{"meta":{"query_hash":"a02a07d1756b","filters":{"venue":"Vehicles"},"cohort_total":26,"direct_labels_cover":0,"predictions_cover":26,"exported":26,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/a02a07d1756b","api":"https://metacan.xera.ac/api/v1/cohort?venue=Vehicles"},"results":[{"id":"W3037690351","doi":"10.3390/vehicles2030021","title":"Environmental and Economic Benefits of a Battery Electric Vehicle Powertrain with a Zinc–Air Range Extender in the Transition to Electric Vehicles","year":2020,"lang":"en","type":"article","venue":"Vehicles","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Powertrain; Battery pack; Automotive engineering; Electric vehicle; Battery (electricity); Driving range; Range (aeronautics); Environmental science; Engineering; Aerospace engineering","score_opus":0.004923997890336755,"score_gpt":0.16495745574547485,"score_spread":0.1600334578551381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037690351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99546427,0.0021356295,0.00016811695,0.0016471909,0.000012101527,0.00036538873,0.000025619081,0.0000693616,0.00011233807],"genre_scores_gemma":[0.9979201,0.00024354376,0.00014308628,0.0015205977,0.000090140995,0.000030809653,0.000005936721,0.000043947024,0.0000018578197],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988054,0.00005545335,0.00028787795,0.00029138196,0.00018116046,0.00037869767],"domain_scores_gemma":[0.9996041,0.00008044976,0.000040071896,0.00015831398,0.0000062857234,0.00011075326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001247956,0.00023980832,0.0002736297,0.00016127282,0.000056768797,0.000029531177,0.00020531903,0.00009869877,0.000026274007],"category_scores_gemma":[0.00000368538,0.0001885508,0.000051126462,0.00039210782,0.00002978203,0.00017611697,0.00001556783,0.00027525716,0.000014613072],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041142164,0.00010675824,0.015097339,0.00016999076,0.00013000502,0.000032505155,0.009663075,0.07309607,0.7873404,0.00034802785,0.0015764127,0.11202797],"study_design_scores_gemma":[0.0026212002,0.0015324063,0.78664875,0.000075216456,0.000088597866,0.00009885161,0.0008797138,0.12309294,0.08292774,0.00027614046,0.00094076537,0.0008176982],"about_ca_topic_score_codex":0.000037062302,"about_ca_topic_score_gemma":0.00003021868,"teacher_disagreement_score":0.7715514,"about_ca_system_score_codex":0.000073134885,"about_ca_system_score_gemma":0.000022373211,"threshold_uncertainty_score":0.7688878},"labels":[],"label_agreement":null},{"id":"W3037972087","doi":"10.3390/vehicles2030022","title":"An Approach for Estimating the Reliability of IGBT Power Modules in Electrified Vehicle Traction Inverters","year":2020,"lang":"en","type":"article","venue":"Vehicles","topic":"Silicon Carbide Semiconductor Technologies","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inverter; Insulated-gate bipolar transistor; Traction (geology); Reliability (semiconductor); Junction temperature; Power (physics); Electronic engineering; Power electronics; Automotive engineering; Power cycling; Grid-tie inverter; Maximum power point tracking; Engineering; Traction motor; Computer science; Voltage; Electrical engineering; Mechanical engineering; Physics","score_opus":0.023405518920127003,"score_gpt":0.23646981552623697,"score_spread":0.21306429660610998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037972087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994174,0.000109822206,0.0045955633,0.00024087948,0.00005591366,0.00031257386,0.000008348972,0.00042199242,0.00008092916],"genre_scores_gemma":[0.99189967,0.000004398735,0.0079230275,0.000059061505,0.000031985364,0.00005164225,0.000005326812,0.000024348572,5.1645054e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992667,0.000028704459,0.00024235748,0.0001920757,0.000093374554,0.00017680564],"domain_scores_gemma":[0.99952096,0.000120206336,0.000042167834,0.00025820304,0.000028971013,0.000029464623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019257561,0.00011037381,0.00016959861,0.000051998974,0.000028293702,0.000017561943,0.0002473708,0.00010614338,0.0000020087373],"category_scores_gemma":[0.00024603002,0.00009080607,0.000048832055,0.000253485,0.00006712367,0.00019678623,0.000012816471,0.00020431042,8.4619836e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019153156,0.00002303349,0.0036393849,0.000080298174,0.000008523168,1.8779954e-7,0.0007234293,0.11492155,0.867246,0.000082782855,0.00011786034,0.013137847],"study_design_scores_gemma":[0.00017691002,0.000045441735,0.004489669,0.0000054093134,0.0000048609336,4.565025e-7,0.0006642076,0.72401756,0.27014142,0.00036938506,0.00000971507,0.00007497044],"about_ca_topic_score_codex":0.000035469457,"about_ca_topic_score_gemma":0.0000029446571,"teacher_disagreement_score":0.609096,"about_ca_system_score_codex":0.000044207358,"about_ca_system_score_gemma":0.00000930589,"threshold_uncertainty_score":0.3702964},"labels":[],"label_agreement":null},{"id":"W3117789960","doi":"10.3390/vehicles3010002","title":"Design of a Hybrid Electric Vehicle Powertrain for Performance Optimization Considering Various Powertrain Components and Configurations","year":2020,"lang":"en","type":"article","venue":"Vehicles","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":143,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Powertrain; Automotive engineering; MATLAB; Electric vehicle; Fuel efficiency; Battery electric vehicle; Battery (electricity); Axle; Hybrid vehicle; Engineering; Computer science; Power (physics); Torque; Mechanical