{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":1124,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":1124,"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":"0cec8acfd36d","filters":{"topic":"Vehicle emissions and performance"}},"results":[{"id":"W2023071828","doi":"10.1016/j.trb.2011.02.004","title":"The Pollution-Routing Problem","year":2011,"lang":"en","type":"article","venue":"Transportation Research Part B Methodological","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":1163,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"Engineering and Physical Sciences Research Council","keywords":"Vehicle routing problem; Routing (electronic design automation); Greenhouse gas; Fuel efficiency; Pollution; Extension (predicate logic); Function (biology); Mathematical optimization; Computer science; Operations research; Transport engineering; Environmental science; Automotive engineering; Engineering; Mathematics; Computer network","retraction":null,"screen_n_in":null,"score":{"opus":0.4927973662076421,"gpt":0.4359530616057904,"spread":0.05684430460185164,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004325977,0.00008886235,0.0001094835,0.00004736879,0.0004827189,0.00002476395,0.0002171954,0.00009534501,0.0004526043],"category_scores_gemma":[0.0001269329,0.00005424796,0.00005185949,0.000353031,0.0001676716,0.00009057602,0.000005403148,0.0004931283,0.00007547553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000206761,"about_ca_system_score_gemma":0.00002172694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003804252,"about_ca_topic_score_gemma":0.00005449553,"domain_scores_codex":[0.9983934,0.0004149685,0.0002734746,0.0001507056,0.0003157874,0.0004516805],"domain_scores_gemma":[0.9989462,0.0006401219,0.00001760245,0.0001792283,0.00009820497,0.0001186674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007799732,0.0003337488,0.08449109,0.0003864933,0.0003028599,0.0001561856,0.01793749,0.01846459,0.03046115,0.3515959,0.04222217,0.4528683],"study_design_scores_gemma":[0.0005734178,0.0002939355,0.6832359,0.00008868361,0.0000176072,0.000005836024,0.001431259,0.01480967,0.01852952,0.01963761,0.2609208,0.000455664],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8921363,0.0007009828,0.05705335,0.0006911763,0.0004332524,0.0007586706,0.00002502661,0.000742825,0.04745837],"genre_scores_gemma":[0.9728913,0.0004966998,0.02599723,0.00001985911,0.00008735104,0.0001010705,0.000008353551,0.00001381795,0.0003843108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5987449,"threshold_uncertainty_score":0.4955699,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1969029115","doi":"10.1016/j.ejor.2013.12.033","title":"A review of recent research on green road freight transportation","year":2014,"lang":"en","type":"review","venue":"European Journal of Operational Research","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":738,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"","keywords":"Transport engineering; Traffic management; Green logistics; Sustainable transport; Traffic planning; Road traffic; Business; Computer science; Environmental economics; Engineering; Sustainability; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.2809694111096483,"gpt":0.4583880352755617,"spread":0.1774186241659133,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01701055,0.0002235203,0.0009441361,0.0008337051,0.0001711773,0.00005186064,0.0007855319,0.00007728767,0.001180456],"category_scores_gemma":[0.0003744043,0.0001578257,0.0002930569,0.001059824,0.0001028701,0.000147186,0.00003043044,0.002433521,0.0003159918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001871924,"about_ca_system_score_gemma":0.0005597548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004540768,"about_ca_topic_score_gemma":0.000001407015,"domain_scores_codex":[0.9931296,0.002773874,0.001534007,0.0001970714,0.002003403,0.0003620895],"domain_scores_gemma":[0.996501,0.0004998061,0.0002058036,0.000359972,0.002197446,0.0002359323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001285614,0.00004119103,4.578646e-7,0.04349842,0.00007561946,0.00005463387,0.00004264625,0.0001787551,0.000007654055,0.0001919491,0.04648563,0.9094102],"study_design_scores_gemma":[0.0001342262,0.000339381,0.00002962206,0.1206841,0.00002898385,0.00003760643,0.000004092276,0.0001306754,0.000008118337,0.000006565056,0.878479,0.0001176161],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002590754,0.9821084,0.00006023589,0.0002625998,0.000153304,0.0003816481,0.00004201398,0.000008176386,0.01695778],"genre_scores_gemma":[0.00009090482,0.9981592,0.0002394517,0.0000437803,0.0008151653,0.000009962349,0.00008413503,0.00008168411,0.0004757074],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9092926,"threshold_uncertainty_score":0.9998679,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2054974723","doi":"10.1016/j.trd.2011.01.011","title":"A comparative analysis of several vehicle emission models for road freight transportation","year":2011,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":397,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"HEC Montréal","funders":"","keywords":"Greenhouse gas; Transport engineering; Process (computing); Traffic management; Environmental science; Computer science; Engineering; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.09033477990017989,"gpt":0.2951937572182257,"spread":0.2048589773180458,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000325125,0.0001873218,0.0003966832,0.0002769905,0.0001437812,0.000005184979,0.000109346,0.0001138881,0.0004294463],"category_scores_gemma":[3.957352e-7,0.0001760817,0.0001580007,0.0003980209,0.0001338566,0.0002763667,8.573455e-7,0.0001835553,0.000002404358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000280203,"about_ca_system_score_gemma":0.00001698898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000198463,"about_ca_topic_score_gemma":0.000295499,"domain_scores_codex":[0.9984178,0.00002202929,0.0005163327,0.0002928933,0.0004052728,0.0003456914],"domain_scores_gemma":[0.999476,0.0000352515,0.000047429,0.0001938453,0.00005002312,0.0001974884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0008826563,0.0005563452,0.1088988,0.0006845587,0.00175262,0.00001720093,0.0485548,0.8199183,0.0114631,0.00184279,0.0003173708,0.005111481],"study_design_scores_gemma":[0.000791137,0.0001664413,0.7175055,0.00004777854,0.0004376087,9.960664e-8,0.0005191213,0.2683012,0.008910191,0.0003716517,0.002694932,0.0002544025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9727683,0.0002837456,0.02516701,0.00001834481,0.00003112829,0.0004892732,0.0005105971,0.0000514362,0.0006801488],"genre_scores_gemma":[0.9960758,0.001236921,0.001494898,0.000005404531,0.00001577851,0.0001688992,0.0008488604,0.00001970102,0.0001337319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6086067,"threshold_uncertainty_score":0.7180401,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1977923271","doi":"10.1021/es048293+","title":"Life Cycle Assessment of Switchgrass- and Corn Stover-Derived Ethanol-Fueled Automobiles","year":2005,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":273,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"Natural Resources Canada; Ontario Ministry of Food and Agriculture","keywords":"Corn stover; Greenhouse gas; Life-cycle assessment; Stover; Ethanol fuel; Corn ethanol; Biofuel; Cellulosic ethanol; Gasoline; Environmental science; Environmental engineering; Waste management; Engineering; Agronomy; Crop; Production (economics); Cellulose; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.004555043552259096,"gpt":0.2229272860279661,"spread":0.218372242475707,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001515359,0.0001198757,0.0001504359,0.0002151262,0.0001297779,0.0000114495,0.0002796095,0.0001028981,0.0001771166],"category_scores_gemma":[0.00001230319,0.0001111149,0.00001893638,0.0003455034,0.000842676,0.000221919,0.0001694844,0.0001835361,0.0000169503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001372068,"about_ca_system_score_gemma":0.00003175962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002999339,"about_ca_topic_score_gemma":0.000002343607,"domain_scores_codex":[0.9990965,0.000005038346,0.0001808666,0.0002233253,0.0002023693,0.0002919426],"domain_scores_gemma":[0.9995775,0.00001199917,0.00003934219,0.0002442628,0.000003197268,0.0001237425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001164429,0.00004236031,0.02124046,0.000006785784,0.000005282588,8.098095e-7,0.00007180343,0.006670187,0.9360306,0.0001256684,0.00002071671,0.03578413],"study_design_scores_gemma":[0.0005293596,0.000174519,0.2350362,0.00002736537,0.00001053423,0.0000248018,0.0004254658,0.2774424,0.481195,0.0001777424,0.004637432,0.0003191485],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975448,0.0002546957,0.0006457716,0.0002792592,0.00005996668,0.000112253,0.000007037904,0.0001771629,0.0009190641],"genre_scores_gemma":[0.9961921,0.0002925442,0.003404378,0.00003699612,0.00001586553,0.00001622167,0.000001104482,0.00001117996,0.00002962848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4548356,"threshold_uncertainty_score":0.4531135,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1526449531","doi":"","title":"A Lifecycle Emissions Model (LEM): Lifecycle Emissions from Transportation Fuels, Motor Vehicles, Transportation Modes, Electricity Use, Heating and Cooking Fuels, and Materials","year":2003,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":164,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Oak Ridge National Laboratory; Natural Resources Canada; U.S. Department of Energy","keywords":"Greenhouse gas; Environmental science; Waste management; Methane; NOx; Criteria air contaminants; Particulates; Ozone; Environmental engineering; Engineering; Air pollution; Air pollutants; Chemistry; Combustion","retraction":null,"screen_n_in":null,"score":{"opus":0.01340073361577972,"gpt":0.1986505209627934,"spread":0.1852497873470136,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001550332,0.0004657879,0.0004326484,0.0001646244,0.0004015883,0.0008700663,0.0001661267,0.0003108667,0.0001161906],"category_scores_gemma":[0.00009463899,0.0004585134,0.00008919066,0.00036997,0.00005409583,0.004186315,0.00001513106,0.0004932031,0.00001929585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003881133,"about_ca_system_score_gemma":0.00008723189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003012383,"about_ca_topic_score_gemma":0.000007059827,"domain_scores_codex":[0.9978026,0.00006465577,0.0007285699,0.0005381929,0.000305798,0.0005602238],"domain_scores_gemma":[0.9987705,0.000181776,0.0001173353,0.0002866498,0.00003725876,0.0006064473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004297964,0.000479585,0.2929495,0.001010071,0.0002909533,0.00007122521,0.001133085,0.02296973,0.6510907,0.00299823,0.001709713,0.02486742],"study_design_scores_gemma":[0.004705719,0.0002604762,0.174548,0.00190761,0.0003308647,0.00002925941,0.0003607992,0.335308,0.4235601,0.02183698,0.03335629,0.003795898],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869259,0.0008917676,0.003478196,0.00006382839,0.00006077575,0.0003742292,0.007139268,0.0005724461,0.0004935614],"genre_scores_gemma":[0.9931989,0.0005238039,0.004122159,0.0001105204,0.00007294254,0.00004365906,0.001590809,0.0001411161,0.0001961105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3123383,"threshold_uncertainty_score":0.9997867,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3184563094","doi":"10.1016/j.rser.2021.111521","title":"Driving conditions-driven energy management strategies for hybrid electric vehicles: A review","year":2021,"lang":"en","type":"review","venue":"Renewable and Sustainable Energy Reviews","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":163,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Chongqing; National Natural Science Foundation of China","keywords":"Energy management; Driving cycle; Field (mathematics); Domain (mathematical analysis); Fuel efficiency; Energy (signal processing); Energy consumption; Computer science; Transport engineering; Risk analysis (engineering); Systems engineering; Environmental economics; Automotive engineering; Engineering; Power (physics); Electric vehicle; Business","retraction":null,"screen_n_in":null,"score":{"opus":0.01759049106796133,"gpt":0.2732645704153369,"spread":0.2556740793473756,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000621799,0.0008364122,0.003179213,0.0003349407,0.0004087176,0.0002433662,0.0004041512,0.0002273972,0.0001137149],"category_scores_gemma":[0.00003520699,0.0007047168,0.0007590855,0.0009785115,0.00003218715,0.0003040774,0.0001782356,0.0002308936,0.000005471608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002818335,"about_ca_system_score_gemma":0.0003305802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009590406,"about_ca_topic_score_gemma":0.00001948739,"domain_scores_codex":[0.9965549,0.0002021754,0.001285174,0.0006855865,0.0001930455,0.001079109],"domain_scores_gemma":[0.9983956,0.0001410612,0.0002992598,0.0007643561,0.0001466676,0.0002530133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[4.928138e-7,0.0000193061,9.455449e-8,0.2066499,0.0002012961,0.00007629622,0.000003768156,0.0006158775,0.000001029904,0.008576472,0.09279998,0.6910555],"study_design_scores_gemma":[0.0001314497,0.00003660582,2.98885e-8,0.07725389,0.00103866,0.0001100455,0.00005713489,0.001479034,0.0000057151,0.0003713151,0.9187918,0.0007242916],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[4.326278e-7,0.9838778,0.007659259,0.00001405643,0.0001167271,0.0009846477,0.00001820847,0.0001587632,0.007170146],"genre_scores_gemma":[0.00000494918,0.9718923,0.0004839346,0.0001749954,0.0002290303,0.003245484,0.0005944634,0.0001466182,0.02322823],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8259919,"threshold_uncertainty_score":0.9995404,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2037156026","doi":"10.1139/l03-017","title":"Comparison of MOBILE5a, MOBILE6, VT-MICRO, and CMEM models for estimating hot-stabilized light-duty gasoline vehicle