{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":9,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":9,"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":"1fb1c4b34eba","filters":{"venue":"Transport"}},"results":[{"id":"W2089422147","doi":"10.3846/16484142.2013.785019","title":"EFFICIENCY EVALUATION IN PUBLIC ROAD TRANSPORT: A STOCHASTIC FRONTIER ANALYSIS","year":2013,"lang":"en","type":"article","venue":"Transport","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Stochastic frontier analysis; Investment (military); Frontier; Public transport; Profit (economics); Sample (material); Transport engineering; Environmental economics; Business; Econometrics; Industrial organization; Economics; Engineering; Microeconomics","retraction":null,"screen_n_in":null,"score":{"opus":0.07946227745493478,"gpt":0.35098403134698,"spread":0.2715217538920452,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.008320361,0.0003252614,0.0008856282,0.003064503,0.0001816457,0.0001586182,0.001274952,0.0001809882,0.008944831],"category_scores_gemma":[0.0006296395,0.0002589451,0.0006809025,0.01208188,0.0002200485,0.0009447798,0.00001327744,0.0002945408,0.0009696371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000149158,"about_ca_system_score_gemma":0.0003348631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001603347,"about_ca_topic_score_gemma":0.00411526,"domain_scores_codex":[0.9915656,0.0003568929,0.001810796,0.001214655,0.004335815,0.0007162123],"domain_scores_gemma":[0.9968637,0.0002853951,0.0003514354,0.001280486,0.0009620404,0.0002570071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002815295,0.0008249277,0.5441371,0.000006114108,0.0003311424,0.00002118946,0.003568033,0.3867852,0.0003007937,0.0003925434,0.000233775,0.06337102],"study_design_scores_gemma":[0.0004606174,0.00002804996,0.6862018,0.000007038668,0.0005854277,0.000001073856,0.0003608508,0.3099259,0.00001057709,0.002004948,0.0001594569,0.0002542297],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7897393,0.0002009675,0.2045568,0.0008578416,0.0001777766,0.000590227,0.00001315486,0.0000647028,0.00379923],"genre_scores_gemma":[0.9983059,0.000003360645,0.0004877639,0.0001418045,0.00003521202,0.0001211235,0.00007050901,0.00001949851,0.0008148652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2085666,"threshold_uncertainty_score":0.9999863,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1969065232","doi":"10.3846/16484142.2014.1003324","title":"Modelling bus delay at bus stop","year":2015,"lang":"en","type":"article","venue":"Transport","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Queueing theory; Transfer (computing); Block (permutation group theory); Queuing delay; Computer science; Simulation; Real-time computing; Mathematics; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.06535190371015827,"gpt":0.2931136581688241,"spread":0.2277617544586659,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003837445,0.00008279474,0.0001064725,0.00004693235,0.0002500159,0.00001306848,0.0001145008,0.00009457773,0.0001393758],"category_scores_gemma":[0.000006555628,0.00008648638,0.00004541755,0.0001878094,0.00006272863,0.0001800836,0.000001073536,0.00007410476,0.00008077775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007340276,"about_ca_system_score_gemma":0.0001668021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003234497,"about_ca_topic_score_gemma":0.002017427,"domain_scores_codex":[0.9990069,0.00002961533,0.0001809657,0.0001720848,0.0003823979,0.0002280292],"domain_scores_gemma":[0.9995068,0.00001971151,0.0000458351,0.00009763845,0.0001208545,0.000209161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005427887,0.00003237602,0.04705742,0.000005429898,0.00001022937,0.00003320492,0.04298388,0.9008238,0.000004544824,0.008267552,0.0004881539,0.000239076],"study_design_scores_gemma":[0.003353629,0.000155368,0.0198911,0.0001039397,0.0002522136,0.000008886029,0.01219647,0.06139046,0.0002266096,0.003362829,0.8977168,0.001341665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7785257,0.0001795398,0.1602217,0.0006005248,0.0004630729,0.0001930097,0.00002171586,0.0003604605,0.05943435],"genre_scores_gemma":[0.9862691,0.00006838403,0.003914009,0.00009022726,0.0001013116,0.000006648119,0.0001189885,0.00001283978,0.009418524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8972287,"threshold_uncertainty_score":0.4889614,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2009946293","doi":"10.3846/1648-4142.2008.23.230-235","title":"DECISION