engineering","score_opus":0.02582703479126393,"score_gpt":0.20246601145052626,"score_spread":0.17663897665926231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3117789960","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64294666,0.0007629143,0.35491893,0.00032852465,0.00002489169,0.0004189147,0.000014199117,0.0004888329,0.00009609523],"genre_scores_gemma":[0.98586494,0.00040051405,0.0135278795,0.00009877858,0.000018860752,0.000038375827,0.000011982018,0.000033999906,0.0000046449723],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991469,0.000020038566,0.00027787773,0.00018708271,0.00010356586,0.00026454768],"domain_scores_gemma":[0.9995298,0.00018066679,0.00005699723,0.00010819443,0.000059501326,0.000064850195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011097459,0.00015883743,0.00023718808,0.00010825233,0.00009721089,0.000030857707,0.00012162244,0.000052905765,0.000008116546],"category_scores_gemma":[0.00007601679,0.00017034341,0.000031947966,0.00025293115,0.000057754853,0.00014877999,0.000019136061,0.00013316055,0.0000022989773],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058199927,0.000025852914,0.00034953922,0.00017577242,0.00007012985,0.0000051391803,0.00024744126,0.46246314,0.5258232,0.0003920035,0.00038694093,0.0100026755],"study_design_scores_gemma":[0.0004838542,0.00021617461,0.0004615482,0.000018335455,0.000019937828,0.000014412766,0.000023423867,0.8113986,0.1869746,0.00013478898,0.00009885571,0.00015541598],"about_ca_topic_score_codex":0.000004180377,"about_ca_topic_score_gemma":2.4013005e-7,"teacher_disagreement_score":0.34893548,"about_ca_system_score_codex":0.000023988336,"about_ca_system_score_gemma":0.000027254015,"threshold_uncertainty_score":0.6946402},"labels":[],"label_agreement":null},{"id":"W3198254577","doi":"10.3390/vehicles3030034","title":"EV Overnight Charging Strategy in Residential Sector: Case of Winter Season in Quebec","year":2021,"lang":"en","type":"article","venue":"Vehicles","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Ministère des relations internationales et de la Francophonie","keywords":"Grid; Software deployment; Market penetration; Environmental science; Consumption (sociology); Peak demand; Automotive engineering; Probabilistic logic; Electric vehicle; Power consumption; Environmental economics; Computer science; Power (physics); Electrical engineering; Electricity; Engineering; Economics","score_opus":0.007113818706124044,"score_gpt":0.21342955145598408,"score_spread":0.20631573274986004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198254577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99712574,0.0014687701,0.000037574646,0.000044107266,0.00008063872,0.000056050903,0.0000108864915,0.00003965735,0.001136567],"genre_scores_gemma":[0.9995357,0.00005979561,0.000061788734,0.000018733135,0.00008364413,0.000003200787,0.000006158684,0.000022788405,0.00020822317],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992037,0.000040367322,0.00025434783,0.00015708622,0.000102226855,0.00024231414],"domain_scores_gemma":[0.99972576,0.00003382745,0.000026434462,0.0001491177,0.000025919744,0.000038959537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000078187215,0.00011833896,0.00019106605,0.00011948708,0.000015049254,0.000032518332,0.00007348092,0.000101415484,0.00022157775],"category_scores_gemma":[0.0000132772475,0.00012307944,0.000046459012,0.00034080417,0.000014942012,0.00016522681,0.00001900418,0.00024963627,0.000004389596],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069321555,0.00011567428,0.12530258,0.0006552798,0.000101963844,0.011736884,0.0035178424,0.06231827,0.72946095,0.0014976904,0.00403244,0.06119111],"study_design_scores_gemma":[0.0020672467,0.00007088585,0.25974172,0.0004736491,0.00002347842,0.0007572596,0.0016326621,0.10720529,0.62450236,0.0010856044,0.0017845047,0.00065531174],"about_ca_topic_score_codex":0.0057252496,"about_ca_topic_score_gemma":0.07375994,"teacher_disagreement_score":0.13443916,"about_ca_system_score_codex":0.00011370598,"about_ca_system_score_gemma":0.000057926438,"threshold_uncertainty_score":0.9431415},"labels":[],"label_agreement":null},{"id":"W3215417243","doi":"10.3390/vehicles3040048","title":"Design of Fast Charging Station with Energy Management for eBuses","year":2021,"lang":"en","type":"article","venue":"Vehicles","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Energy storage; Renewable energy; Energy management; Automotive engineering; Computer science; Hybrid power; Controller (irrigation); Power (physics); Electrical engineering; Energy (signal processing); Engineering","score_opus":0.023015095545730405,"score_gpt":0.24842045388586315,"score_spread":0.22540535834013276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215417243","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04287333,0.00021300137,0.9563946,0.000052110114,0.000016223566,0.00009040887,0.000006994319,0.00018115145,0.0001721809],"genre_scores_gemma":[0.8856068,0.00028735338,0.11378646,0.000012034808,0.0000083232935,0.00008450118,0.000010812089,0.000023096596,0.00018060779],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99960345,0.00000696119,0.0000744855,0.00008873955,0.0000902341,0.00013613485],"domain_scores_gemma":[0.9997455,0.000059340808,0.000012612658,0.0001267504,0.000044924214,0.000010908964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000031634892,0.000057135556,0.00007276544,0.000069485264,0.000020890824,0.000009475095,0.00007269785,0.00002093044,0.000007765173],"category_scores_gemma":[0.000006826889,0.000050912462,0.000010347759,0.00014654294,0.000021137093,0.00006478599,0.000025502812,0.000029484347,0.000001123918],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003656697,0.000028102166,0.0002196593,0.00036795763,0.00012103869,0.000028065304,0.0001132827,0.36463308,0.19614992,0.0050715436,0.0005004293,0.43273035],"study_design_scores_gemma":[0.00033485514,0.000054859076,0.00033349567,0.00006496975,0.000008018145,0.0000022669594,0.00052512187,0.06522015,0.9289032,0.0014198807,0.0030262677,0.000106890904],"about_ca_topic_score_codex":0.0000012959375,"about_ca_topic_score_gemma":0.0000034924228,"teacher_disagreement_score":0.8427335,"about_ca_system_score_codex":0.000026540394,"about_ca_system_score_gemma":0.000005584817,"threshold_uncertainty_score":0.20761499},"labels":[],"label_agreement":null},{"id":"W4206933402","doi":"10.3390/vehicles4010005","title":"Improved Mathematical Approach for Modeling Sport Differential Mechanism","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Mechanical Engineering and Vibrations Research","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Clutch; Torque; Kinematics; Computer science; Control theory (sociology); Mechanism (biology); Mathematical model; Differential equation; Constraint (computer-aided design); Control engineering; Engineering; Automotive engineering; Control (management); Mathematics; Mechanical engineering; Physics","score_opus":0.027418754963298805,"score_gpt":0.2415665244687862,"score_spread":0.21414776950548742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206933402","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11376186,0.000027201339,0.88526887,0.000016878426,0.00008228202,0.0002530045,0.000021626445,0.00030087505,0.00026741225],"genre_scores_gemma":[0.9714972,0.0000035082924,0.027681114,0.0000067833935,0.000078028184,0.00049288175,0.00004505502,0.00004137242,0.00015409855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925655,0.0000071316886,0.00016752805,0.00014439889,0.00017962475,0.00024477133],"domain_scores_gemma":[0.9997146,0.00002314261,0.000007190058,0.00016689497,0.000016094991,0.00007207413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016145555,0.00009717647,0.00013901884,0.00007288311,0.0001462632,0.000029430215,0.00017115253,0.000038964987,0.00012882418],"category_scores_gemma":[0.000012685842,0.000096215816,0.00007154491,0.00010300614,0.0000051635348,0.00003720699,0.00007113295,0.00019987173,0.000003383251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019006831,0.00009378191,5.667028e-7,0.00020783854,0.000044398563,0.0000010060849,0.00008582808,0.8106543,0.09379696,0.09240101,0.000113644695,0.0025816474],"study_design_scores_gemma":[0.00021819113,0.00004057222,3.2994615e-7,0.000002161961,0.000008010296,0.0000038049118,0.00007487281,0.9891152,0.0056731766,0.004630727,0.00011779866,0.000115157905],"about_ca_topic_score_codex":0.000002333284,"about_ca_topic_score_gemma":1.1651909e-7,"teacher_disagreement_score":0.8577353,"about_ca_system_score_codex":0.000039651426,"about_ca_system_score_gemma":0.00000906885,"threshold_uncertainty_score":0.39235672},"labels":[],"label_agreement":null},{"id":"W4210590506","doi":"10.3390/vehicles4010007","title":"Shared Automated Electric Vehicle Prospects for Low Carbon Road Transportation in British Columbia, Canada","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Electrification; Automation; Transport engineering; Environmental economics; Electric vehicle; Energy (signal processing); Engineering; Electricity; Economics; Electrical engineering","score_opus":0.004715734943976558,"score_gpt":0.18178489473279483,"score_spread":0.17706915978881826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210590506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99804264,0.000101031525,0.000020176027,0.000062873005,0.00015279603,0.0005606734,0.00046926434,0.0005303848,0.000060180842],"genre_scores_gemma":[0.99863464,0.0000037875884,0.000077293764,0.00007555972,0.000013649708,0.00058646715,0.0005094816,0.000027977301,0.000071152],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99915427,0.000010717219,0.00028470714,0.0001623626,0.00017368952,0.0002142572],"domain_scores_gemma":[0.99977654,0.000019868032,0.000028127897,0.0000909922,0.000047861908,0.0000365847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007826535,0.000066927336,0.00012253388,0.000059424325,0.000114237235,0.000046940622,0.00008775844,0.000031577045,0.000056447312],"category_scores_gemma":[0.00000759709,0.0001341247,0.000026382962,0.0007081835,0.000006644151,0.00006562749,0.0000015697549,0.00012881824,2.6057856e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004436038,0.0004492087,0.5849717,0.00067441864,0.00013128736,0.00014804173,0.0016194195,0.24770494,0.110269755,0.00022795025,0.015297196,0.038461715],"study_design_scores_gemma":[0.00064359483,0.000026668398,0.8392045,0.000011228834,0.000007823223,0.0000013342383,0.00013037419,0.15823546,0.0007313616,0.000056168894,0.0008019005,0.00014959207],"about_ca_topic_score_codex":0.6889305,"about_ca_topic_score_gemma":0.992393,"teacher_disagreement_score":0.30346254,"about_ca_system_score_codex":0.00028350562,"about_ca_system_score_gemma":0.00020180078,"threshold_uncertainty_score":0.5469446},"labels":[],"label_agreement":null},{"id":"W4226061075","doi":"10.3390/vehicles4020021","title":"Motion Planning for Autonomous Vehicles Based on Sequential Optimization","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Kinematics; Acceleration; Trajectory; Trajectory optimization; Control theory (sociology); Nonlinear system; Computer science; Finite element method; Node (physics); Mathematics; Engineering; Physics; Artificial intelligence; Classical mechanics; Structural engineering","score_opus":0.034962854737969395,"score_gpt":0.2689507922467902,"score_spread":0.2339879375088208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226061075","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007970813,0.00003739064,0.98945755,0.00096020766,0.0006249338,0.00028512735,0.000023463357,0.00040620493,0.00023431578],"genre_scores_gemma":[0.5611535,3.0793984e-7,0.43780735,0.0006007293,0.00011250266,0.00014375261,0.000063388565,0.000020490816,0.00009804707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985751,0.00013112958,0.00021045883,0.00042386944,0.0003667612,0.00029271288],"domain_scores_gemma":[0.9992119,0.00019371338,0.00012551191,0.00035762155,0.00004736289,0.00006390278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048058745,0.0001379547,0.00013524684,0.00020231158,0.0005812561,0.00013278656,0.00057538395,0.00004363486,0.000013970697],"category_scores_gemma":[0.00004871617,0.0001521976,0.00007054373,0.00029802154,0.000021806429,0.00021171027,0.00014634922,0.00015904632,0.000007653973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018234194,0.000065115986,0.0002839223,0.000007954329,0.0000063339867,0.000015143314,0.00026078793,0.9848963,0.00040984133,0.0010544811,0.0006191082,0.012362752],"study_design_scores_gemma":[0.00056344364,0.0002677265,0.00071692775,0.0000146640505,0.0000066739503,0.00000882685,0.000034875906,0.99574286,0.0012333281,0.00036923605,0.00086552976,0.00017588114],"about_ca_topic_score_codex":0.000012213517,"about_ca_topic_score_gemma":7.267805e-8,"teacher_disagreement_score":0.5531826,"about_ca_system_score_codex":0.00015567573,"about_ca_system_score_gemma":0.00009857578,"threshold_uncertainty_score":0.62064373},"labels":[],"label_agreement":null},{"id":"W4281558663","doi":"10.3390/vehicles4020030","title":"Modeling