emissions","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":150,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Environmental science; Gasoline; Emission inventory; Acceleration; Meteorology; Environmental engineering; Atmospheric sciences; Air quality index; Engineering; Waste management; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.01635507644052815,"gpt":0.2390256014856303,"spread":0.2226705250451022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003337675,0.0002047921,0.00045826,0.0002630797,0.0001071731,0.00003644373,0.0001554719,0.000110491,0.00006637562],"category_scores_gemma":[0.0001595688,0.0002006538,0.0001054657,0.0002037161,0.00002413623,0.0002453832,0.000007501706,0.0003120721,4.708532e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001077015,"about_ca_system_score_gemma":0.0002244306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004908228,"about_ca_topic_score_gemma":0.001183303,"domain_scores_codex":[0.9987156,0.00001216654,0.0006344483,0.0001137937,0.0001161716,0.0004077617],"domain_scores_gemma":[0.9987966,0.0001159709,0.0001203276,0.0001699525,0.0001472481,0.0006498553],"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":[0.000005667591,0.00001205208,0.0007480297,0.0002549717,0.00003746931,0.000004649955,0.0007044628,0.9663467,0.02992448,0.0001067502,0.0007479321,0.001106815],"study_design_scores_gemma":[0.0007065398,0.00007187275,0.0001690876,0.0004197604,0.00003347338,0.0000628064,0.0001572222,0.9739802,0.0175221,0.00009633803,0.006558019,0.0002225173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8490006,0.006235262,0.1428588,0.00005054014,0.0007340875,0.0002708772,0.00004177999,0.0000496336,0.0007584301],"genre_scores_gemma":[0.9788294,0.00004711892,0.02092844,0.000006698983,0.0001002314,0.000009546093,0.000002057831,0.0000522267,0.00002428967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1298288,"threshold_uncertainty_score":0.8182424,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2055758422","doi":"10.3155/1047-3289.60.10.1204","title":"Updating the Conceptual Model for Fine Particle Mass Emissions from Combustion Systems Allen L. Robinson","year":2010,"lang":"en","type":"review","venue":"Journal of the Air & Waste Management Association","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":148,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Combustion; Volatility (finance); Aerosol; Particulates; Environmental science; Environmental chemistry; Atmospheric sciences; Chemistry; Environmental engineering; Meteorology; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.02678282274668617,"gpt":0.2591617536581421,"spread":0.2323789309114559,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001089268,0.0002140938,0.0005425605,0.00004969947,0.0002574715,0.00008939151,0.0005139263,0.000203947,0.000008191843],"category_scores_gemma":[0.00008089255,0.0001205713,0.0003799755,0.0001329947,0.00001132355,0.0001742137,0.00007864786,0.000623068,0.000005662452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004212991,"about_ca_system_score_gemma":0.00003355931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000268985,"about_ca_topic_score_gemma":0.000004438964,"domain_scores_codex":[0.9983527,0.0001167399,0.000798446,0.0001073447,0.0003976768,0.0002270892],"domain_scores_gemma":[0.9981964,0.0002388231,0.001119748,0.0002824366,0.0001091546,0.00005342076],"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":[0.000007081087,0.00002635417,0.0000476697,0.001632956,0.0007243749,8.598706e-7,0.0003917911,0.7568926,0.00004353979,0.0003567085,0.03474883,0.2051272],"study_design_scores_gemma":[0.000279365,0.00001206652,0.000008854936,0.002943349,0.0007938154,0.000001219714,0.0002696732,0.5282167,0.000008866325,0.00005068822,0.4672863,0.0001290976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003229316,0.9655978,0.02220576,0.00103783,0.004835444,0.002120464,0.0001808895,0.00008939193,0.000703076],"genre_scores_gemma":[0.01766777,0.9750457,0.001124811,0.00003898077,0.001291265,0.00008770458,0.00005296703,0.00008112147,0.004609674],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4325374,"threshold_uncertainty_score":0.4916756,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1991325560","doi":"10.1080/02786826.2015.1047012","title":"Measurement of Aircraft Engine Non-Volatile PM Emissions: Results of the Aviation-Particle Regulatory Instrumentation Demonstration Experiment (A-PRIDE) 4 Campaign","year":2015,"lang":"en","type":"article","venue":"Aerosol Science and Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":144,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"Federal Aviation Administration","keywords":"Instrumentation (computer programming); Particulates; Environmental science; Engine power; Particle number; NOx; Range (aeronautics); Nuclear engineering; Automotive engineering; Engineering; Aerospace engineering; Chemistry; Power (physics); Physics; Nuclear physics; Computer science; Plasma; Thermodynamics","retraction":null,"screen_n_in":null,"score":{"opus":0.0161892947187823,"gpt":0.2351318783437023,"spread":0.21894258362492,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005631539,0.00006892068,0.00009249545,0.00007926121,0.0001019117,0.000008168195,0.0001697282,0.00006128613,0.000002451837],"category_scores_gemma":[0.0001288028,0.00005092956,0.00001168858,0.0007169181,0.0002807351,0.0002053842,0.00005219824,0.00007049576,0.000001085936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008455359,"about_ca_system_score_gemma":0.0001649638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001699124,"about_ca_topic_score_gemma":0.000008861415,"domain_scores_codex":[0.9990767,0.000007717734,0.0002647394,0.0001259162,0.0003860012,0.0001389284],"domain_scores_gemma":[0.9993722,0.000007185007,0.00007676445,0.0002536132,0.0002329162,0.0000573067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007488567,0.00002268845,0.005665382,0.00001199422,0.000003932912,9.350619e-8,0.0004657149,0.00145832,0.9788184,0.0001875795,0.0001686498,0.01318973],"study_design_scores_gemma":[0.000388724,0.00008214072,0.00354597,0.00006263955,0.000004426522,0.000002631417,0.0004837019,0.04979376,0.9454045,0.0001187532,0.00005639232,0.00005632348],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983817,0.0002272509,0.0005744317,0.00028573,0.0001183711,0.0001579389,0.000002316671,0.0000472695,0.0002049357],"genre_scores_gemma":[0.9990735,0.00002313691,0.0008602528,0.000006074583,0.000008338175,0.00001540303,5.63178e-7,0.000004024163,0.000008720564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04833544,"threshold_uncertainty_score":0.2076847,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2616591444","doi":"10.1109/tie.2017.2703673","title":"Cyber-Physical Control for Energy-Saving Vehicle Following With Connectivity","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":143,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Benchmark (surveying); Controller (irrigation); Vehicle dynamics; Computer science; Transmission (telecommunications); Automotive engineering; Variety (cybernetics); Optimal control; Work (physics); Control (management); Variable (mathematics); Efficient energy use; Model predictive control; Scheme (mathematics); State (computer science); Engineering; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.0184249217634253,"gpt":0.2400631706224222,"spread":0.2216382488589969,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001441174,0.0002182246,0.0002801518,0.00005933249,0.0009046744,0.0001247873,0.0002288074,0.0001849994,0.00001067936],"category_scores_gemma":[0.00001055126,0.0001984818,0.0001749968,0.00008556381,0.00003892387,0.0003220435,7.863907e-7,0.0005537586,0.000004257528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001792948,"about_ca_system_score_gemma":0.0001212415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006001442,"about_ca_topic_score_gemma":0.0002036284,"domain_scores_codex":[0.9989328,0.00002012661,0.0001577707,0.0002271746,0.0001695718,0.0004925259],"domain_scores_gemma":[0.9992026,0.0001781559,0.00005587385,0.0004129225,0.00003385754,0.0001165955],"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":[0.001116717,0.0003712535,0.0002262076,0.00003110673,0.0008461519,0.00001176509,0.0001936707,0.5065879,0.04887604,0.001117092,0.0005444168,0.4400777],"study_design_scores_gemma":[0.008357643,0.0009529203,0.00008820549,0.0001200657,0.000248576,0.000008931121,0.00002534824,0.7808736,0.194462,0.0002413426,0.01397258,0.0006487578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6500795,0.00003388541,0.3481746,0.0001359137,0.0006529933,0.0002443662,0.00003714691,0.0001875592,0.0004540454],"genre_scores_gemma":[0.9991941,0.00002121947,0.00006384156,0.0000255433,0.0003224389,0.0001356788,0.000001900044,0.00005457829,0.0001807368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.439429,"threshold_uncertainty_score":0.8093854,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389828818","doi":"10.1007/s42823-023-00647-4","title":"Carbon dynamics in agricultural greenhouse gas emissions and removals: a comprehensive review","year":2023,"lang":"en","type":"review","venue":"Carbon letters","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":139,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Regina","funders":"Universiti Teknologi Malaysia","keywords":"Greenhouse gas; Agriculture; Materials science; Carbon fibers; Waste management; Natural resource economics; Environmental engineering; Environmental science; Engineering; Composite material; Economics; Ecology","retraction":null,"screen_n_in":null,"score":{"opus":0.03302663878493424,"gpt":0.2750643573437598,"spread":0.2420377185588256,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001284042,0.0005256336,0.001496734,0.0002140411,0.00003761041,0.00002650307,0.0002390233,0.0002503142,0.000003963685],"category_scores_gemma":[0.0000285046,0.0004005617,0.0002117576,0.0007735871,0.00004472823,0.00004303352,0.0001005581,0.0008263135,0.000008794957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000397688,"about_ca_system_score_gemma":0.0000310992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007566597,"about_ca_topic_score_gemma":0.00003677989,"domain_scores_codex":[0.998284,0.00008964702,0.0006479269,0.0003744374,0.0001816697,0.0004223592],"domain_scores_gemma":[0.999166,0.000131356,0.0001139029,0.0004008709,0.00002055207,0.000167281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001553668,0.00001474005,0.0000277386,0.2464757,0.0002116089,0.0003704732,0.000114428,0.0003310278,0.00006214528,0.00001124273,0.006947919,0.7454315],"study_design_scores_gemma":[0.0001707955,0.00001428339,0.00003713767,0.1720357,0.0003943965,0.00019767,0.00003521073,0.01432381,6.77471e-7,0.000002461344,0.8119211,0.0008668352],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003783453,0.9938186,5.270131e-7,0.0003012469,0.0003454665,0.0006870001,0.00002867649,0.0003212197,0.0007137822],"genre_scores_gemma":[0.0000291978,0.9991894,0.0000386537,0.0001784347,0.0001493703,0.0001018686,0.0001088543,0.0001154982,0.00008872864],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8049731,"threshold_uncertainty_score":0.9998446,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1567870876","doi":"10.1002/cjce.5450780217","title":"Coal combustion in O<sub>2</sub>/CO<sub>2</sub> mixtures compared with air","year":2000,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":136,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true},"ca_institutions":"Natural Resources Canada","funders":"Natural Resources Canada; Canadian Electricity Association","keywords":"Flue gas; Coal; Combustion; Bituminous coal; Coal combustion products; Environmental science; Limiting oxygen concentration; Chemistry; Waste management; Oxygen; Environmental chemistry; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.005574704362334618,"gpt":0.176005436813257,"spread":0.1704307324509224,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001971614,0.0002109324,0.0002744819,0.0001774488,0.00006629346,0.00004216504,0.0002703673,0.0001174012,0.0000337089],"category_scores_gemma":[0.00001789246,0.0001651595,0.00006848148,0.0002755674,0.00005663635,0.0001612818,0.000004946666,0.0007640027,0.00001666055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002638034,"about_ca_system_score_gemma":0.0001493401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001145798,"about_ca_topic_score_gemma":0.0003716012,"domain_scores_codex":[0.9988935,0.00001266151,0.0003559016,0.0000959171,0.0001988368,0.0004432121],"domain_scores_gemma":[0.9992326,0.00005437078,0.00004313654,0.000162565,0.00004348635,0.0004638465],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002171177,0.000005150738,0.0001403211,0.00003231662,0.00002575006,0.00005535328,0.000174527,0.606851,0.3889142,0.000005436169,0.001042897,0.002731327],"study_design_scores_gemma":[0.0006165411,0.00003044187,0.001415568,0.0003536734,0.00001957368,0.0003441474,0.00001031494,0.1137879,0.8816624,0.00001360409,0.001479342,0.0002664968],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986415,0.0004958152,0.0002042952,0.0001827151,0.0001219481,0.00007848599,0.00001079959,0.00004151532,0.0002229334],"genre_scores_gemma":[0.9995101,0.00004630079,0.0001092599,0.00005594171,0.0002202731,0.000003874459,0.000007309355,0.00004376736,0.000003153529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4930631,"threshold_uncertainty_score":0.6735009,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2144490447","doi":"10.1016/j.atmosenv.2008.01.049","title":"Greenhouse gas emissions from heavy-duty vehicles","year":2008,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":126,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Diesel fuel; Greenhouse gas; Ultra-low-sulfur diesel; Diesel particulate filter; Compressed natural gas; Environmental science; Waste management; Biodiesel; Biofuel; Environmental