of Industry","keywords":"Corporate governance; Process management; Scale (ratio); Business; Service (business); Risk analysis (engineering); Transport engineering; Industrial organization; Engineering; Marketing; Finance; Geography","score_opus":0.01391464450378224,"score_gpt":0.30008067123633514,"score_spread":0.2861660267325529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411047196","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":[0.11163219,0.0016625171,0.34903893,0.06472258,0.00032174334,0.00036254938,0.00022472808,0.00019488439,0.47183987],"genre_scores_gemma":[0.9858649,0.00028474972,0.010113861,0.00048028608,0.0001042463,0.00017687729,0.00003142655,0.000030391206,0.0029132618],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99077386,0.0041232225,0.00046072598,0.0015204031,0.0016148258,0.0015069802],"domain_scores_gemma":[0.9856995,0.0069488892,0.0018056959,0.0022512295,0.0019333014,0.0013613922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011133314,0.0007435877,0.0010440095,0.002450721,0.0044994093,0.014017334,0.0026636412,0.006934838,0.007595838],"category_scores_gemma":[0.025703592,0.0005189355,0.0011675406,0.0027713845,0.034530964,0.017098095,0.009158776,0.0049052266,0.0006103311],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000002011559,0.000004559114,0.00012571653,0.0000064214887,0.0000025071192,0.000014091248,0.00025047967,0.0005364096,0.000018609604,0.99799514,0.0002037751,0.00084045454],"study_design_scores_gemma":[0.000014717396,0.000012006686,0.00030468774,0.00005646599,0.0000068404725,0.000020342533,0.0006889421,0.0026723314,0.00004542261,0.99028265,0.005886863,0.000008640079],"about_ca_topic_score_codex":0.0050229034,"about_ca_topic_score_gemma":0.0054852464,"teacher_disagreement_score":0.014017334,"about_ca_system_score_codex":0.006768472,"about_ca_system_score_gemma":0.008924879,"threshold_uncertainty_score":0.058879316},"labels":[],"label_agreement":null},{"id":"W4415595466","doi":"10.1016/j.retrec.2025.101661","title":"Analysis of the spatial range advantage of vehicle owners and its implications on vehicle ownership aspirations: Insights from India and takeaways for transportation equity","year":2025,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Urban Transport and Accessibility","field":"Social Sciences","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 British Columbia","funders":"","keywords":"Equity (law); Car ownership; Public transport; Range (aeronautics); Context (archaeology); Travel behavior; Vehicle miles of travel; Survey data collection","score_opus":0.11843764944469513,"score_gpt":0.39916797723678127,"score_spread":0.2807303277920861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415595466","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":[0.9890644,0.00012078288,0.00029128324,0.0004032383,0.0000021407716,0.0000052235737,0.00008770599,0.0000030790618,0.010022244],"genre_scores_gemma":[0.9995402,0.000030971954,0.00003167724,0.0000057705697,9.129715e-7,0.0000011530008,0.00001612096,6.4411375e-7,0.00037259946],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99966645,0.00008548805,0.00000974302,0.000036547568,0.00005513394,0.00014658325],"domain_scores_gemma":[0.9981201,0.0010232563,0.00032773253,0.00009419094,0.00023014135,0.00020462579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037856845,0.00013004075,0.00020276276,0.0009747159,0.001008283,0.0018175133,0.0005494456,0.00027375377,0.0047039036],"category_scores_gemma":[0.0018173271,0.000116979456,0.0003714982,0.002037659,0.0016335469,0.0012596127,0.0013048919,0.00082928175,0.00019654437],"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":[0.00021729266,0.00026381828,0.8441466,0.000100828576,0.0001261507,0.0010159193,0.022909163,0.004537368,0.0011184308,0.094307594,0.0013863144,0.029870592],"study_design_scores_gemma":[0.000010511937,0.00011862618,0.9014989,0.0000560838,0.00011667917,0.00028643996,0.06667336,0.006383826,0.0006148561,0.019731654,0.0044768928,0.00003209773],"about_ca_topic_score_codex":0.07999472,"about_ca_topic_score_gemma":0.119783364,"teacher_disagreement_score":0.07999472,"about_ca_system_score_codex":0.001769662,"about_ca_system_score_gemma":0.0011878494,"threshold_uncertainty_score":0.15905821},"labels":[],"label_agreement":null},{"id":"W4416970916","doi":"10.1016/j.retrec.2025.101692","title":"Towards a revitalization of passenger rail services in South African cities: Lessons from international institutional reforms","year":2025,"lang":"en","type":"article","venue":"Research in Transportation Economics","topic":"Transport and Economic Policies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Devolution (biology); Passenger transport; Transport policy; Private sector; Public transport; Key (lock); Taxis","score_opus":0.05083980442437745,"score_gpt":0.30717503577617294,"score_spread":0.2563352313517955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416970916","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":[0.7932985,0.0057282606,0.0027515509,0.07335237,0.00021717403,0.00027820727,0.000067174224,0.0000345399,0.12427232],"genre_scores_gemma":[0.99279904,0.0018042634,0.00047822658,0.00094434014,0.00001859859,0.000035810117,0.000014644788,0.000012118365,0.0038930061],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9955375,0.0018370528,0.00021918758,0.00023793585,0.0003672245,0.0018011876],"domain_scores_gemma":[0.99622345,0.0014519168,0.00080981216,0.00041879574,0.00047177917,0.0006241198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006358471,0.00043304515,0.00026523357,0.0019399575,0.010501888,0.012345685,0.0012582588,0.0023947877,0.004804403],"category_scores_gemma":[0.007656931,0.0005251099,0.0003715464,0.003988384,0.021785485,0.009002272,0.012021206,0.005423238,0.00024441685],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006487559,0.00010206753,0.005349678,0.0006005848,0.000015676822,0.002980084,0.25657353,0.0019262036,0.0013489969,0.69235927,0.0038397766,0.034839287],"study_design_scores_gemma":[0.000040360293,0.00010020449,0.022343164,0.00165138,0.00002593846,0.00057732756,0.6326163,0.0012673469,0.0014121601,0.028985847,0.31090382,0.00007616383],"about_ca_topic_score_codex":0.07125271,"about_ca_topic_score_gemma":0.09963806,"teacher_disagreement_score":0.07125271,"about_ca_system_score_codex":0.03598083,"about_ca_system_score_gemma":0.04049706,"threshold_uncertainty_score":0.26106048},"labels":[],"label_agreement":null}]}