Combined Operation of Engine and Torque Converter for Improved Vehicle Powertrain’s Complex Control","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Mechanical Systems and Engineering","field":"Energy","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Powertrain; Torque converter; Crankshaft; Torque; Jerk; Drivetrain; Computer science; Control engineering; Acceleration; Moment (physics); Control theory (sociology); Vehicle dynamics; Automotive engineering; Engineering; Control (management); Clutch","score_opus":0.01730193480290733,"score_gpt":0.2112047239667688,"score_spread":0.19390278916386144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281558663","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8293575,0.00022420134,0.16876319,0.00063427334,0.00022546951,0.0005218521,0.000087008164,0.00009564541,0.000090845475],"genre_scores_gemma":[0.9988807,0.0000035035036,0.0006894219,0.00017791083,0.000048609778,0.00010561253,0.000029254967,0.000021695245,0.00004329533],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993228,0.00003396726,0.00025462286,0.00015022192,0.000082218925,0.00015621744],"domain_scores_gemma":[0.9996995,0.00006271308,0.00003330261,0.00011412849,0.000038580372,0.000051797753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021783095,0.00009126677,0.00021983252,0.00003428072,0.00010562889,0.000015741025,0.00007902145,0.000035346136,0.000099547615],"category_scores_gemma":[0.000020136675,0.000087955996,0.000047734935,0.000043338277,0.000009143545,0.000053328087,0.000037233225,0.00006770714,6.717283e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014884623,0.000044588967,0.000029178622,0.00006596829,0.000053533822,5.2177495e-7,0.00016887214,0.15392669,0.81625426,0.023348322,0.00010159124,0.0058576595],"study_design_scores_gemma":[0.0020011065,0.00021742575,0.00006261237,0.00000624699,0.000012653642,0.0000018137135,0.00010958927,0.9921439,0.0026209326,0.0003792348,0.0023383088,0.000106166466],"about_ca_topic_score_codex":0.0006726161,"about_ca_topic_score_gemma":0.000036277648,"teacher_disagreement_score":0.8382172,"about_ca_system_score_codex":0.000028618231,"about_ca_system_score_gemma":0.000010139677,"threshold_uncertainty_score":0.35867417},"labels":[],"label_agreement":null},{"id":"W4292066939","doi":"10.3390/vehicles4030047","title":"Off-Road Electric Vehicles and Autonomous Robots in Agricultural Sector: Trends, Challenges, and Opportunities","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":138,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Ministère des relations internationales et de la Francophonie","keywords":"Electrification; Agriculture; Renewable energy; Engineering; Environmental economics; Business; Electricity; Economics; Electrical engineering","score_opus":0.04701379401515565,"score_gpt":0.20724833189270278,"score_spread":0.16023453787754713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292066939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9569419,0.0345299,6.2676113e-9,0.0063129826,0.000061020575,0.000108675405,0.000026239943,0.0000884807,0.0019307836],"genre_scores_gemma":[0.99319315,0.0052683554,0.0000074037885,0.0002941789,0.00019946211,0.000053955806,0.00006506629,0.0000016838543,0.0009167611],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986748,0.00015015194,0.00021626496,0.00038691383,0.00021399702,0.0003578456],"domain_scores_gemma":[0.9996325,0.000106846564,0.00007618234,0.000044385986,0.000022310918,0.00011779249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020765245,0.00020610742,0.00024587408,0.000050267325,0.0003532805,0.00006687175,0.00017110474,0.00007573657,0.00012540736],"category_scores_gemma":[0.000007290016,0.000081947815,0.00005230707,0.00030027988,0.000048095815,0.0001707714,0.00019384132,0.0002336981,0.0000025975287],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019000781,0.000096818934,0.0023665163,0.000007383158,0.000014122792,0.000026598233,0.00056508306,0.0000047987287,0.058357567,0.00093348866,0.0013206009,0.936288],"study_design_scores_gemma":[0.00022918737,0.00034217854,0.9385409,0.000010204144,0.0000126478735,0.000096668984,0.0033155454,0.00006172681,0.00042487407,0.00024798975,0.056422837,0.00029525653],"about_ca_topic_score_codex":0.00032042785,"about_ca_topic_score_gemma":0.0011487221,"teacher_disagreement_score":0.9361744,"about_ca_system_score_codex":0.000040878553,"about_ca_system_score_gemma":0.000007865686,"threshold_uncertainty_score":0.3341735},"labels":[],"label_agreement":null},{"id":"W4304775246","doi":"10.3390/vehicles4040060","title":"Improved Technique for Autonomous Vehicle Motion Planning Based on Integral Constraints and Sequential Optimization","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kinematics; Integral sliding mode; Nonlinear system; Curvature; Trajectory; Motion planning; Node (physics); Piecewise; Trajectory optimization; Mathematical optimization; Computer science; Motion (physics); Degrees of freedom (physics and chemistry); Nonlinear programming; Control theory (sociology); Mathematics; Geometry; Engineering; Artificial intelligence; Mathematical analysis; Optimal control; Robot; Structural