engineering; Engineering; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.009466647555344673,"gpt":0.1784333457790246,"spread":0.1689666982236799,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003797228,0.000206162,0.0001779172,0.000002449546,0.000204871,0.000009157226,0.0001719502,0.00009538555,0.00185327],"category_scores_gemma":[0.000003226623,0.0001877688,0.00006997873,0.0000829553,0.00006980437,0.0001086658,0.00005995086,0.000193831,0.0006442626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001023599,"about_ca_system_score_gemma":0.00001066393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000911619,"about_ca_topic_score_gemma":0.00000233625,"domain_scores_codex":[0.9990058,0.00001510341,0.0002259921,0.0002251255,0.0002163914,0.0003115994],"domain_scores_gemma":[0.9992924,0.00003520566,0.00002587867,0.0004275212,0.000002574236,0.0002163753],"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":[0.00006951315,0.0006301994,0.2036763,0.00006086436,0.0002672586,0.0003012878,0.003097659,0.5167845,0.03759625,0.00003669316,0.07987831,0.1576012],"study_design_scores_gemma":[0.0008304982,0.0001204699,0.1498057,0.00005842291,0.00003381718,0.00004200665,0.0001133799,0.2226293,0.008128857,0.0001288086,0.6173357,0.0007730395],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992923,0.001739359,0.002704964,0.0001084352,0.000150569,0.0001028604,0.00001281566,0.0002854012,0.001972586],"genre_scores_gemma":[0.978109,0.006109353,0.01418135,0.0001002747,0.0001533029,0.00002764815,0.00001536644,0.00005709786,0.0012466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5374573,"threshold_uncertainty_score":0.9990592,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1978662634","doi":"10.1016/j.trd.2014.11.010","title":"Development of simulated driving cycles for light, medium, and heavy duty trucks: Case of the Toronto Waterfront Area","year":2014,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Truck; Driving cycle; Automotive engineering; Acceleration; Range (aeronautics); Duty cycle; Heavy duty; Driving simulator; Schedule; Dynamometer; Environmental science; Simulation; Traffic simulation; Transport engineering; Engineering; Computer science; Microsimulation; Voltage","retraction":null,"screen_n_in":null,"score":{"opus":0.02536820724684131,"gpt":0.2619109305279488,"spread":0.2365427232811075,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004667608,0.0001246016,0.0001942435,0.00003101409,0.0001673602,0.000004386886,0.00007176929,0.00006807892,0.00007501391],"category_scores_gemma":[0.000001839943,0.00009021998,0.00004089932,0.00004006606,0.000100284,0.00009499669,0.000003534481,0.00009429664,3.193968e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002977746,"about_ca_system_score_gemma":0.00001526697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009213343,"about_ca_topic_score_gemma":0.002126495,"domain_scores_codex":[0.9989328,0.00001736874,0.0004109752,0.0001667991,0.0002401812,0.0002319171],"domain_scores_gemma":[0.9996214,0.0000527263,0.00003432242,0.0001585314,0.00002046173,0.0001125621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007672817,0.0006441879,0.4946622,0.005212817,0.0005801476,0.00004731241,0.08086924,0.1567043,0.1521966,0.0006640176,0.0001926634,0.1074592],"study_design_scores_gemma":[0.001885855,0.0002035564,0.718483,0.0003842698,0.00008187415,0.000007350878,0.00148722,0.03921152,0.1767153,0.0001211635,0.06101833,0.0004005498],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970373,0.0002527099,0.00212522,0.00006500843,0.00003666738,0.0003640432,0.00003126709,0.00001644287,0.00007132158],"genre_scores_gemma":[0.9980679,0.0005703227,0.001212311,0.000002666781,0.00001522705,0.00004093634,0.00003441683,0.00001755579,0.00003863861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2238208,"threshold_uncertainty_score":0.3679064,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2051946970","doi":"10.4271/2012-01-1727","title":"Evaluation of a Gasoline Particulate Filter to Reduce Particle Emissions from a Gasoline Direct Injection Vehicle","year":2012,"lang":"en","type":"article","venue":"SAE international journal of fuels and lubricants","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":116,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada","funders":"Government of Canada","keywords":"Gasoline; Gasoline direct injection; Particulates; Environmental science; Diesel particulate filter; Particle (ecology); Automotive engineering; Waste management; Environmental engineering; Chemistry; Engineering; Geology","retraction":null,"screen_n_in":null,"score":{"opus":0.03371190004815333,"gpt":0.3071856626082284,"spread":0.2734737625600751,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006727319,0.00008516981,0.0001524449,0.00008263647,0.00003012816,0.00001976815,0.0001032057,0.00003428353,0.0002264515],"category_scores_gemma":[0.0001341519,0.00006915035,0.00004991559,0.0001229719,0.000015903,0.0002792444,0.00002975385,0.0001018029,0.000006454656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006723179,"about_ca_system_score_gemma":0.00003357481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003646209,"about_ca_topic_score_gemma":0.000009543502,"domain_scores_codex":[0.9988301,0.000049235,0.0003753788,0.00006724696,0.0005241804,0.0001538249],"domain_scores_gemma":[0.9991196,0.00005366195,0.0001186038,0.00007806918,0.0004350963,0.0001949896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002144488,0.0002702941,0.07410811,0.00001512586,0.0004065027,0.000005879021,0.002368891,0.04255306,0.6214736,0.00001911738,0.002465121,0.2560999],"study_design_scores_gemma":[0.001943827,0.0001988702,0.589744,0.0004393652,0.0002133137,0.0001464851,0.0002411787,0.1721596,0.2295295,0.0002676662,0.004875451,0.0002407725],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997333,0.0009625389,0.0002762036,0.0002840269,0.0006511553,0.00006224588,0.00002709868,0.00001178671,0.0003918917],"genre_scores_gemma":[0.9987223,0.0001991334,0.0005323941,0.00004650465,0.0004537288,0.000002924296,0.000003242506,0.00001070186,0.00002908513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5156359,"threshold_uncertainty_score":0.281987,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1589221021","doi":"10.4271/2004-01-2616","title":"The Predictive Cruise Control – A System to Reduce Fuel Consumption of Heavy Duty Trucks","year":2004,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":116,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Truck; Heavy duty; Cruise control; Automotive engineering; Fuel efficiency; Cruise; Model predictive control; Consumption (sociology); Computer science; Control (management); Environmental science; Engineering; Aerospace engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.008934247094477621,"gpt":0.2329186413269594,"spread":0.2239843942324818,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000638735,0.0005775957,0.000776135,0.0001429258,0.0004149516,0.00007380625,0.0008321073,0.0005794151,0.00006731377],"category_scores_gemma":[0.0003106994,0.0004227799,0.0003263081,0.0005783205,0.0006475807,0.0002914221,0.0001585788,0.0009886863,0.0001027143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005293743,"about_ca_system_score_gemma":0.00009465114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002922813,"about_ca_topic_score_gemma":0.007238698,"domain_scores_codex":[0.9966992,0.00008992266,0.001070421,0.0006337929,0.0007075873,0.0007991121],"domain_scores_gemma":[0.9976577,0.0003947049,0.0001515923,0.001215904,0.0001353363,0.0004448018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008852909,0.0001284083,0.0001281578,0.0002335188,0.00007526316,0.00001783194,0.00007042719,0.004281004,0.981459,0.008243991,0.001099805,0.00337728],"study_design_scores_gemma":[0.001706058,0.001318074,0.9731166,0.0009381426,0.00009527517,0.0001288336,0.0001950551,0.000005820749,0.001371315,0.0005168027,0.02001482,0.000593258],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9647859,0.001544125,0.00003014426,0.002564796,0.0006116908,0.002127207,0.0002179896,0.003693488,0.02442469],"genre_scores_gemma":[0.9971508,0.0006617248,0.001001119,0.0003013167,0.000155631,0.0005173571,0.0000111303,0.0001015518,0.00009937306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9800877,"threshold_uncertainty_score":0.9998224,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2978036655","doi":"10.1016/j.trd.2019.09.020","title":"Simulating impacts of automated driving behavior and traffic conditions on vehicle emissions","year":2019,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":115,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Greenhouse gas; Microsimulation; Traffic flow (computer networking); Transport engineering; Traffic congestion; Electrification; Computer science; Automotive engineering; Environmental science; Engineering; Computer security","retraction":null,"screen_n_in":null,"score":{"opus":0.02302816725912848,"gpt":0.2955877370933237,"spread":0.2725595698341952,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002148854,0.0001349094,0.0001766753,0.0001165743,0.0001453636,0.000009004631,0.00005296959,0.00008337747,0.0004673546],"category_scores_gemma":[0.000001591529,0.0001269978,0.00003691947,0.0001208821,0.00009597133,0.0001306198,0.000002003164,0.000242993,0.00001602408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002243422,"about_ca_system_score_gemma":0.00001271755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001720709,"about_ca_topic_score_gemma":0.00002459169,"domain_scores_codex":[0.9988607,0.00001814911,0.000304216,0.0002019489,0.0003258029,0.0002892187],"domain_scores_gemma":[0.9995189,0.00008262508,0.00002542273,0.0001537286,0.00001394196,0.000205324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003317831,0.0001678511,0.5642095,0.0003254566,0.00004000708,0.00001715895,0.001872723,0.3643308,0.06560469,0.00009016248,0.00007587295,0.003232689],"study_design_scores_gemma":[0.0005864287,0.0001414727,0.9261318,0.0001751309,0.00002184929,6.95246e-7,0.0002134923,0.06883892,0.002584807,0.000006613146,0.001153864,0.0001449249],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990321,0.0001032997,0.00001344271,0.00004429648,0.0000313363,0.0003738228,0.00008149173,0.0001307941,0.0001894344],"genre_scores_gemma":[0.9988838,0.0007356267,0.00008433708,0.000005103358,0.00001207818,0.00004196268,0.0001346564,0.00002506347,0.0000773229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3619224,"threshold_uncertainty_score":0.5178822,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3166052246","doi":"10.1080/15567036.2021.1924313","title":"A comprehensive study on the effects of multiple injection strategies and exhaust gas recirculation on diesel engine characteristics that utilize waste high density polyethylene oil","year":2021,"lang":"en","type":"article","venue":"Energy Sources Part A Recovery Utilization and Environmental Effects","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":114,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Diesel fuel; Diesel engine; NOx; Exhaust gas; Materials science; Exhaust gas recirculation; Smoke; Waste management; Pulp and paper industry; Chemistry; Automotive engineering; Combustion; Organic chemistry; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01332890575933382,"gpt":0.1937741432885168,"spread":0.180445237529183,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005671951,0.000217215,0.0002331824,0.00005836033,0.0001860584,0.00005436533,0.00003816041,0.00008606852,0.00001282091],"category_scores_gemma":[0.00003141112,0.0001781709,0.00003618126,0.0001004202,0.00006074106,0.0001544845,0.0000447989,0.0001201215,0.000001390555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004379156,"about_ca_system_score_gemma":0.000005546643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002763751,"about_ca_topic_score_gemma":0.00001408751,"domain_scores_codex":[0.9991166,0.0001393409,0.0001734454,0.000235776,0.0001839738,0.0001508902],"domain_scores_gemma":[0.9991996,0.0004699001,0.00007021688,0.0001894507,0.000008635539,0.00006214937],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006026027,0.001190311,0.06921915,0.001612673,0.0005586037,0.00006327028,0.004769374,0.1647465,0.4003032,0.0002889124,0.0001340968,0.3565113],"study_design_scores_gemma":[0.001696349,0.001161079,0.4733257,0.0004958537,0.00009439598,0.00002140779,0.00387248,0.1456959,0.3719024,0.00003545951,0.001264181,0.0004348327],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982249,0.0007025022,0.0004687567,0.00001109724,0.0003552542,0.0001301381,0.00001149277,0.00004451974,0.00005131527],"genre_scores_gemma":[0.9963897,0.003232585,0.000009247799,0.00005945799,0.00006382843,0.00003111568,0.0001001068,0.00002561199,0.00008827322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4041065,"threshold_uncertainty_score":0.7265599,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2994253361","doi":"10.5194/acp-20-5231-2020","title":"Nitrous acid (HONO) emissions under real-world driving conditions from vehicles in a UK road tunnel","year":2020,"lang":"en","type":"article","venue":"Atmospheric chemistry and physics","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":113,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"York University","funders":"Natural Environment Research Council; Sight Research UK","keywords":"NOx; Nitrous acid; Environmental science; Diesel fuel; Meteorology; Nitrous oxide; Atmospheric sciences; Truck; Particulates; Nitrogen oxides; Environmental engineering; Automotive engineering; Chemistry; Waste