SUPPORT SYSTEM FOR SOLVING THE STREET ROUTING PROBLEM","year":2008,"lang":"en","type":"article","venue":"Transport","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Vehicle routing problem; Heuristics; Routing (electronic design automation); Computer science; Key (lock); Software; Operations research; Range (aeronautics); Geographic information system; Path (computing); Engineering; Computer network; Computer security; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.0230692832423031,"gpt":0.2500738406211221,"spread":0.2270045573788191,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006664763,0.0001537011,0.0001947828,0.00004583222,0.0002525953,0.00001148655,0.0002037959,0.00008142146,0.00001953008],"category_scores_gemma":[0.00001776823,0.0001231569,0.00009498995,0.0001825832,0.00002718554,0.0001063162,0.000005826676,0.0001304692,0.000008928274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006415749,"about_ca_system_score_gemma":0.00003608536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009648372,"about_ca_topic_score_gemma":0.0000181232,"domain_scores_codex":[0.9988964,0.00001382706,0.0003989387,0.0001786039,0.0001990343,0.0003132024],"domain_scores_gemma":[0.9993995,0.0001795685,0.0000441302,0.0002567942,0.00006167121,0.00005831844],"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":[0.00002422959,0.00001757222,0.03961816,0.0003059812,0.00005909834,0.00002968644,0.002170029,0.9453058,0.0008438522,0.001053219,0.0007171563,0.009855233],"study_design_scores_gemma":[0.002190886,0.0001069796,0.03559835,0.0004119602,0.000159638,0.0001841309,0.0008936652,0.9414256,0.01178923,0.00009391602,0.006265365,0.0008803467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1743326,0.00003860807,0.8215442,0.00002237797,0.0002995043,0.000444646,0.00001734789,0.0007342229,0.002566449],"genre_scores_gemma":[0.8189769,0.00001334636,0.1806892,0.00001476263,0.0000895759,0.00004442308,0.00001967417,0.00005383738,0.00009821352],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6446443,"threshold_uncertainty_score":0.5022191,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2849389845","doi":"10.3846/transport.2018.1579","title":"MODELLING THE IMPACTS OF UNCERTAIN CARBON TAX POLICY ON MARITIME FLEET MIX STRATEGY AND CARBON MITIGATION","year":2018,"lang":"en","type":"article","venue":"Transport","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"","keywords":"Carbon tax; Greenhouse gas; Stochastic programming; Constraint (computer-aided design); Environmental economics; Integer programming; Fleet management; Business; Control (management); Charter; Operations research; Economics; Computer science; Transport engineering; Engineering; Mathematical optimization","retraction":null,"screen_n_in":null,"score":{"opus":0.01278348893324701,"gpt":0.2382689986683713,"spread":0.2254855097351243,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002761218,0.0001687731,0.0001679985,0.0000492038,0.0001238154,0.000008453306,0.0001690252,0.00008953083,0.0004248091],"category_scores_gemma":[0.000003936601,0.000121583,0.00004930357,0.0002995349,0.0004415076,0.00006008615,0.00000942882,0.0001303916,0.000006000262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000495688,"about_ca_system_score_gemma":0.00005596652,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04115068,"about_ca_topic_score_gemma":0.0008555614,"domain_scores_codex":[0.9987635,0.00002700481,0.0002825518,0.0002900547,0.000322972,0.0003138898],"domain_scores_gemma":[0.9994803,0.00002784656,0.00006945758