engineering","score_opus":0.008584506742554305,"score_gpt":0.20921727654192107,"score_spread":0.20063276979936676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304775246","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15956372,0.00006588047,0.8382519,0.00010368881,0.00026307462,0.00086086476,0.00014204878,0.00033952473,0.00040929197],"genre_scores_gemma":[0.9959594,0.0000010297547,0.003278332,0.00006389141,0.000054308915,0.0005192613,0.00006810961,0.000036644396,0.00001903557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930793,0.00003750874,0.00018551313,0.00018070929,0.0000969002,0.00019144522],"domain_scores_gemma":[0.99972475,0.000049975595,0.000042121606,0.00011240738,0.000024506284,0.000046232995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024459884,0.00012562869,0.00013929582,0.00010850561,0.00018963063,0.000051466257,0.00008441327,0.000058124566,0.000023269617],"category_scores_gemma":[0.00001044469,0.00013848228,0.00004811159,0.00008432616,0.00003101209,0.00005864488,0.000022877348,0.00015691126,3.8143082e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041155276,0.000019736242,0.00020019538,0.000035025845,0.000015382717,0.0000026240166,0.00006527151,0.9115401,0.07484078,0.00037559212,0.000031847223,0.012832319],"study_design_scores_gemma":[0.00079894776,0.00016046251,0.0001430394,0.000017981572,0.000011031298,0.0000072754406,0.0001055377,0.9954932,0.0028236986,0.00006850851,0.00021889039,0.0001514727],"about_ca_topic_score_codex":0.000020396155,"about_ca_topic_score_gemma":0.000002029572,"teacher_disagreement_score":0.8363957,"about_ca_system_score_codex":0.00012650213,"about_ca_system_score_gemma":0.000021148355,"threshold_uncertainty_score":0.5647144},"labels":[],"label_agreement":null},{"id":"W4368376864","doi":"10.3390/vehicles5020030","title":"Intelligent Deep Learning Estimators of a Lithium-Ion Battery State of Charge Design and MATLAB Implementation—A Case Study","year":2023,"lang":"en","type":"article","venue":"Vehicles","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; John Abbott College","funders":"","keywords":"State of charge; Estimator; Computer science; Adaptive neuro fuzzy inference system; Extended Kalman filter; Robustness (evolution); Artificial neural network; Mean squared error; Control theory (sociology); Machine learning; Kalman filter; Artificial intelligence; Battery (electricity); Fuzzy logic; Fuzzy control system; Mathematics; Statistics","score_opus":0.03779208041597391,"score_gpt":0.3247762620696241,"score_spread":0.2869841816536502,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4368376864","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96959,0.000114835566,0.029537123,0.000016771364,0.000027735588,0.00037591584,0.0000063807643,0.0003262376,0.0000049856026],"genre_scores_gemma":[0.99776596,0.00017780386,0.0019500173,0.0000017275892,0.000004328594,0.000048276415,0.0000038198477,0.00002840632,0.000019661691],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99913645,0.000056834786,0.0002806104,0.00014095903,0.00016381651,0.00022131484],"domain_scores_gemma":[0.9995105,0.00021714157,0.000049536196,0.00015121335,0.000039492406,0.0000321037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031155636,0.00010498199,0.0001679155,0.00030361483,0.000046264013,0.000013633481,0.00009747016,0.00002784767,0.000026285905],"category_scores_gemma":[0.000045439738,0.00010290816,0.00001776587,0.00041833214,0.000053793625,0.00010424635,0.00012605576,0.00015039124,0.0000140456505],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030316323,0.00008140117,0.084935024,0.00048113547,0.00015945428,0.0007296273,0.0072673755,0.19209887,0.10509611,0.000018665769,0.00013753684,0.6089645],"study_design_scores_gemma":[0.00067374326,0.0006074026,0.013067142,0.000065505985,0.000023145052,0.000109652596,0.023969615,0.2457304,0.71497583,0.00037751862,0.00012024661,0.00027978903],"about_ca_topic_score_codex":0.00005412656,"about_ca_topic_score_gemma":0.000014013088,"teacher_disagreement_score":0.60987973,"about_ca_system_score_codex":0.000030004278,"about_ca_system_score_gemma":0.000006542155,"threshold_uncertainty_score":0.4196473},"labels":[],"label_agreement":null},{"id":"W4383955260","doi":"10.3390/vehicles5030045","title":"Design and Experimental Evaluation of a Scaled Modular Testbed Platform for the Drivetrain of Electric Vehicles","year":2023,"lang":"en","type":"article","venue":"Vehicles","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Testbed; Drivetrain; Modular design; Powertrain; Automotive engineering; Computer science; Torque; Embedded system; Hardware-in-the-loop simulation; Engineering","score_opus":0.041715501496205266,"score_gpt":0.2754465086059056,"score_spread":0.23373100710970032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383955260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9902044,0.0012933292,0.0074892417,0.000024300292,0.00003783492,0.00079895934,0.000003823203,0.00008187349,0.00006622164],"genre_scores_gemma":[0.9995664,0.000016630638,0.0002263542,0.0000033150104,0.000028050523,0.00012626793,0.0000041595454,0.000016527527,0.00001233241],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930567,0.000041946634,0.00021873371,0.000084985404,0.00023147053,0.00011718578],"domain_scores_gemma":[0.99934685,0.00039593672,0.00004829343,0.00011058473,0.000076431825,0.000021879168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080159935,0.00007790499,0.00014371636,0.00009897639,0.00004316836,0.000014270587,0.0000690061,0.000044989723,0.000006142796],"category_scores_gemma":[0.00004679607,0.00005961084,0.000042233118,0.00023414232,0.000022574182,0.00007384579,0.0000078521625,0.000029355839,0.0000024110955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023251934,0.0000084821095,0.0000728928,0.000024420011,0.000041393225,7.468211e-8,0.00036315073,0.3852055,0.59440786,0.00011006937,0.00006027699,0.019682618],"study_design_scores_gemma":[0.0009480237,0.00005157172,0.004889358,0.000015036317,0.000028839522,5.702182e-7,0.00023591713,0.8043838,0.18904424,0.00032729525,0.000025232344,0.000050094175],"about_ca_topic_score_codex":0.00001436455,"about_ca_topic_score_gemma":0.000001026728,"teacher_disagreement_score":0.4191783,"about_ca_system_score_codex":0.000023244904,"about_ca_system_score_gemma":0.000016644346,"threshold_uncertainty_score":0.24308597},"labels":[],"label_agreement":null},{"id":"W4385420139","doi":"10.3390/vehicles5030049","title":"Real-Time Hardware-in-the-Loop Emulation of Path Tracking in Low-Cost Agricultural Robots","year":2023,"lang":"en","type":"article","venue":"Vehicles","topic":"Control and Dynamics of Mobile Robots","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Ministère des relations internationales et de la Francophonie","keywords":"Emulation; Inertial measurement unit; Robot; Computer science; Simulation; Real-time computing; Servo; MATLAB; Encoder; Path (computing); Servomotor; Rate gyro; Tracking (education); Control engineering; Embedded system; Engineering; Artificial intelligence; Gyroscope","score_opus":0.009924921821698662,"score_gpt":0.22424220986523125,"score_spread":0.2143172880435326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385420139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99875355,0.00005859107,0.00006914787,0.000095080424,0.00007001674,0.00021139144,0.000008872958,0.00014207077,0.0005912644],"genre_scores_gemma":[0.99965554,0.00008964972,0.00006558999,0.0000045239394,0.00004407721,0.000026488839,0.000038735885,0.0000136798635,0.00006171783],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99926454,0.000029231864,0.00024052142,0.000112395835,0.00014407885,0.00020925813],"domain_scores_gemma":[0.99967986,0.00012322338,0.000028523664,0.00012471866,0.000022016775,0.0000216836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020902496,0.00010155938,0.00016438335,0.00011791365,0.000021423159,0.000023501882,0.00013031147,0.00006147537,0.0000064547803],"category_scores_gemma":[0.000023366589,0.00007836203,0.00005194241,0.00043299733,0.000010823431,0.00012993035,0.000016832966,0.00010524545,0.000044429427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000070750166,0.000023355333,0.0049265474,0.000056305187,0.000006646529,0.000019095085,0.00067905197,0.91402185,0.06492498,0.00009403233,0.00013404284,0.015107012],"study_design_scores_gemma":[0.00033391116,0.000007667283,0.5790056,0.000103195336,0.000003924803,0.0000014923704,0.00013665835,0.4198099,0.00038391748,0.000107034015,0.000013611645,0.00009311567],"about_ca_topic_score_codex":0.00010885406,"about_ca_topic_score_gemma":0.00021976772,"teacher_disagreement_score":0.57407904,"about_ca_system_score_codex":0.000037677277,"about_ca_system_score_gemma":0.0000059841054,"threshold_uncertainty_score":0.31955105},"labels":[],"label_agreement":null},{"id":"W4386050717","doi":"10.3390/vehicles5030055","title":"Adaptive Robust Terminal Sliding Mode Control with Integral Backstepping Synthesized Method for Autonomous Ground Vehicle Control","year":2023,"lang":"en","type":"article","venue":"Vehicles","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Control theory (sociology); Backstepping; Robustness (evolution); Terminal sliding mode; Parametric statistics; Lyapunov stability; Lyapunov function; Computer science; Sliding mode control; Robust control; Adaptive control; Nonlinear system; Control engineering; Engineering; Control system; Mathematics; Control (management); Artificial intelligence","score_opus":0.01521694788775248,"score_gpt":0.232976594598852,"score_spread":0.2177596467110995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386050717","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34966892,0.00025920232,0.64618653,0.00026173936,0.0003142553,0.0013758027,0.00025597707,0.001079576,0.00059800345],"genre_scores_gemma":[0.992101,0.000011367214,0.006461604,0.000094766045,0.00029812104,0.0006397947,0.000018433202,0.00015046078,0.00022443812],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997784,0.00013447,0.0005157503,0.0004671653,0.00026469596,0.0008339094],"domain_scores_gemma":[0.99807227,0.0011694501,0.000121865625,0.0003353411,0.00012397072,0.00017709621],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006996746,0.00042615403,0.00075568474,0.00023483619,0.00025332512,0.00019244288,0.00032796912,0.00018596654,0.000011186131],"category_scores_gemma":[0.00005730509,0.00037176823,0.00022232255,0.00034699024,0.00004543957,0.00027380686,0.000025606672,0.00027894467,0.000042786098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011044659,0.00005524859,0.0008877027,0.0002576673,0.0010605414,0.00009293053,0.0006315194,0.84120023,0.096586235,0.0055583026,0.00038884557,0.052176278],"study_design_scores_gemma":[0.0051319683,0.00021365563,0.0011147516,0.00017280594,0.00016428613,0.00003573707,0.00068484625,0.99073344,0.0005089346,0.00020558668,0.000538559,0.0004954327],"about_ca_topic_score_codex":0.00024119791,"about_ca_topic_score_gemma":0.00016887605,"teacher_disagreement_score":0.6424321,"about_ca_system_score_codex":0.00020693087,"about_ca_system_score_gemma":0.000057415866,"threshold_uncertainty_score":0.9998734},"labels":[],"label_agreement":null},{"id":"W4387693951","doi":"10.3390/vehicles5040078","title":"A Review of Deep Reinforcement Learning Algorithms for Mobile Robot Path Planning","year":2023,"lang":"en","type":"review","venue":"Vehicles","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Reinforcement learning; Motion planning; Computer science; Mobile robot; Path (computing); Plan (archaeology); Artificial intelligence; Artificial neural network; Robot; Shortest path problem; Function (biology); Distributed computing; Human–computer interaction; Theoretical computer science; Computer network; Geography","score_opus":0.04751599244975764,"score_gpt":0.31945919341772816,"score_spread":0.27194320096797053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387693951","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[9.755227e-7,0.9813443,0.015981192,0.0000040631858,0.00014468741,0.0013484586,0.000016536222,0.00096618297,0.00019365158],"genre_scores_gemma":[0.000017728202,0.9969746,0.0012546744,0.000018017732,0.00008058034,0.0011542554,0.00020801325,0.00013497389,0.00015718935],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982452,0.00004212587,0.00092613057,0.0002796357,0.00012457217,0.00038234095],"domain_scores_gemma":[0.9989994,0.0002774962,0.00028345812,0.0003442114,0.00004494594,0.000050472016],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00049972814,0.00038319404,0.0016183404,0.00019416827,0.00008985967,0.000008473276,0.0003583273,0.00042420393,0.000024583791],"category_scores_gemma":[0.00007519115,0.0003466443,0.0004670664,0.00037306538,0.00004974397,0.00004833667,0.00010023806,0.0005648324,0.000068256646],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[7.457906e-7,0.0000045965285,5.017077e-7,0.19196154,0.00018684287,0.0000046533523,0.00003380839,0.011482363,8.0891533e-7,0.000061688916,0.0004530353,0.7958094],"study_design_scores_gemma":[0.00009300711,0.000085680746,4.232551e-7,0.11434931,0.0003735824,0.000009434687,0.000025574573,0.01904642,0.0000100346115,0.000032244847,0.86565197,0.0003223477],"about_ca_topic_score_codex":0.0000025791796,"about_ca_topic_score_gemma":3.4872153e-7,"teacher_disagreement_score":0.8651989,"about_ca_system_score_codex":0.000101203485,"about_ca_system_score_gemma":0.00005372137,"threshold_uncertainty_score":0.99989855},"labels":[],"label_agreement":null},{"id":"W4390815511","doi":"10.3390/vehicles6010007","title":"Collision