management; Engineering; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01029685024489066,"gpt":0.2187475879282273,"spread":0.2084507376833366,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002205066,0.000192548,0.0002086715,3.495563e-7,0.0001144718,0.00003691166,0.0001174512,0.00008134537,0.0005203232],"category_scores_gemma":[0.000006463608,0.0002008842,0.00004834596,0.0003154608,0.00004367434,0.0001105209,0.00003991194,0.0003070884,0.00001870762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004029549,"about_ca_system_score_gemma":0.00002806573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001946849,"about_ca_topic_score_gemma":0.00002108217,"domain_scores_codex":[0.9992474,0.000007835577,0.0001985777,0.000225475,0.00009085665,0.0002298907],"domain_scores_gemma":[0.9995329,0.00004093772,0.00002883043,0.0001773936,0.0000114287,0.0002084611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002289687,0.00009301348,0.0381101,0.0002045642,0.0001104139,0.00002791002,0.001758192,0.06295955,0.8186046,0.00007953051,0.003491908,0.07453725],"study_design_scores_gemma":[0.0008495017,0.00001581801,0.0779573,0.0002290391,0.00004273735,0.000003745337,0.0005083979,0.8572257,0.0574213,0.001552611,0.003539248,0.0006545584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924726,0.0002337087,0.0009079551,0.0001560528,0.0000333924,0.00005491815,0.00003183712,0.0001525371,0.005956951],"genre_scores_gemma":[0.9965798,0.0003131068,0.002186487,0.0001179452,0.0003041742,0.00001634379,0.00007245618,0.00002966291,0.000379969],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7942662,"threshold_uncertainty_score":0.8191819,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1992282476","doi":"10.1080/00423114.2011.637566","title":"Models for road surface roughness","year":2011,"lang":"en","type":"article","venue":"Vehicle System Dynamics","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":102,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Stiftelsen för Strategisk Forskning; Centre de Recherches Mathématiques","keywords":"Laplace transform; Gaussian process; Gaussian; Surface roughness; Surface (topology); Road surface; Process (computing); Engineering; Surface finish; Laplace's equation; Gaussian surface; Statistical model; Structural engineering; Mathematics; Mathematical analysis; Computer science; Mechanical engineering; Statistics; Geometry; Physics; Civil engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.02132657958606078,"gpt":0.2094966325347346,"spread":0.1881700529486738,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000177183,0.000170711,0.0002077708,0.00003807139,0.000107057,0.00002404308,0.0002165676,0.0001294168,0.00001054526],"category_scores_gemma":[0.000002314936,0.0001631924,0.00007571271,0.0001558668,0.00001610403,0.000252368,0.00002590734,0.0001036572,0.00003751199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001630043,"about_ca_system_score_gemma":0.00001668247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009081746,"about_ca_topic_score_gemma":0.00003380412,"domain_scores_codex":[0.9990985,0.00001306822,0.0002667148,0.0001743182,0.0001130515,0.0003343351],"domain_scores_gemma":[0.9994521,0.00001833599,0.00003563599,0.0003239589,0.0000642287,0.0001057953],"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":[0.00006045854,0.00006143517,0.003006753,0.001839924,0.0001096404,0.00001078659,0.00167765,0.9365029,0.001443245,0.03124994,0.0005717871,0.02346545],"study_design_scores_gemma":[0.000288265,0.00002705304,0.0005910739,0.00008977018,0.00001215341,0.000008427639,0.0003203571,0.9975673,0.0004493936,0.000160706,0.0002617491,0.000223753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8166441,0.0002195932,0.1608535,0.000008845037,0.0006533961,0.000352927,0.00008798929,0.0007127913,0.02046686],"genre_scores_gemma":[0.9954355,0.00002006686,0.003944424,0.000006686027,0.00006842366,0.00003671348,0.00001741341,0.00006395461,0.0004068001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1787914,"threshold_uncertainty_score":0.6654794,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2138868522","doi":"10.1287/trsc.2013.0477","title":"Hours of Service Regulations in Road Freight Transport: An Optimization-Based International Assessment","year":2013,"lang":"en","type":"article","venue":"Transportation Science","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":100,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Université de Montréal","funders":"","keywords":"Transport engineering; European union; Truck; Service (business); Engineering; Business; Operations research; Risk analysis (engineering); International trade; Marketing; Automotive engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01241733130484501,"gpt":0.2614500720696989,"spread":0.2490327407648539,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001811361,0.00008193625,0.00008859259,0.0002404048,0.00005543323,0.00002038042,0.000259822,0.00003523692,0.0006021512],"category_scores_gemma":[0.000002184774,0.00008160384,0.00001986128,0.0009169917,0.00006342983,0.001024446,8.634771e-7,0.00007436775,0.000003923046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004471634,"about_ca_system_score_gemma":0.0001183532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003125808,"about_ca_topic_score_gemma":0.0003136103,"domain_scores_codex":[0.999042,0.000006008645,0.0003122061,0.0001547713,0.0003435281,0.0001414782],"domain_scores_gemma":[0.9994853,0.00001182513,0.00004535838,0.0001614706,0.0002130839,0.00008292986],"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":[0.000001514609,0.00003126692,0.05647891,0.00001272158,0.000001457682,3.482158e-7,0.0005075657,0.9363115,0.005375164,0.0001460142,0.000003648819,0.001129825],"study_design_scores_gemma":[0.0001482748,0.000006125201,0.4662707,0.00001804682,0.000001737645,9.220955e-8,0.000070509,0.5321886,0.001217089,0.00001455192,0.00001031793,0.00005399471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9508173,0.000005863686,0.04678472,0.0002494193,0.0001430467,0.0001589944,0.00002878471,0.00006695169,0.001744876],"genre_scores_gemma":[0.9806404,0.00000793353,0.01910345,0.00006245494,0.00001154176,0.00002986338,0.0001255257,0.000008951457,0.000009922995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4097917,"threshold_uncertainty_score":0.6593133,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2313063547","doi":"10.1021/es501791b","title":"Black Carbon Emissions in Gasoline Exhaust and a Reduction Alternative with a Gasoline Particulate Filter","year":2014,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":98,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada","funders":"Government of Canada","keywords":"Gasoline; Particulates; Gasoline direct injection; Driving cycle; Environmental science; Particle number; Cold start (automotive); Carbon black; Waste management; Chemistry; Environmental engineering; Volume (thermodynamics); Engineering; Automotive engineering; Physics","retraction":null,"screen_n_in":null,"score":{"opus":0.004522211235940386,"gpt":0.1951694866324312,"spread":0.1906472753964908,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001329064,0.0001125514,0.0001075636,0.000230755,0.00007932711,0.00001122325,0.0001357436,0.00006428627,0.00003569025],"category_scores_gemma":[0.000008115077,0.00008906649,0.000007471484,0.0004267847,0.0007912853,0.000128336,0.00008179715,0.0001904111,0.000008180956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009971237,"about_ca_system_score_gemma":0.000006195241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001161072,"about_ca_topic_score_gemma":0.000007179643,"domain_scores_codex":[0.9992014,0.000006443167,0.0001243574,0.0002452942,0.0001260094,0.0002965599],"domain_scores_gemma":[0.9996976,0.000005607299,0.00002361412,0.0001887118,0.00000259222,0.00008186314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001960539,0.00008036316,0.05121081,0.00001189612,0.000006749082,0.0000119067,0.0007213144,0.06718194,0.8584722,0.0001312012,0.0000203637,0.02213163],"study_design_scores_gemma":[0.000660891,0.0002480957,0.03198817,0.00008482181,0.000008029491,0.0001558418,0.0004284035,0.7257628,0.2375474,0.0003291683,0.002493381,0.0002929649],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985631,0.00005033823,0.0003264236,0.0002796256,0.00004344161,0.0001026156,0.000001489664,0.00008455422,0.0005484297],"genre_scores_gemma":[0.9989069,0.0001320916,0.0008172375,0.00001130334,0.00002572517,0.00001662745,0.000001384155,0.0000103324,0.0000784261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6585809,"threshold_uncertainty_score":0.3632026,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3012893977","doi":"10.1155/2020/9263605","title":"Vehicle Fuel Consumption Prediction Method Based on Driving Behavior Data Collected from Smartphones","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":96,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Natural Science Foundation of Beijing Municipality; Beijing University of Technology; National Natural Science Foundation of China","keywords":"Fuel efficiency; Mobile phone; Automotive engineering; Consumption (sociology); Acceleration; Energy consumption; Idle; Simulation; Engineering; Computer science; Telecommunications","retraction":null,"screen_n_in":null,"score":{"opus":0.02735851094659277,"gpt":0.273474723839059,"spread":0.2461162128924662,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001134972,0.0001130586,0.0001790009,0.00007314647,0.00005279676,0.00001748637,0.0001446867,0.00006387312,0.00009828754],"category_scores_gemma":[0.00002328304,0.00010857,0.00004705742,0.0001994018,0.00000913958,0.0005578313,0.000001813554,0.0002478439,0.000004678467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003681924,"about_ca_system_score_gemma":0.00003096073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003201763,"about_ca_topic_score_gemma":0.00002642831,"domain_scores_codex":[0.9990549,0.00002538305,0.0004374951,0.0001341452,0.0002428867,0.0001051692],"domain_scores_gemma":[0.9994118,0.00008532513,0.0001499103,0.0001515963,0.00008311426,0.0001182367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002151276,0.00004867035,0.03443446,0.0000628601,0.00002732192,0.00001990721,0.0006602227,0.838598,0.10765,0.000001774876,0.0002391617,0.01804244],"study_design_scores_gemma":[0.001115723,0.0001333235,0.60637,0.0001114819,0.0000824693,0.000001346343,0.00006585448,0.3840847,0.006749626,0.000008589343,0.001185845,0.00009101866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9161107,0.0001363374,0.08279809,0.0001242543,0.0003967393,0.0001116735,0.0002243976,0.00008069747,0.0000171075],"genre_scores_gemma":[0.9654247,0.0002035434,0.03377764,0.00006072395,0.0001690473,0.000004613898,0.0003344037,0.00002268424,0.000002682839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5719355,"threshold_uncertainty_score":0.4427358,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2075508175","doi":"10.1109/tits.2013.2262175","title":"Optimization of Fuel Cost and Emissions Using V2V Communications","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":95,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"","keywords":"Fuel efficiency; Heuristic; Key (lock); Computer science; Vehicular communication systems; Engineering; Automotive engineering; Telecommunications; Artificial intelligence; Vehicular ad hoc network; Computer security; Wireless; Wireless ad hoc network","retraction":null,"screen_n_in":null,"score":{"opus":0.03783664197611921,"gpt":0.2612315346568426,"spread":0.2233948926807234,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008418855,0.0001556655,0.0001940377,0.0001865993,0.000146434,0.00003508302,0.0001386416,0.0001070566,0.000191282],"category_scores_gemma":[0.000001051197,0.0001528893,0.00006091196,0.000293119,0.00006479018,0.0002709155,2.949522e-7,0.0001739307,0.00001597515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005027664,"about_ca_system_score_gemma":0.00002264094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00023899,"about_ca_topic_score_gemma":0.00002795773,"domain_scores_codex":[0.9989855,0.00002965502,0.0005359491,0.0001359722,0.0001592737,0.0001536189],"domain_scores_gemma":[0.9992351,0.0000710464,0.00007102024,0.0003525147,0.0001425386,0.0001277876],"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":[0.000004328652,0.00005328696,0.0001417132,0.0001677235,0.00003719659,1.831663e-7,0.0007613428,0.9911665,0.003910246,0.00006410647,0.00003524222,0.003658139],"study_design_scores_gemma":[0.0001664226,0.00002975126,0.000265536,0.0002272497,0.00004295862,0.000004860774,0.0007709193,0.9893211,0.008181406,0.000007761506,0.0008126081,0.0001694455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07435466,0.0004200948,0.9236907,0.00002679799,0.0003951652,0.0005744698,0.00008955358,0.0001381139,0.0003104115],"genre_scores_gemma":[0.994419,0.00164786,0.003613827,0.000008483117,0.00001427747,0.0001333249,0.00002776195,0.00003214261,0.0001033564],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9200769,"threshold_uncertainty_score":0.6234643,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2790882261","doi":"10.1111/mice.12344","title":"Modeling Relationship between Truck Fuel Consumption and Driving Behavior Using Data from Internet of Vehicles","year":2018,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":93,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Toronto Metropolitan University","funders":"Ministry of Transport of the People's Republic of China; National Natural Science Foundation of China","keywords":"Truck; Fuel efficiency; Automotive engineering; Modal; Computer science; Energy consumption; The Internet; Index (typography); Consumption (sociology); Fuel cells; Regression analysis; Simulation; Transport engineering; Engineering; Machine learning","retraction":null,"screen_n_in":null,"score":{"opus":0.04064972787617242,"gpt":0.2522759280864324,"spread":0.21162620021026,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001058902,0.0002079847,0.0002545675,0.0001300827,0.00006493844,0.00006208002,0.0002063729,0.0001342192,0.0000203005],"category_scores_gemma":[0.00002004068,0.0002114837,0.00002050626,0.0001045809,0.00005181677,0.0004293131,0.0002417346,0.0002586007,0.000001177595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002476436,"about_ca_system_score_gemma":0.000009074917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002782694,"about_ca_topic_score_gemma":0.00001013493,"domain_scores_codex":[0.9990787,0.00001187424,0.0003385036,0.0002654071,0.0001048124,0.0002007087],"domain_scores_gemma":[0.9993929,0.0001032563,0.00004188369,0.0003200116,0.00003244609,0.0001094773],"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":[0.000004853503,0.000005170485,0.7108003,0.0002730365,0.00006477789,0.000002166683,0.0007533251,0.2630156,0.009017105,0.00008338432,0.00006930518,0.01591098],"study_design_scores_gemma":[0.0001658632,0.00001570349,0.3321159,0.0002082862,0.00003447977,0.000009538464,0.00000629554,0.6668561,0.0003094816,0.00007411464,0.00005606228,0.0001481737],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6748942,0.0004522535,0.3242632,0.000001830021,0.0002010939,0.00005870338,0.00002513703,0.00009514112,0.000008509365],"genre_scores_gemma":[0.9647777,0.00005895707,0.03458742,0.000004204286,0.0004751939,0.000001770009,0.00006029728,0.00003307397,0.000001385678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4038406,"threshold_uncertainty_score":0.8624056,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2059213224","doi":"10.4271/2013-01-0527","title":"Impact