,0.0002722487,0.00001353417,0.0001366051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006577977,0.0008517329,0.4818818,0.0002520091,0.00008695702,0.00007886628,0.00865013,0.4290105,0.05510857,0.007402858,0.0002184765,0.01580036],"study_design_scores_gemma":[0.001659355,0.001542039,0.379135,0.0003097144,0.0001523479,0.00002981456,0.0004801652,0.5851497,0.02223967,0.004626979,0.003667487,0.001007655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9164136,0.00003494522,0.0001898748,0.0003058135,0.0000265883,0.0002014296,0.00002277868,0.00002409103,0.08278085],"genre_scores_gemma":[0.9989834,0.00005442592,0.0001755512,0.00007904204,0.00006586986,0.000006485139,0.00001572473,0.00001598644,0.0006034457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1561393,"threshold_uncertainty_score":0.9652344,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2914388772","doi":"10.3846/transport.2019.7672","title":"COMBINED NONPARAMETRIC CHI-SQUARED AND BINOMIAL STATISTICAL TEST ON TRUCK TRAFFIC VOLUME CHANGES IN CANADIAN PROVINCIAL HIGHWAY NETWORK","year":2019,"lang":"en","type":"article","venue":"Transport","topic":"Transport Systems and Technology","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Regina","funders":"","keywords":"Truck; Transport engineering; Negative binomial distribution; Trailer; Nonparametric statistics; Traffic volume; Distribution (mathematics); Binomial distribution; Environmental science; Engineering; Statistics; Mathematics; Automotive engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.003955001288936345,"gpt":0.1697942001686534,"spread":0.1658391988797171,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001349698,0.0002433311,0.0004336056,0.0003966845,0.00004003229,0.00001183493,0.0001364811,0.0002795037,0.0001633395],"category_scores_gemma":[0.000005506245,0.0002526373,0.00003352404,0.0004632314,0.0000521868,0.00004301133,0.000001903069,0.0003253323,0.00007018654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001325195,"about_ca_system_score_gemma":0.00009394232,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03131931,"about_ca_topic_score_gemma":0.6351858,"domain_scores_codex":[0.9985598,0.000009693292,0.000311973,0.0003142941,0.0001365203,0.0006677601],"domain_scores_gemma":[0.9994711,0.00005039171,0.00002352272,0.0002164921,0.0000118642,0.0002266887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008543842,0.0000794745,0.976207,0.0002565551,0.00003627822,0.000273519,0.0002569296,0.01421967,0.0001296201,0.002777914,0.0004171334,0.005260468],"study_design_scores_gemma":[0.001440557,0.0004545885,0.9803793,0.0000571021,0.00002141823,0.000007516064,0.00001354662,0.009598128,0.00003723467,0.0000244517,0.007614342,0.0003518174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970222,0.00006904816,0.00008595296,0.0001159912,0.0005573736,0.0006647174,0.0002915263,0.0003340985,0.0008591471],"genre_scores_gemma":[0.9993071,0.00001899925,0.0001846933,0.00002993561,0.000109195,0.00004369891,0.0001307721,0.00005381335,0.0001218206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6038665,"threshold_uncertainty_score":0.9999926,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2322806996","doi":"10.3846/16484142.2016.1156021","title":"An Octopus and a circle at the basis of a framework for the evaluation of sustainable mobility","year":2016,"lang":"en","type":"article","venue":"Transport","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Polytechnique Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Conceptualization; Sustainability; octopus (software); Sustainable development; Standardization; Representation (politics); Transport engineering; Computer science; Order (exchange); Risk analysis (engineering); Management science; Process management; Engineering; Business; Artificial intelligence; Political