Risk in Autonomous Vehicles: Classification, Challenges, and Open Research Areas","year":2024,"lang":"en","type":"article","venue":"Vehicles","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Collision; Reliability (semiconductor); Computer science; Hazard; Warning system; Open research; Field (mathematics); Collision avoidance; Stability (learning theory); Risk analysis (engineering); Computer security; Machine learning; Business; Telecommunications","score_opus":0.0725604630638158,"score_gpt":0.31593062204655636,"score_spread":0.24337015898274056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390815511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.941807,0.037934337,0.00008830801,0.0023133606,0.00015055762,0.0005271887,0.000023044955,0.0009890854,0.016167117],"genre_scores_gemma":[0.9742336,0.024947237,0.00036904847,0.000012208565,0.00004982062,0.00011637813,0.000007194944,0.000046810987,0.00021768786],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9985501,0.00014037456,0.0003050796,0.00044339572,0.00016979378,0.000391227],"domain_scores_gemma":[0.9991188,0.0003326693,0.000018717948,0.00040641564,0.000042318483,0.00008104531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015650254,0.00016440435,0.00022496609,0.0003958578,0.00016123222,0.00014680602,0.00047919288,0.00030850142,0.000013464728],"category_scores_gemma":[0.00006900701,0.0001605506,0.000026722286,0.00046761116,0.00019675824,0.00031778353,0.00024685936,0.00083696545,0.000167154],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036753172,0.000085133484,0.0035186799,0.00021838253,0.000062915016,0.000087356784,0.002926373,0.00065714604,0.0021566488,0.087280616,0.00189302,0.901077],"study_design_scores_gemma":[0.0010825775,0.0001935307,0.40395015,0.00054024777,0.000026660984,0.000049618804,0.0025378575,0.31082755,0.0037831801,0.06283925,0.21350099,0.00066836877],"about_ca_topic_score_codex":0.00011440524,"about_ca_topic_score_gemma":0.00028673655,"teacher_disagreement_score":0.9004086,"about_ca_system_score_codex":0.00019028716,"about_ca_system_score_gemma":0.00007496106,"threshold_uncertainty_score":0.6547063},"labels":[],"label_agreement":null},{"id":"W4390819080","doi":"10.3390/vehicles6010008","title":"Planning Speed Mode of All-Wheel Drive Autonomous Vehicles Considering Complete Constraint Set","year":2024,"lang":"en","type":"article","venue":"Vehicles","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Axle; Control theory (sociology); Kinematics; Nonlinear system; Torque; Drivetrain; Engineering; Quadratic programming; Vehicle dynamics; Computer science; Automotive engineering; Mathematics; Mathematical optimization; Control (management); Structural engineering","score_opus":0.023905289509571687,"score_gpt":0.2500028419976921,"score_spread":0.22609755248812044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390819080","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98849595,0.0024970863,0.0034947668,0.00015949666,0.000504841,0.0002623126,0.0003052852,0.0008201389,0.0034601241],"genre_scores_gemma":[0.9990856,0.000037194954,0.0005161933,0.00004742905,0.0001379586,0.000012961156,0.00003237089,0.00007430203,0.000055997905],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984824,0.000037036945,0.00053316454,0.0002985041,0.00022586799,0.0004229932],"domain_scores_gemma":[0.9993087,0.00020385078,0.00005426028,0.00026570316,0.00004568949,0.00012177038],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018081059,0.00027644238,0.00044401898,0.00018231645,0.000058459715,0.00013639333,0.00020697711,0.00013179558,0.000026956508],"category_scores_gemma":[0.000012450906,0.00028092356,0.0001509438,0.0001568573,0.0001248996,0.0001422525,0.000056316872,0.00028202048,0.000047672558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019196641,0.00002414183,0.001766488,0.0007840824,0.00076579646,0.00031956309,0.0037644717,0.39339167,0.5687058,0.014640214,0.0011096736,0.014708898],"study_design_scores_gemma":[0.00038033415,0.00003730782,0.00062452146,0.00038625393,0.000050780964,0.00007448279,0.00056986953,0.98757774,0.0037308324,0.00083557796,0.0054071466,0.00032518516],"about_ca_topic_score_codex":0.00015246685,"about_ca_topic_score_gemma":0.000025993713,"teacher_disagreement_score":0.59418607,"about_ca_system_score_codex":0.00009570281,"about_ca_system_score_gemma":0.000053961263,"threshold_uncertainty_score":0.9999643},"labels":[],"label_agreement":null},{"id":"W4391404746","doi":"10.3390/vehicles6010013","title":"Deep Learning-Based Stereopsis and Monocular Depth Estimation Techniques: A Review","year":2024,"lang":"en","type":"review","venue":"Vehicles","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Stereopsis; Monocular; Artificial intelligence; Computer science; Computer vision; Deep learning; Depth