of Ambient Temperature on Gaseous and Particle Emissions from a Direct Injection Gasoline Vehicle and its Implications on Particle Filtration","year":2013,"lang":"en","type":"article","venue":"SAE international journal of fuels and lubricants","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada","funders":"Government of Canada","keywords":"Gasoline; Gasoline direct injection; Particle (ecology); Environmental science; Filtration (mathematics); Waste management; Automotive engineering; Particulates; Environmental engineering; Chemistry; Engineering; Organic chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.01222975674117941,"gpt":0.2648042136887579,"spread":0.2525744569475785,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006779035,0.00008647986,0.0001227526,0.00005242493,0.0000543929,0.00005052217,0.00005667592,0.00003742738,0.00006928818],"category_scores_gemma":[0.00004174797,0.00006354859,0.00003528064,0.00007464088,0.00001726276,0.0002072003,0.00001446452,0.000123109,0.000002295428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003486656,"about_ca_system_score_gemma":0.0000168175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006198836,"about_ca_topic_score_gemma":0.00000759903,"domain_scores_codex":[0.9994143,0.00001813355,0.0002403636,0.00008716023,0.0001434765,0.00009662695],"domain_scores_gemma":[0.9994834,0.0000826615,0.00009006381,0.00005940892,0.0001480599,0.0001364181],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001078049,0.0001510331,0.06523572,0.000009252455,0.0001309327,0.000003630727,0.0004413578,0.004267218,0.8963415,0.00006853569,0.0007235298,0.03251947],"study_design_scores_gemma":[0.0005734427,0.0004318611,0.9407403,0.0001341106,0.00001379857,0.00004748114,0.00005508767,0.0224605,0.03521524,0.0001603218,0.00008862755,0.00007926513],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987696,0.000425928,0.00001029838,0.0004655831,0.0001032174,0.00006941958,0.00005717421,0.00001089456,0.00008785639],"genre_scores_gemma":[0.9988871,0.0008855349,0.00004133178,0.00004552109,0.000100485,0.000003309149,0.000003995904,0.000008016352,0.00002470244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8755046,"threshold_uncertainty_score":0.2591437,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2060668501","doi":"10.1016/j.trd.2006.01.001","title":"Investigating the sustainability of lignocellulose-derived fuels for light-duty vehicles","year":2006,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":88,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Gasoline; Greenhouse gas; Environmental science; Life-cycle assessment; Biofuel; Sustainability; Raw material; Fischer–Tropsch process; Fossil fuel; Propulsion; Waste management; Production (economics); Engineering; Chemistry; Economics","retraction":null,"screen_n_in":null,"score":{"opus":0.02639994260794951,"gpt":0.2615539268461178,"spread":0.2351539842381683,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006347281,0.0001375053,0.0001697902,0.00005247314,0.0002485538,0.00001059036,0.000113747,0.00007722552,0.00005181026],"category_scores_gemma":[0.00000351051,0.0001062025,0.00006838037,0.0001256309,0.0002561821,0.0001068463,0.00000227363,0.0001952145,0.000001784677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000385126,"about_ca_system_score_gemma":0.00002814099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001432468,"about_ca_topic_score_gemma":0.000129224,"domain_scores_codex":[0.9986836,0.0000264611,0.0004060313,0.0002025568,0.0003376296,0.0003437093],"domain_scores_gemma":[0.9995202,0.0001042311,0.00003352829,0.0001989484,0.00005074789,0.00009233142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001667732,0.0005169829,0.5375283,0.004194269,0.0001553413,0.0000139053,0.007985966,0.1793132,0.2409289,0.005022142,0.00205231,0.02212191],"study_design_scores_gemma":[0.0009437503,0.0001168242,0.849113,0.00007214428,0.00004195283,4.296865e-7,0.0008862718,0.006354791,0.09315928,0.004818731,0.0442273,0.0002655589],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959746,0.0005480705,0.001841212,0.000659319,0.00002686767,0.0006401328,0.0000678009,0.00004721749,0.0001947691],"genre_scores_gemma":[0.9986454,0.0004644575,0.0003681347,0.000007076783,0.00005936245,0.000190219,0.0001025877,0.00002399956,0.0001387359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3115847,"threshold_uncertainty_score":0.4330814,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W574499664","doi":"","title":"Comparison of Passenger Vehicle Fuel Economy and Greenhouse Gas Emission Standards Around the World","year":2004,"lang":"en","type":"article","venue":"","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Greenhouse gas; European union; Truck; Economy; International trade; Environmental science; Natural resource economics; Economics; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01570094371605268,"gpt":0.2689646914630746,"spread":0.2532637477470219,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001431566,0.0001002572,0.0001493629,0.00004297879,0.00007476586,0.00002956469,0.00008790706,0.00003751659,0.0001302679],"category_scores_gemma":[0.000005579904,0.00006550959,0.00002759143,0.0001202718,0.00004326073,0.0001242998,0.00002890993,0.0001434196,0.000005121744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004771661,"about_ca_system_score_gemma":0.00002462966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003352204,"about_ca_topic_score_gemma":0.0001546546,"domain_scores_codex":[0.9994478,0.000007133856,0.0002005643,0.00009151577,0.0001044592,0.0001484824],"domain_scores_gemma":[0.9996362,0.00004290215,0.00002635881,0.0001872204,0.00003289287,0.00007439599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002779448,0.0006558428,0.3856492,0.002216591,0.0003835093,0.00001718173,0.01083666,0.3110588,0.05625639,0.00958589,0.05916318,0.1638988],"study_design_scores_gemma":[0.003283309,0.0002796231,0.03332149,0.0004448001,0.00005897948,0.00001900558,0.001953681,0.3287939,0.2050029,0.004000219,0.4220073,0.0008348327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971018,0.0006435412,0.0005403299,0.0004005241,0.00006088099,0.00008783521,0.000006136647,0.00009432396,0.02714843],"genre_scores_gemma":[0.998988,0.0001182846,0.0003798687,0.00003283649,0.00005704242,0.000004100651,0.000001021298,0.00001589855,0.000402888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3628441,"threshold_uncertainty_score":0.2671404,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2104449353","doi":"10.1109/tvt.2010.2061243","title":"Statistical Development of a Duty Cycle for Plug-in Vehicles in a North American Urban Setting Using Fleet Information","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Manitoba","funders":"Manitoba Hydro","keywords":"Driving cycle; Duty cycle; Plug-in; Transport engineering; Automotive engineering; Statistical analysis; Engineering; Operations research; Simulation; Power (physics); Computer science; Electric vehicle; Electrical engineering; Voltage; Statistics","retraction":null,"screen_n_in":null,"score":{"opus":0.006106146595711878,"gpt":0.2268478563685591,"spread":0.2207417097728472,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001328409,0.0001298579,0.0002069045,0.0005943314,0.00007518474,0.000008406189,0.0001190224,0.0001139615,0.000006308977],"category_scores_gemma":[0.00001047988,0.0001372585,0.00002946909,0.0006964252,0.00008559439,0.0001494228,0.00000178311,0.0004538269,0.000003716414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007952427,"about_ca_system_score_gemma":0.0000579424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004096772,"about_ca_topic_score_gemma":0.001942424,"domain_scores_codex":[0.9990917,0.000008477507,0.0004165173,0.0001196477,0.00009566404,0.0002679731],"domain_scores_gemma":[0.9996545,0.00004594643,0.00005406069,0.000170608,0.00003639322,0.00003851807],"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":[0.00005809436,0.0001630895,0.02078718,0.0002055621,0.00004015381,0.000005289778,0.001016537,0.508442,0.04128928,0.0001529747,0.000009562549,0.4278302],"study_design_scores_gemma":[0.0007408346,0.00006137991,0.02161474,0.00005667735,0.00001092251,0.00001225134,0.0002244431,0.8644789,0.1114289,0.0000417886,0.001080545,0.000248589],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.708168,0.000004909592,0.2914141,0.00002965604,0.00007523279,0.0001741019,0.00002817592,0.00009703417,0.000008789538],"genre_scores_gemma":[0.941644,0.000005743865,0.05822826,0.00001026844,0.000006454005,0.00008156874,0.000007276439,0.0000155039,9.3796e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4275816,"threshold_uncertainty_score":0.5597239,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2999881469","doi":"10.1016/j.apenergy.2019.114471","title":"Energy oriented driving behavior analysis and personalized prediction of vehicle states with joint time series modeling","year":2020,"lang":"en","type":"article","venue":"Applied Energy","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Waterloo","funders":"Nanyang Technological University","keywords":"Energy consumption; Headway; Acceleration; Energy (signal processing); Computer science; Simulation; Efficient energy use; Automotive engineering; Energy management; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.006995649746421736,"gpt":0.1725407218759127,"spread":0.165545072129491,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003086475,0.0001293445,0.0002322121,0.00007914002,0.00006018294,0.00001439499,0.00004428202,0.0000492057,0.00007317451],"category_scores_gemma":[0.00000106514,0.0001134609,0.00003624006,0.0004268512,0.00003304925,0.00009628048,0.00002599366,0.00005572059,6.773619e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001509787,"about_ca_system_score_gemma":0.000009002699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009472719,"about_ca_topic_score_gemma":0.00001707351,"domain_scores_codex":[0.9993523,0.000006471824,0.0001929955,0.000166917,0.0001332395,0.0001480821],"domain_scores_gemma":[0.9997204,0.000008082588,0.00003272033,0.0001032904,0.00003081651,0.0001046863],"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":[0.00006766285,0.0000249738,0.001753952,0.00004190498,0.0003383188,0.000002924328,0.0008680804,0.8245133,0.1652114,0.001262702,0.0000673032,0.005847434],"study_design_scores_gemma":[0.0002985339,0.00005434552,0.0005360111,0.00001205903,0.000186392,0.000001406211,0.0001555877,0.969303,0.02828655,0.00001397066,0.001032536,0.0001196842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.881753,0.0001369847,0.1173902,0.00002505963,0.00001108346,0.00002794396,0.00001902623,0.0001598495,0.0004768827],"genre_scores_gemma":[0.9980078,0.0002604299,0.001474923,0.00002531056,0.00003513777,0.0000338784,0.00008065,0.00002506413,0.00005674727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1447896,"threshold_uncertainty_score":0.4626801,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2565163371","doi":"10.1080/02786826.2016.1274368","title":"Raman spectroscopy and TEM characterization of solid particulate matter emitted from soot generators and aircraft turbine engines","year":2016,"lang":"en","type":"article","venue":"Aerosol Science and Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"Transport Canada","keywords":"Soot; Diesel exhaust; Materials science; Particulates; Raman spectroscopy; Combustion; Particle (ecology); Analytical Chemistry (journal); Chemistry; Optics; Environmental chemistry; Organic chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.004358458788957597,"gpt":0.201499972466844,"spread":0.1971415136778864,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007213457,0.00008736144,0.0001227832,0.0001092595,0.0000804919,0.00001655959,0.00007759238,0.00007729819,0.00001972947],"category_scores_gemma":[0.00001189532,0.00005895474,0.000004891024,0.0002942451,0.0003803437,0.0002031682,0.00005858785,0.00005145471,0.000003831302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008808056,"about_ca_system_score_gemma":0.00001031955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004524955,"about_ca_topic_score_gemma":0.000002449354,"domain_scores_codex":[0.9994358,0.000002839429,0.0001244642,0.0001776989,0.00007091538,0.0001882496],"domain_scores_gemma":[0.9997424,0.000009560572,0.00002592345,0.000132487,0.00003716917,0.0000523924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001357288,0.000003180776,0.04645389,0.000007449243,0.000003317514,6.010987e-7,0.00003688161,0.000001435314,0.9480261,0.00002813167,0.0000212507,0.005416363],"study_design_scores_gemma":[0.0001870156,0.00003324499,0.04326907,0.00003941882,0.000004931338,0.000008762181,0.00001016975,0.005495496,0.9506374,0.00009865315,0.0001234521,0.00009241546],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981743,0.0001194164,0.0005720882,0.0008984151,0.00006382109,0.00005996631,0.00001275774,0.00008757794,0.00001167316],"genre_scores_gemma":[0.9990947,0.0003775871,0.0004432829,0.00003036453,0.00002156086,0.000006397809,0.000001304161,0.000006997614,0.00001785871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00549406,"threshold_uncertainty_score":0.2404105,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2417212667","doi":"10.1021/acs.est.5b01655","title":"Life Cycle Assessment of Vehicle Lightweighting: Novel Mathematical Methods to Estimate Use-Phase Fuel