science","retraction":null,"screen_n_in":null,"score":{"opus":0.0231479553444116,"gpt":0.3187614833385834,"spread":0.2956135279941718,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009435449,0.00005116981,0.00008050171,0.000004005655,0.0001172553,0.000002109792,0.0001128451,0.00003629411,0.0008960384],"category_scores_gemma":[0.00002206435,0.00002541484,0.00004328654,0.00005386423,0.0003624018,0.0001152319,0.00001725158,0.00002408094,0.000001938731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001081389,"about_ca_system_score_gemma":0.00001000285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005606035,"about_ca_topic_score_gemma":0.0001887063,"domain_scores_codex":[0.9992901,0.00004422401,0.0001265223,0.0001165542,0.0002987809,0.0001238018],"domain_scores_gemma":[0.9995445,0.0001359084,0.00006155238,0.0002179023,0.000008713458,0.0000314318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001001528,0.0002626545,0.9065402,0.00002430065,0.00003145756,2.90572e-7,0.003214433,0.0001954851,0.01847197,0.0006194931,0.00002779069,0.07051183],"study_design_scores_gemma":[0.0002835479,0.0000849417,0.9786875,0.000005346169,0.00007454649,2.287294e-7,0.0009358857,0.00004826412,0.01130103,0.008415143,0.0001250054,0.00003853004],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960617,0.00003921593,0.002591206,0.0003757617,0.00001646859,0.0005996874,0.00002699983,0.000003302805,0.0002856488],"genre_scores_gemma":[0.999508,0.00002666696,0.000150658,0.00004132928,0.000007003288,0.00006205471,0.000001806129,0.000004774988,0.0001977646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07214738,"threshold_uncertainty_score":0.9810992,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200135565","doi":"10.53052/9788366249851.01","title":"ANALYSIS OF THE IMPACT OF THE COVID-19 PANDEMIC ON ROAD TRAFFIC ON SELECTED STREET ROUTES IN THE CITY","year":2021,"lang":"en","type":"book-chapter","venue":"Transport","topic":"COVID-19 impact on air quality","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Transport Canada","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Traffic volume; Road traffic; 2019-20 coronavirus outbreak; Transport engineering; Geography; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Engineering; Virology; Medicine","retraction":null,"screen_n_in":null,"score":{"opus":0.05998905537240801,"gpt":0.3253642287047809,"spread":0.2653751733323729,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001108446,0.0004233504,0.0007667681,0.0001356599,0.0001025528,0.000009113184,0.001206807,0.0002938113,0.003535391],"category_scores_gemma":[0.0001604629,0.0002094491,0.001213136,0.001128935,0.0005018089,0.00004440874,0.00004534654,0.000763481,0.000006730524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001082347,"about_ca_system_score_gemma":0.0004415279,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01145967,"about_ca_topic_score_gemma":0.05804486,"domain_scores_codex":[0.9969685,0.0003055717,0.000712775,0.0005314949,0.001173616,0.000308045],"domain_scores_gemma":[0.9973294,0.000525831,0.0005231399,0.001488022,0.00001943409,0.0001141731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001568195,0.0002281002,0.9017832,0.00003057232,0.0005257297,0.000008163185,0.00221382,0.09375214,0.0001612811,0.0001377429,0.0001639823,0.0008384516],"study_design_scores_gemma":[0.0003436996,0.000142469,0.9973966,0.00005556579,0.0006941367,0.000001547764,0.00004814434,0.0002270392,0.00004338499,0.00009524863,0.0007304837,0.0002217075],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878172,0.00002406779,0.00001220566,0.0005874274,0.00003795118,0.0006390283,0.0008474125,0.00002577478,0.01000898],"genre_scores_gemma":[0.995422,0.00004516468,0.000002159903,0.001251616,0.00001331104,0.000008001665,0.00008807377,0.00002455791,0.003145135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09561338,"threshold_uncertainty_score":0.9973755,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200491053","doi":"10.53052/9788366249851.05","title":"PARKING IN PAID PARKING ZONES - OVERVIEW OF THE SCIENTIFIC LITERATURE","year":2021,"lang":"en","type":"book-chapter","venue":"Transport","topic":"Smart Parking Systems Research","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":"Transport Canada","funders":"","keywords":"Transport engineering; Automotive industry; Car parking; Parking guidance and information; Business; Field (mathematics); Engineering; Architectural engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04605150938575443,"gpt":0.2548357115026352,"spread":0.2087842021168808,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000714234,0.0003654552,0.0006300605,0.0003021612,0.00007588378,0.0000766173,0.0005204615,0.0003931509,0.0002489233],"category_scores_gemma":[0.00001246375,0.000307247,0.0003409106,0.0003649402,0.000133111,0.00008654752,0.00003562987,0.0009044915,0.00001509938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001120363,"about_ca_system_score_gemma":0.0001275197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002148301,"about_ca_topic_score_gemma":0.000510839,"domain_scores_codex":[0.9976669,0.00003719767,0.0006725224,0.0004417398,0.0007962959,0.0003853721],"domain_scores_gemma":[0.9987639,0.00008686046,0.00009590102,0.0008834236,0.0001092754,0.00006070832],"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":[0.0002542165,0.0005219538,0.2497722,0.162914,0.005091656,0.009933058,0.05409979,0.0455698,0.03222103,0.3118143,0.01953603,0.108272],"study_design_scores_gemma":[0.0003419964,0.00001170486,0.01334624,0.02550493,0.00007784912,0.00004496713,0.00002788256,0.0003834767,0.001001016,0.0007745718,0.9577956,0.000689737],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.07706485,0.2361689,0.0002415439,0.0001493602,0.01021963,0.002536983,0.0005592332,0.0005822842,0.6724772],"genre_scores_gemma":[0.8308623,0.002187067,0.0001050762,0.00001611875,0.0003382629,0.00004068722,0.0001994714,0.0002191811,0.1660318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9382596,"threshold_uncertainty_score":0.999938,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4200348915","doi":"10.53052/9788366249851.06","title":"INTERCHANGE NODES IN PASSENGER TRANSPORT - A CASE STUDY ON THE EXAMPLE OF THE CITY OF SOSNOWIEC (POLAND","year":2021,"lang":"en","type":"book-chapter","venue":"Transport","topic":"transportation and logistics systems","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Transport Canada","funders":"","keywords":"Passenger transport; Transport engineering; Public transport; Transfer (computing); Computer science; Business; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1641456264145434,"gpt":0.3205601034367812,"spread":0.1564144770222377,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001291983,0.0002838122,0.0006488027,0.0001185803,0.0001625906,0.000008061299,0.0004387316,0.0002776515,0.0008353376],"category_scores_gemma":[0.00001601054,0.0001852097,0.0003456028,0.0001686196,0.0005323965,0.00004138382,0.0000056806,0.0005138345,0.000002375112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005572869,"about_ca_system_score_gemma":0.0003457696,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08112424,"about_ca_topic_score_gemma":0.4588386,"domain_scores_codex":[0.9975451,0.0001636303,0.0008749794,0.0003841997,0.0007900197,0.0002420667],"domain_scores_gemma":[0.9985505,0.0002965408,0.0003426544,0.0005734265,0.0001665432,0.00007035886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001318872,0.0007933976,0.4860878,0.0003394905,0.000355022,0.002827826,0.2841441,0.00002031096,0.00004223061,0.2247538,0.00004962504,0.0004545012],"study_design_scores_gemma":[0.0021841,0.0004537755,0.7878436,0.002193851,0.001093859,0.00005736096,0.1049949,0.000002994248,0.0001510214,0.002715471,0.09703904,0.001270038],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7982866,0.00018016,0.0000918427,0.000385938,0.0004969211,0.001867706,0.0005486274,0.00003419658,0.198108],"genre_scores_gemma":[0.9690824,0.00006650075,0.000006747125,0.00005609733,0.00008344196,0.00003655441,0.00003156117,0.00003286107,0.0306039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3777144,"threshold_uncertainty_score":0.9249946,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}