Consumption","year":2015,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Ford Motor Company; Canada Excellence Research Chairs, Government of Canada; U.S. Department of Energy","keywords":"Fuel efficiency; Automotive engineering; Powertrain; Life-cycle assessment; Greenhouse gas; Driving cycle; Consumption (sociology); Environmental science; Dynamometer; Axle; Phase (matter); Computer science; Production (economics); Engineering; Mechanical engineering; Electric vehicle; Chemistry; Power (physics)","retraction":null,"screen_n_in":null,"score":{"opus":0.03450787640178311,"gpt":0.3609973091457265,"spread":0.3264894327439434,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000551706,0.0001293709,0.0001862184,0.0002740606,0.00008821095,0.00002412599,0.000346509,0.0000987034,0.00009811666],"category_scores_gemma":[0.0001083326,0.0001158474,0.00002357616,0.0004737163,0.000485979,0.0002788711,0.0002178655,0.0001651792,0.00007906139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001847935,"about_ca_system_score_gemma":0.0000424319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001578582,"about_ca_topic_score_gemma":3.69648e-7,"domain_scores_codex":[0.9988705,0.00001058087,0.0002697099,0.0002410352,0.0002794089,0.0003287481],"domain_scores_gemma":[0.9992446,0.00003224769,0.00004718228,0.0003373096,0.000008709503,0.0003300073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004115786,0.0002070575,0.00639366,0.00002029428,0.000007312795,0.000001917804,0.0001729752,0.02070722,0.9573764,0.001855159,0.00004812198,0.01320572],"study_design_scores_gemma":[0.0006875404,0.0002370757,0.009984016,0.0000390236,0.0000147773,0.00002864867,0.0001483768,0.7501954,0.2330966,0.0007178512,0.004604937,0.0002456712],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8947306,0.0000629396,0.1040503,0.0002108756,0.0001010497,0.0001492823,0.000008059037,0.0001809159,0.0005059717],"genre_scores_gemma":[0.7860854,0.00000990506,0.2138133,0.00002869842,0.000008315325,0.00001860922,0.000001240835,0.00001176451,0.00002283606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7294882,"threshold_uncertainty_score":0.4724119,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2141573669","doi":"10.1093/annhyg/men053","title":"Characterization and Kinetics Study of Off-Gas Emissions from Stored Wood Pellets","year":2008,"lang":"en","type":"article","venue":"The Annals of Occupational Hygiene","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Pellets; Biomass (ecology); Kinetics; Chemistry; Gas composition; Materials science; Environmental science; Waste management; Environmental chemistry; Analytical Chemistry (journal); Composite material; Thermodynamics","retraction":null,"screen_n_in":null,"score":{"opus":0.0702744874248256,"gpt":0.3013088161398796,"spread":0.231034328715054,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007232744,0.00008333592,0.0001350422,0.00005402448,0.00006632088,0.000003633443,0.0001109606,0.00003359034,0.00006753279],"category_scores_gemma":[0.00002391973,0.00006246574,0.00002285236,0.0001388831,0.00004289205,0.00007995007,0.00003267965,0.00006193716,0.000002503478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003542157,"about_ca_system_score_gemma":0.00001565349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002229579,"about_ca_topic_score_gemma":0.000003378385,"domain_scores_codex":[0.9993781,0.00002174823,0.0002399167,0.00008017676,0.0001932371,0.00008679707],"domain_scores_gemma":[0.9995232,0.00006429272,0.00007400909,0.0001853793,0.0001090695,0.00004410437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005840501,0.00160562,0.1548318,0.0001011895,0.0003139041,0.00000743848,0.01763589,0.03250942,0.7161102,0.0001129619,0.003081372,0.07310626],"study_design_scores_gemma":[0.0003829829,0.0001647385,0.9268169,0.00003715279,0.00001269142,0.000002986665,0.0001456233,0.03257038,0.03816126,0.00002561266,0.001583841,0.00009587028],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990473,0.0002276635,0.0002119259,0.0001033234,0.00005663745,0.000118898,0.00009232775,0.00002103162,0.000120903],"genre_scores_gemma":[0.9991167,0.0005437186,0.0000977059,0.00002111748,0.00005645621,0.000005086354,0.00006445642,0.00001017755,0.00008455182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7719851,"threshold_uncertainty_score":0.2547279,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3013805051","doi":"10.1016/j.jaerosci.2020.105557","title":"Comparison of standardized sampling and measurement reference systems for aircraft engine non-volatile particulate matter emissions","year":2020,"lang":"en","type":"article","venue":"Journal of Aerosol Science","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"Federal Aviation Administration; Natural Environment Research Council; Sight Research UK; Transport Canada","keywords":"Environmental science; Sampling (signal processing); Particulates; Repeatability; Instrumentation (computer programming); Measurement uncertainty; Automotive engineering; Meteorology; Engineering; Statistics; Computer science; Mathematics; Chemistry; Detector; Physics; Electrical engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.07790858243984257,"gpt":0.3136723227640573,"spread":0.2357637403242148,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006735605,0.00008943308,0.0002833154,0.00004664186,0.000117348,0.00005331412,0.0001805467,0.0000302604,0.00001372817],"category_scores_gemma":[0.00008301334,0.0000664533,0.00003792598,0.0002178141,0.00006431207,0.0002477191,0.0000291652,0.0001446541,0.000001164787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004936939,"about_ca_system_score_gemma":0.0000974974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002161935,"about_ca_topic_score_gemma":3.244199e-7,"domain_scores_codex":[0.9987651,0.000007629531,0.0004694677,0.0000963622,0.0004715181,0.0001899093],"domain_scores_gemma":[0.999153,0.0000380736,0.0001548649,0.00008846398,0.0003249801,0.0002406595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004214804,0.00001532399,0.008598531,0.0002197799,0.00001559191,5.483053e-7,0.0008309158,0.1676787,0.8211052,0.000003015293,0.000850263,0.0006400024],"study_design_scores_gemma":[0.0006110679,0.0002173791,0.00259989,0.0004427438,0.00002675945,0.00001123147,0.000240453,0.7712496,0.223479,0.000002523083,0.0009885347,0.0001308234],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9256356,0.0006330897,0.07309268,0.0002074957,0.0001975589,0.000129904,0.00001098943,0.00001216163,0.00008050496],"genre_scores_gemma":[0.9925346,0.0000610326,0.007328712,0.00001449002,0.00004753579,0.000002521398,2.28449e-7,0.000007604852,0.000003300609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6035709,"threshold_uncertainty_score":0.2709887,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2125118005","doi":"10.1287/trsc.1120.0447","title":"Using Large Driving Record Samples and a Stochastic Approach for Real-World Driving Cycle Construction: Winnipeg Driving Cycle","year":2012,"lang":"en","type":"article","venue":"Transportation Science","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Manitoba; Invenia (Canada)","funders":"AUTO21 Network of Centres of Excellence; Manitoba Hydro; University of Winnipeg","keywords":"Driving cycle; Powertrain; Automotive engineering; Engineering; Sample (material); Transport engineering; Computer science; Electric vehicle","retraction":null,"screen_n_in":null,"score":{"opus":0.03524157595241564,"gpt":0.2837194590002566,"spread":0.248477883047841,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006179068,0.000167267,0.000186445,0.0002225118,0.0006170953,0.0000869751,0.000150412,0.00004803361,0.00002787031],"category_scores_gemma":[0.0000273531,0.0001721359,0.00004177095,0.0007129365,0.0001775079,0.001317873,0.000008815603,0.0001309511,0.000001287371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007380434,"about_ca_system_score_gemma":0.0000497447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005447688,"about_ca_topic_score_gemma":0.0001488307,"domain_scores_codex":[0.9985629,0.000009479511,0.0003223488,0.0002832643,0.0002585523,0.0005634894],"domain_scores_gemma":[0.9993618,0.00008612625,0.000075996,0.0001804493,0.00007052057,0.000225109],"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":[0.00001004313,0.00006114891,0.6793479,0.0002389556,0.00002228443,6.902634e-7,0.006803607,0.2239314,0.0683383,0.003769368,0.00001653482,0.01745984],"study_design_scores_gemma":[0.0002573023,0.000009731104,0.3520058,0.00008754284,0.00002420362,0.00000686065,0.0005297606,0.6455722,0.0009774885,0.00008882282,0.0001914884,0.0002487672],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6080413,0.00003517748,0.3911759,0.00000731812,0.0002198638,0.0001527414,0.00001048123,0.0001151179,0.0002420343],"genre_scores_gemma":[0.8950287,0.00002210793,0.1047315,0.000009660499,0.0001318748,0.00002344605,0.00001143847,0.0000240315,0.00001720444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4216408,"threshold_uncertainty_score":0.7019498,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1520142507","doi":"10.4271/2007-01-1327","title":"Emission Factors Analysis for Multiple Vehicles Using an On-Board, In-Use Emissions Measurement System","year":2007,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":81,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Alberta","funders":"","keywords":"On board; Automotive engineering; Computer science; Environmental science; Engineering; Aerospace engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04265159358423549,"gpt":0.2691493445034625,"spread":0.226497750919227,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001410531,0.0008097278,0.001055687,0.0006967138,0.000541711,0.000122739,0.0007233014,0.0008838549,0.00006947413],"category_scores_gemma":[0.0006406691,0.0006596805,0.0005963351,0.001613228,0.000219303,0.0005767838,0.0001414967,0.001048606,0.000009517954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001129214,"about_ca_system_score_gemma":0.00007427895,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001217517,"about_ca_topic_score_gemma":0.03728585,"domain_scores_codex":[0.9953246,0.00009343641,0.001320873,0.0009979146,0.001096627,0.001166616],"domain_scores_gemma":[0.9969274,0.0006496386,0.0001654954,0.001333909,0.000163153,0.0007603818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003143174,0.0003427174,0.01134197,0.0001315824,0.0001218636,0.00002203623,0.0000560044,0.009861283,0.9749845,0.0003287297,0.0002584037,0.002236575],"study_design_scores_gemma":[0.0008044523,0.000543637,0.983891,0.0006370078,0.0002101239,0.00001081641,0.000391242,0.0001752092,0.003427709,0.00003647425,0.009050525,0.0008218196],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994138,0.0001590848,0.00006921109,0.0001298796,0.0002364709,0.0009790384,0.00008930309,0.002220408,0.001978584],"genre_scores_gemma":[0.9953359,0.00007719525,0.003926678,0.0001394689,0.0001283585,0.0001154721,0.00006008804,0.0001546322,0.0000622423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.972549,"threshold_uncertainty_score":0.9995854,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2071765991","doi":"10.1021/es0622251","title":"Evaluation and Comparison of Portable Emissions Measurement Systems and Federal Reference Methods for Emissions from a Back-Up Generator and a Diesel Truck Operated on a Chassis Dynamometer","year":2007,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":76,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"National Research Council Canada","funders":"West Virginia University; New York State Department of Environmental Conservation","keywords":"Dynamometer; Truck; Chassis; Automotive engineering; Diesel fuel; Diesel generator; Engineering; Environmental science; Mechanical engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.05704970813862895,"gpt":0.3337670173671334,"spread":0.2767173092285045,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001341158,0.0001466066,0.0002323618,0.0001978842,0.0003488382,0.00003437911,0.0001199211,0.0001389303,0.0000382479],"category_scores_gemma":[0.00007977292,0.0001192383,0.00001195353,0.0002754884,0.0003620098,0.0001281424,0.00009286022,0.0001395233,9.477988e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001879269,"about_ca_system_score_gemma":0.00002866469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002525523,"about_ca_topic_score_gemma":0.00001109863,"domain_scores_codex":[0.9987744,0.00002693721,0.0002832967,0.0003297436,0.0003110733,0.0002745575],"domain_scores_gemma":[0.9995264,0.00004634381,0.00006340685,0.0001888915,0.00002861737,0.0001463336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001464234,0.00003801897,0.01003361,0.00001565961,0.00001601119,1.941621e-7,0.0002507741,0.0006999099,0.8932221,0.00003281955,0.00003416443,0.09564209],"study_design_scores_gemma":[0.0008936542,0.0003415007,0.02966388,0.0001399976,0.00004693906,0.00001105297,0.001745386,0.6795134,0.2844665,0.0001130427,0.002788847,0.0002758087],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858756,0.002684917,0.01066026,0.00006747132,0.0001050446,0.0004067485,0.0000268304,0.00003950732,0.0001336324],"genre_scores_gemma":[0.9883035,0.0002054085,0.01137026,0.00000721748,0.000009399676,0.00005383121,0.000006383078,0.00001063668,0.00003340825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6788135,"threshold_uncertainty_score":0.4862397,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2946905609","doi":"10.1080/15567036.2019.1679914","title":"Carbon dioxide emissions prediction of five Middle Eastern countries using artificial neural networks","year":2019,"lang":"en","type":"article","venue":"Energy Sources Part A Recovery Utilization and Environmental Effects","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Greenhouse gas; Artificial neural network; Environmental science; Carbon dioxide; Work (physics); Climate change; Mean absolute percentage error; Global warming; Meteorology; Engineering; Computer science; Geography; Machine learning; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.01135163550061098,"gpt":0.1836423000830233,"spread":0.1722906645824124,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004921009,0.0001432375,0.0001613384,0.00005200666,0.00007282938,0.00001591441,0.00004135231,0.0001007489,0.00005346555],"category_scores_gemma":[0.000003096661,0.0001384832,0.00003913444,0.00007170689,0.00004546611,0.0001423903,0.00003234714,0.00007034369,0.000001507223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003971426,"about_ca_system_score_gemma":0.000003585987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002780489,"about_ca_topic_score_gemma":0.000004645227,"domain_scores_codex":[0.9993308,0.00003393385,0.0001960694,0.0001533664,0.0001230039,0.0001628704],"domain_scores_gemma":[0.9997076,0.00004470878,0.0000537342,0.0001151688,0.000002976469,0.00007582206],"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":[0.00003631003,0.00002247534,0.03634125,0.00007628251,0.00002527971,9.273859e-7,0.000178349,0.9498843,0.008752069,0.0000171245,0.00001112962,0.004654515],"study_design_scores_gemma":[0.0002081513,0.00007792313,0.003853072,0.0001130409,0.00002044072,0.000005401303,0.0001126937,0.982726,0.01082172,0.000008489626,0.001933473,0.0001195978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961053,0.001159324,0.001842432,0.000002456618,0.0004830691,0.00009314982,0.00001873755,0.00005057946,0.0002450208],"genre_scores_gemma":[0.9987761,0.0007135413,0.00001771978,0.00002420114,0.0001016182,0.000006514674,0.00008109924,0.00002347105,0.0002557276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03284171,"threshold_uncertainty_score":0.5647182,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2190857524","doi":"10.1016/j.jngse.2015.12.007","title":"A review of novel energy options for clean rail applications","year":2015,"lang":"en","type":"review","venue":"Journal of Natural Gas Science and Engineering","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":74,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Ontario Institute of Technology","funders":"","keywords":"Ultra-low-sulfur diesel; Diesel fuel; Environmental science; Life-cycle assessment; Petrochemical; Natural gas; Pollutant; Environmental impact assessment; Work (physics); Waste management; Reducer; Engineering; Environmental engineering; Civil engineering; Chemistry; Production (economics)","retraction":null,"screen_n_in":null,"score":{"opus":0.03732316475174119,"gpt":0.3090409159374172,"spread":0.271717751185676,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008100758,0.0001657013,0.0006798354,0.00030437,0.00005093736,0.00002451703,0.0003372319,0.00006606874,0.000001463788],"category_scores_gemma":[0.00009271193,0.0001195254,0.0001692062,0.0007392013,0.00004957037,0.0002649113,0.00003311882,0.0002662675,2.603334e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001021081,"about_ca_system_score_gemma":0.0002185145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.659963e-7,"about_ca_topic_score_gemma":1.43016e-7,"domain_scores_codex":[0.9989156,0.000003064566,0.0005440715,0.00009715981,0.0002534615,0.000186706],"domain_scores_gemma":[0.9990482,0.00005253184,0.0001936809,0.0001358227,0.0004134833,0.0001562467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[4.718156e-7,0.00000723429,2.564708e-8,0.02966895,0.00002175017,2.922059e-7,0.00000753163,0.001754955,0.00009378094,0.0002060847,0.001151482,0.9670874],"study_design_scores_gemma":[0.00008191147,0.00002365099,2.696783e-7,0.03342525,0.000109265,0.0001499381,0.000003483933,0.01751573,0.00001037696,0.000003760889,0.9485505,0.0001259213],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000345569,0.9917176,0.007740894,0.00001801415,0.0002931852,0.000150852,0.00001334638,0.00001526311,0.00004733536],"genre_scores_gemma":[0.00004087035,0.9924265,0.007244617,0.00001355791,0.0002131161,0.00002218863,0.000003081057,0.00001834367,0.00001771494],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9669615,"threshold_uncertainty_score":0.4874103,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2429909282","doi":"10.1016/j.envpol.2016.05.082","title":"Scenario analysis to vehicular emission reduction in Beijing-Tianjin-Hebei (BTH) region, China","year":2016,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"University of British Columbia; Ministry of Environmental Protection","keywords":"Beijing; Environmental science; Population; Baseline (sea); Pollutant; NOx; China; Reduction (mathematics); Air quality index; Scenario analysis; Term (time); Environmental economics; Environmental engineering; Environmental protection; Business; Meteorology; Geography; Economics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.004335927495037468,"gpt":0.1826676369708014,"spread":0.178331709475764,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001221096,0.0001594694,0.0001570654,0.0002737992,0.00009639958,0.00001285877,0.00009545602,0.0001087056,0.0001923555],"category_scores_gemma":[0.000006628446,0.0001269477,0.00008480769,0.0004116033,0.00003127669,0.0002387491,0.000037265,0.0001098162,0.0001372156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005135438,"about_ca_system_score_gemma":0.000005040016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002347647,"about_ca_topic_score_gemma":0.000008534287,"domain_scores_codex":[0.9990581,0.000028829,0.0002150082,0.0002532529,0.0001784409,0.0002663908],"domain_scores_gemma":[0.9995522,0.00000423959,0.00003193779,0.0002663513,0.000001683879,0.0001435702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005176181,0.00009043187,0.04970675,0.00001366866,0.0001126101,0.00001210525,0.0004866876,0.1137432,0.7500765,0.00001458049,0.002909103,0.08278261],"study_design_scores_gemma":[0.0007341284,0.00008062135,0.9156269,0.0001408557,0.00009970047,0.00002763121,0.0001147594,0.02785477,0.04084789,0.00004748365,0.01393251,0.0004927026],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923247,0.0001787367,0.005877151,0.0009043065,0.000194814,0.0001444717,0.0000120414,0.0000917586,0.0002720319],"genre_scores_gemma":[0.9984422,0.0002060615,0.0001735019,0.00002641199,0.0001217804,0.00001366044,0.00002174694,0.00002241524,0.0009722126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8659202,"threshold_uncertainty_score":0.5176776,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2260451370","doi":"10.1021/acs.est.5b04444","title":"Field Measurements of Gasoline Direct Injection Emission Factors: Spatial and Seasonal Variability","year":2016,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Toronto","funders":"AUTO21 Network of Centres of Excellence; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Gasoline; Environmental science; Field (mathematics); Atmospheric sciences; Seasonality; Spatial variability; Environmental chemistry; Meteorology; Geography; Chemistry; Waste management; Engineering; Geology; Statistics; Mathematics","retraction":null,"screen_n_in":null,"score":{"opus":0.008002998606001656,"gpt":0.2052617110767739,"spread":0.1972587124707722,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002246683,0.00008018961,0.0000921794,0.0001065777,0.00008970539,0.00000389151,0.0001324238,0.00008462559,0.0001663499],"category_scores_gemma":[0.0000607689,0.00005380973,0.00001341156,0.0001828994,0.0003534036,0.0001464365,0.00008948176,0.00006988719,0.000003242136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001093216,"about_ca_system_score_gemma":0.000009564232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009963465,"about_ca_topic_score_gemma":0.000001843626,"domain_scores_codex":[0.9993438,0.000007689779,0.0001169745,0.0001792675,0.0001798811,0.0001723803],"domain_scores_gemma":[0.9997323,0.00002400199,0.00002538526,0.0001569043,0.000003938567,0.00005747018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003646896,0.00001428097,0.3659975,0.000002935914,0.000001536975,1.019217e-7,0.00001575065,0.00002235562,0.5855013,0.000002557758,0.000009442348,0.04842871],"study_design_scores_gemma":[0.0001409282,0.0001400536,0.1134045,0.00002650176,0.000002938051,0.000004923986,0.00001885578,0.001723857,0.8839109,0.00008874843,0.0004558554,0.00008194902],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971905,0.00003475208,0.001827329,0.00008673,0.0001027726,0.00006244957,0.000006300615,0.000075561,0.0006135404],"genre_scores_gemma":[0.9996817,0.00004070554,0.0002192614,0.000003963943,0.00001317935,0.000003814308,5.512143e-7,0.000004532857,0.0000323502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2984097,"threshold_uncertainty_score":0.2194297,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4406929887","doi":"10.1038/s41598-025-87233-y","title":"Deep learning model based prediction of vehicle CO2 emissions with eXplainable AI integration for sustainable environment","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Computer science; Deep learning; Artificial intelligence; Machine learning; Data science","retraction":null,"screen_n_in":null,"score":{"opus":0.006204156852794703,"gpt":0.2061167341158118,"spread":0.1999125772630171,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005319912,0.0000964418,0.0001151432,0.0001568527,0.0003869836,0.00006981356,0.00005526209,0.00005634517,0.00003389382],"category_scores_gemma":[0.00004674305,0.00008079186,0.00003935236,0.0002878486,0.00005485941,0.0002520469,0.00001870433,0.0001141653,6.618512e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000109667,"about_ca_system_score_gemma":0.0001044441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007020079,"about_ca_topic_score_gemma":0.000001808869,"domain_scores_codex":[0.9990453,0.000009242031,0.0002822712,0.0002514941,0.0001819891,0.0002297193],"domain_scores_gemma":[0.9994165,0.00002014495,0.00006853186,0.0003092493,0.0001278529,0.00005771534],"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":[0.00001313116,0.00002839068,0.001197055,0.0001313766,0.00000754421,0.000005517998,0.0001552113,0.9616671,0.03080017,0.0001221893,0.003035626,0.002836689],"study_design_scores_gemma":[0.0001579564,0.00003340948,0.0001576026,0.00009202876,0.00001538747,0.000002313806,0.000365681,0.9010956,0.07839301,0.0007109628,0.01890987,0.00006623202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3116407,0.0001104155,0.6850452,0.00005459526,0.0002933648,0.0003939053,0.00000168758,0.0001105691,0.002349599],"genre_scores_gemma":[0.9826654,0.000005751767,0.003256867,0.000006404786,0.00000935533,0.000104711,0.00006211181,0.00001263191,0.01387679],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6817883,"threshold_uncertainty_score":0.3294596,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2333260056","doi":"10.1021/es505534e","title":"On-road Heavy-duty Vehicle Emissions Monitoring System","year":2015,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":69,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Outotec (Canada)","funders":"California Air Resources Board","keywords":"Particulates; Truck; Environmental science; Diesel fuel; Heavy duty; NOx; Emission inventory; Port (circuit theory); Diesel particulate filter; Air pollution; Environmental engineering; Waste management; Meteorology; Air quality index; Engineering; Automotive engineering; Combustion; Chemistry; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.01116047875459796,"gpt":0.2210617694355932,"spread":0.2099012906809952,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002088386,0.000140232,0.0001203814,0.0002559637,0.0002827839,0.0000233548,0.0004665974,0.000118877,0.00003117455],"category_scores_gemma":[0.00001769073,0.0001241929,0.00002270265,0.0006224156,0.0004169279,0.0001999217,0.0001568535,0.0002651805,0.0004144037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005963606,"about_ca_system_score_gemma":0.00002530473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000048237,"about_ca_topic_score_gemma":1.96863e-7,"domain_scores_codex":[0.9988186,0.00000590059,0.0001548122,0.000265987,0.0003209005,0.0004338235],"domain_scores_gemma":[0.9993293,0.00000837205,0.00002254034,0.0003893709,0.000004379445,0.0002460603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002929432,0.0001718902,0.0565069,0.00003124989,0.00001534341,0.00006144306,0.000651842,0.04976764,0.7509909,0.00197371,0.0009055459,0.1388943],"study_design_scores_gemma":[0.0008153565,0.0004987065,0.02149924,0.0002037394,0.00001092458,0.0001441077,0.00471572,0.1283166,0.824569,0.0003508442,0.01816787,0.0007079006],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992979,0.0002536117,0.0001570736,0.0001184959,0.0005149926,0.00009322755,0.000004467786,0.000612358,0.00526673],"genre_scores_gemma":[0.9992957,0.00003109442,0.0004438205,0.000009158108,0.00005146044,0.00002178016,7.390375e-7,0.00001634623,0.0001299288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1381864,"threshold_uncertainty_score":0.5326459,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2164445937","doi":"10.5194/amt-8-3263-2015","title":"Plume-based analysis of vehicle fleet air pollutant emissions and the contribution from high emitters","year":2015,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Environment and Climate Change Canada; University of Toronto","funders":"Research Executive Agency; Ministry of Education, India; Ministry of Earth Sciences; Canada Foundation for Innovation; Government of Canada","keywords":"Environmental science; Plume; BTEX; Pollutant; Gasoline; Emission inventory; Air pollution; Meteorology; Environmental chemistry; Atmospheric sciences; Toluene; Chemistry; Xylene; Waste management; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.01510745725057513,"gpt":0.2124605611203829,"spread":0.1973531038698078,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008155189,0.000160297,0.0003524506,0.00001476249,0.00007760286,0.00001775066,0.0001603879,0.00008682734,0.00004160483],"category_scores_gemma":[0.00007990749,0.000109077,0.0000939536,0.000596719,0.00009366149,0.00007896472,0.000028612,0.0001257009,0.000001258074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000137954,"about_ca_system_score_gemma":0.00004839151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000594689,"about_ca_topic_score_gemma":0.00004072764,"domain_scores_codex":[0.9988089,0.00007458843,0.0003261424,0.0001583696,0.0004459519,0.000186005],"domain_scores_gemma":[0.9992161,0.0000549738,0.00008457284,0.000340621,0.0001791863,0.0001245101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001548429,0.0005436313,0.1684171,0.0001933574,0.007577036,0.000020418,0.003470208,0.1198902,0.4790507,0.002276782,0.03073374,0.1862785],"study_design_scores_gemma":[0.002050373,0.0001091306,0.03967776,0.0001746005,0.001028059,6.868314e-7,0.0001519935,0.7647033,0.1828496,0.0004379499,0.008428907,0.000387666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9247361,0.001707004,0.07119166,0.000660567,0.0001021994,0.0004178863,0.00003877323,0.0005619425,0.0005838557],"genre_scores_gemma":[0.9921216,0.0001006504,0.007504486,0.0001481672,0.00003115239,0.00005351837,0.00001566176,0.0000163144,0.000008494302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6448131,"threshold_uncertainty_score":0.4448033,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2013025885","doi":"10.1016/j.atmosenv.2013.03.013","title":"An integrated modelling approach to estimate urban traffic emissions","year":2013,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"AERMOD; Environmental science; Air quality index; NOx; Meteorology; Emission inventory; Atmospheric dispersion modeling; Air pollution; Environmental engineering; Atmospheric sciences; Geography; Chemistry","retraction":null,"screen_n_in":null,"score":{"opus":0.008818719349592543,"gpt":0.1976828123374391,"spread":0.1888640929878466,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000601,0.0002109727,0.0001561054,0.000004305068,0.0001070051,0.00004408525,0.0001991157,0.00007991097,0.0006219996],"category_scores_gemma":[0.000001337386,0.0001790306,0.00003773133,0.0001362472,0.0000202208,0.0001868303,0.00002537449,0.0001731428,0.000483367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001031373,"about_ca_system_score_gemma":0.000006908643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000250127,"about_ca_topic_score_gemma":2.085341e-7,"domain_scores_codex":[0.9990347,0.00001419282,0.0002107061,0.0002490635,0.0001503064,0.0003410549],"domain_scores_gemma":[0.9992218,0.00000888245,0.00001676897,0.0003861269,0.000005516176,0.0003609149],"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":[0.000001406785,0.00007905861,0.000308275,0.00001145846,0.00001055088,5.833684e-7,0.0004267055,0.974286,0.001213775,0.000009053855,0.001883172,0.02176992],"study_design_scores_gemma":[0.0001020716,0.00004536948,0.0009979943,0.00001675741,0.000007666245,0.000002914541,0.0001230508,0.9688559,0.0001478585,0.000006186211,0.02945179,0.0002424333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6848301,0.0001490555,0.312641,0.00002598788,0.00005553814,0.0002418309,0.000001824573,0.0002435936,0.001811067],"genre_scores_gemma":[0.7864905,0.00006722588,0.2125807,0.00004011028,0.00004059922,0.0001246288,0.0000181391,0.00004669702,0.0005913647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1016604,"threshold_uncertainty_score":0.7300655,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1995142565","doi":"10.3141/2011-14","title":"Global and Country Inventory of Road Passenger and Freight Transportation","year":2007,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"European Commission","keywords":"Truck; Particulates; Emission inventory; Diesel fuel; Road transport; Environmental science; Gasoline; China; Transport engineering; Business; Economy; Natural resource economics; Air quality index; Environmental protection; Geography; Engineering; Economics; Meteorology; Waste management; Automotive engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.04070981721333041,"gpt":0.3370324940481089,"spread":0.2963226768347785,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003440458,0.000209893,0.0003725821,0.0005136533,0.0002824392,0.0000498201,0.0003695272,0.0002105306,0.00009854191],"category_scores_gemma":[0.00003973854,0.0001655817,0.00013525,0.001381407,0.000532296,0.0005553596,0.000002624487,0.001101396,0.000001763273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001288813,"about_ca_system_score_gemma":0.0001819475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002818125,"about_ca_topic_score_gemma":0.03091528,"domain_scores_codex":[0.9958574,0.0002018932,0.001187706,0.0002388465,0.001899711,0.0006144546],"domain_scores_gemma":[0.9976342,0.0003066567,0.0002125077,0.0002502296,0.001201382,0.0003949768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009068202,0.0001270208,0.9492871,0.0009661444,0.0001789184,0.00009172889,0.003052798,0.002169028,0.008373491,0.002384505,0.002357193,0.03010525],"study_design_scores_gemma":[0.001067927,0.0002498114,0.9861376,0.0003361256,0.00004068317,0.000001301075,0.001180202,0.0007649169,0.001782566,0.0009027784,0.007376907,0.0001592069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960489,0.001400512,0.001141215,0.0002915622,0.0003021226,0.0004108744,0.000110672,0.00002727724,0.0002668556],"genre_scores_gemma":[0.9952989,0.003596626,0.0008268472,0.00001445042,0.0001142736,0.00001085976,0.00001787427,0.00003403008,0.0000861715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03685047,"threshold_uncertainty_score":0.986768,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2094271851","doi":"10.1016/j.scitotenv.2005.09.094","title":"Manganese concentrations in the air of the Montreal (Canada) subway in relation to surface automobile traffic density","year":2005,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Polytechnique Montréal; Société de Transport de Montréal; Université de Montréal","funders":"","keywords":"Gasoline; Manganese; Environmental science; Octane; Combustion; Environmental chemistry; Environmental engineering; Air pollution; Shanghai china; Chemistry; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.004695676927846799,"gpt":0.1755640834683766,"spread":0.1708684065405298,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005153983,0.00006179546,0.000063992,0.0000129984,0.0001357822,0.000005387006,0.0004704004,0.00001710869,0.00001666279],"category_scores_gemma":[0.00001252594,0.00002877963,0.00002453484,0.0003003236,0.000202986,0.00007871809,0.00006916073,0.0001239818,0.000002643455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000182883,"about_ca_system_score_gemma":0.0000539133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003434504,"about_ca_topic_score_gemma":0.009316924,"domain_scores_codex":[0.9991901,0.000043328,0.0001576263,0.00008364569,0.000374205,0.0001510857],"domain_scores_gemma":[0.9995308,0.00004200194,0.00003521575,0.0003653001,0.000003723664,0.00002297881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000002431572,0.00001780374,0.0005031801,0.00000198216,9.039031e-7,9.959079e-8,0.001623698,0.9788628,0.01830197,0.00003503443,0.0000527873,0.0005972757],"study_design_scores_gemma":[0.0000771208,0.000008118939,0.6406557,0.00001534634,0.000002810501,0.000002468336,0.0002747528,0.3419363,0.01690963,0.000009708082,0.00006963599,0.00003842145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970974,0.00004150411,0.000006112075,0.002037295,0.00006416272,0.0002647369,0.000004367547,0.000004176628,0.0004802544],"genre_scores_gemma":[0.999782,0.00001208069,0.00003953994,0.00002426618,0.000009265822,0.000004764947,1.781525e-7,0.000003120625,0.0001248292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6401525,"threshold_uncertainty_score":0.5199062,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2899690256","doi":"10.1155/2018/1890753","title":"Development of a Representative EV Urban Driving Cycle Based on a k-Means and SVM Hybrid Clustering Algorithm","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"Shaanxi Province Postdoctoral Science Foundation; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Driving cycle; Principal component analysis; Cluster analysis; Support vector machine; Curse of dimensionality; Algorithm; Computer science; Data mining; Hierarchical clustering; Electric vehicle; Engineering; Artificial intelligence","retraction":null,"screen_n_in":null,"score":{"opus":0.007379099514557008,"gpt":0.2423588389057061,"spread":0.2349797393911491,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000124179,0.00008721872,0.0001456838,0.0001083676,0.00005510627,0.000006549332,0.00004857201,0.00002071891,0.00001569491],"category_scores_gemma":[0.000006299442,0.00007987156,0.00003328942,0.00009646001,0.00002336384,0.0002355872,9.785701e-7,0.0001074159,5.665244e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000032559,"about_ca_system_score_gemma":0.00002820029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.111284e-7,"about_ca_topic_score_gemma":0.00001601916,"domain_scores_codex":[0.9992589,0.000007094365,0.0003893342,0.00007356949,0.0001694547,0.0001016575],"domain_scores_gemma":[0.9996029,0.00002939133,0.0001427155,0.00006259825,0.00009941617,0.00006302642],"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":[0.0001676558,0.00005274866,0.002658929,0.0001166991,0.00005351897,0.00002173514,0.0108994,0.6872823,0.06280643,0.000004671185,0.00003839051,0.2358976],"study_design_scores_gemma":[0.001852809,0.0004189786,0.1990424,0.0009497582,0.00002730827,0.00001419961,0.0009840195,0.6120796,0.1825958,0.00004473551,0.001753081,0.0002372615],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7597098,0.00003889393,0.2399711,0.00001135152,0.0001284757,0.00004797629,0.000003955768,0.00001305112,0.00007541625],"genre_scores_gemma":[0.8395375,0.00003560561,0.1603354,0.000007994939,0.00006123912,0.000001752162,0.000003769465,0.00001207406,0.000004607905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2356603,"threshold_uncertainty_score":0.3257068,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2754998392","doi":"10.1155/2017/4695975","title":"Differences in Energy Consumption in Electric Vehicles: An Exploratory Real-World Study in Beijing","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"University of Oxford","keywords":"Beijing; Energy consumption; Context (archaeology); Transport engineering; Efficient energy use; Driving cycle; Driving range; Consumption (sociology); Automotive engineering; Range (aeronautics); Environmental economics; Energy (signal processing); Environmental science; Computer science; Electric vehicle; Engineering; China; Geography","retraction":null,"screen_n_in":null,"score":{"opus":0.02540546487221877,"gpt":0.2790238891713138,"spread":0.253618424299095,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002520024,0.00009510469,0.0002129844,0.0004543715,0.00004472272,0.00002282373,0.0001341913,0.0000373643,0.000006104636],"category_scores_gemma":[0.000007301625,0.0000917218,0.00002201344,0.0001787495,0.000009851966,0.001156354,0.000001125222,0.0002394245,3.233961e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009741841,"about_ca_system_score_gemma":0.00002310999,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006617123,"about_ca_topic_score_gemma":0.02017565,"domain_scores_codex":[0.99909,0.00003002993,0.0005037601,0.00008927336,0.0001445198,0.0001424052],"domain_scores_gemma":[0.9996086,0.00002690177,0.0001737291,0.0001155352,0.00002813365,0.00004713453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007720871,0.0001108312,0.8505958,0.00002174703,0.00000423543,0.00005784454,0.002590474,0.1202441,0.008509286,0.00001841096,4.790641e-7,0.01776959],"study_design_scores_gemma":[0.001298343,0.0001282625,0.9889985,0.000205738,0.000004908539,7.652121e-7,0.0008360487,0.007422126,0.0009301588,0.00006479776,0.00001188071,0.0000984851],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999413,0.000195975,0.0001310955,0.00000923463,0.0001373399,0.00007051991,8.998306e-7,0.00001101221,0.00003091065],"genre_scores_gemma":[0.9980273,0.001713568,0.0001900622,0.000003275254,0.00003888349,0.000008852297,0.000002430953,0.00001169643,0.000003965556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1384027,"threshold_uncertainty_score":0.9977036,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3092928354","doi":"10.1016/j.trd.2020.102576","title":"Vehicular fuel consumption estimation using real-world measures through cascaded machine learning modeling","year":2020,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"McGill University","funders":"","keywords":"Fuel efficiency; Computer science; Support vector machine; Artificial neural network; Categorical variable; Usability; Machine learning; Artificial intelligence; Estimation; Automotive engineering; Engineering","retraction":null,"screen_n_in":null,"score":{"opus":0.1262303191769668,"gpt":0.3125266304904852,"spread":0.1862963113135184,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003382036,0.000198229,0.0002170086,0.00008288537,0.0002810728,0.00002292555,0.00007861955,0.00009170438,0.0002521304],"category_scores_gemma":[0.000002348867,0.0002005628,0.00005767547,0.000184396,0.00008161787,0.0003259321,0.000002924196,0.0005241909,0.00002444129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006059903,"about_ca_system_score_gemma":0.00001584833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003617921,"about_ca_topic_score_gemma":0.0001979702,"domain_scores_codex":[0.9983154,0.00004655776,0.0003997114,0.0003079792,0.00056593,0.0003644214],"domain_scores_gemma":[0.9995899,0.00002380283,0.00002836419,0.0001175306,0.00002189773,0.0002185215],"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":[0.0000476037,0.00001793333,0.03895254,0.0003083063,0.00003378656,0.00001890821,0.002393769,0.9524554,0.004249267,0.00007098466,0.000008699415,0.001442798],"study_design_scores_gemma":[0.0005017876,0.00004515161,0.01997046,0.00007517052,0.00004343282,8.684517e-7,0.0001018748,0.9716097,0.001100038,0.00006478005,0.006263022,0.0002237044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.928104,0.00100674,0.06997654,0.0002085024,0.0000317036,0.0003114822,0.00003538129,0.0001604921,0.0001651935],"genre_scores_gemma":[0.9849484,0.01219816,0.00233447,0.0000223658,0.00005648852,0.00003530895,0.0003272464,0.00004294325,0.00003463167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06764207,"threshold_uncertainty_score":0.8178714,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}