perception; Estimation; Geology; Psychology; Engineering; Neuroscience; Perception","score_opus":0.03402237195550226,"score_gpt":0.3576684199612038,"score_spread":0.3236460480057015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391404746","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.183969e-8,0.5942602,0.40488628,0.0001068901,0.000034886536,0.0003038915,5.5981457e-7,0.00031195395,0.00009527831],"genre_scores_gemma":[0.0000011470923,0.8170863,0.18236597,0.0003136083,0.000020736496,0.0000942155,0.00001022797,0.000029199695,0.00007861692],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99842644,0.0001736022,0.00042256882,0.0005693378,0.00020999776,0.00019808268],"domain_scores_gemma":[0.9990912,0.00010750108,0.00020980554,0.0004639666,0.000043574186,0.00008392197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003361729,0.00032190242,0.0008113385,0.00022894947,0.000090779366,0.00023729219,0.00047684857,0.00010091122,0.000004712567],"category_scores_gemma":[0.00010163095,0.00023945104,0.00022500375,0.0005818961,0.00003727771,0.0002831016,0.0002614083,0.00042483484,0.000113205046],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[9.967426e-8,0.0000056191957,2.3264822e-7,0.028373584,0.000011724932,0.000014237302,0.0000110418305,0.0000022903153,1.0725516e-7,0.000109629356,0.00022989586,0.97124153],"study_design_scores_gemma":[0.000021892833,0.000025268782,2.324255e-7,0.07467074,0.00019822016,0.00003163153,0.0000010731794,0.13461891,0.000002829866,0.00018848536,0.7900115,0.00022917429],"about_ca_topic_score_codex":0.0000023453656,"about_ca_topic_score_gemma":6.4543326e-7,"teacher_disagreement_score":0.97101235,"about_ca_system_score_codex":0.00005458092,"about_ca_system_score_gemma":0.00008542449,"threshold_uncertainty_score":0.976453},"labels":[],"label_agreement":null},{"id":"W4391692185","doi":"10.3390/vehicles6010016","title":"Modeling and Validation of a Passenger Car Tire Using Finite Element Analysis","year":2024,"lang":"en","type":"article","venue":"Vehicles","topic":"Mechanical Engineering and Vibrations Research","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Finite element method; Automotive engineering; Car model; Computer science; Engineering; Structural engineering","score_opus":0.034365305742602416,"score_gpt":0.28344401643517375,"score_spread":0.24907871069257134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391692185","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6371338,0.0005685035,0.36212167,0.000014711588,0.000022187121,0.00002817125,0.000006958515,0.00007694544,0.000027054852],"genre_scores_gemma":[0.99783665,0.00008645459,0.0020163145,0.0000010791531,0.000024654912,0.0000040658733,0.000008135665,0.000011006939,0.000011657896],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995912,0.000009934931,0.00012534436,0.00008342333,0.000103326594,0.000086776345],"domain_scores_gemma":[0.999823,0.000042974985,0.0000031993488,0.00008010031,0.000019207195,0.000031572312],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012125033,0.000051443832,0.00008825185,0.00020436714,0.0000189619,0.000036847363,0.00002978893,0.000031174804,0.000020497997],"category_scores_gemma":[0.000013941308,0.000048236478,0.00003681421,0.00040629852,0.000004967918,0.000061850355,0.000013855273,0.000066970315,0.000002145912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.211472e-7,0.000002354394,0.000022769875,0.00010939725,0.00012848733,9.686629e-7,0.000078513,0.9597302,0.03465622,0.00032559247,0.000004064575,0.004940881],"study_design_scores_gemma":[0.000025874675,0.0000062099357,0.000010090496,0.00003198465,0.00007544265,3.157221e-7,0.000024184175,0.9845419,0.015133339,0.00005004277,0.000051406107,0.00004919846],"about_ca_topic_score_codex":0.0000246325,"about_ca_topic_score_gemma":0.000002428986,"teacher_disagreement_score":0.36070284,"about_ca_system_score_codex":0.000016969316,"about_ca_system_score_gemma":0.0000071669974,"threshold_uncertainty_score":0.19670264},"labels":[],"label_agreement":null},{"id":"W4396797019","doi":"10.3390/vehicles6020040","title":"New Design of an Electrical Excavator and Its Path Generation for Energy Saving and Obstacle Avoidance","year":2024,"lang":"en","type":"article","venue":"Vehicles","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Excavator; Obstacle avoidance; Path (computing); Digging; Computer science; Obstacle; Actuator; Energy consumption; Energy (signal processing); Automotive engineering; Simulation; Engineering; Mathematics; Mechanical engineering; Artificial intelligence; Robot; Statistics; Electrical engineering; Mobile robot","score_opus":0.0234422885424767,"score_gpt":0.22485290965035307,"score_spread":0.20141062110787636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396797019","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6633254,0.012657318,0.32369518,0.000016822813,0.00009903891,0.000094138675,0.000004318583,0.00008543425,0.000022331282],"genre_scores_gemma":[0.99566734,0.00018885253,0.0038593449,0.000009124996,0.00017512435,0.000013697176,0.0000027371575,0.000016914872,0.00006687104],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961185,0.000019340625,0.00012312732,0.000101692975,0.000053060805,0.00009094208],"domain_scores_gemma":[0.9997744,0.00010299406,0.000009969395,0.000049734055,0.000010294942,0.000052590378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000103013925,0.000064133776,0.000097537115,0.00003347142,0.000024442475,0.0000376498,0.000027175583,0.000043901335,0.0000025774386],"category_scores_gemma":[0.000013720243,0.00005870058,0.000010686881,0.000063869236,0.0000044535946,0.00010116148,0.000004382823,0.00002585155,6.857708e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005005331,0.000005145298,0.00004935226,0.00027022182,0.000028858583,0.000002500297,0.00094538066,0.0060168155,0.7785551,0.0035383287,0.0014220941,0.20916122],"study_design_scores_gemma":[0.00009408283,0.000053916785,0.00017520858,0.00005325544,0.000008149895,0.000008870053,0.000015577265,0.9561417,0.042093214,0.00026513793,0.0010197525,0.00007109948],"about_ca_topic_score_codex":0.000018315224,"about_ca_topic_score_gemma":0.0000051934057,"teacher_disagreement_score":0.9501249,"about_ca_system_score_codex":0.000011057909,"about_ca_system_score_gemma":0.00001656411,"threshold_uncertainty_score":0.23937403},"labels":[],"label_agreement":null},{"id":"W4400285325","doi":"10.3390/vehicles6030054","title":"STRIDE-Based Cybersecurity Threat Modeling, Risk Assessment and Treatment of an In-Vehicle Infotainment System","year":2024,"lang":"en","type":"article","venue":"Vehicles","topic":"Information and Cyber Security","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"STRIDE; Computer security; Computer science; Threat model; Aeronautics; Internet privacy; Engineering","score_opus":0.015837714204590833,"score_gpt":0.2690548713308107,"score_spread":0.25321715712621984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400285325","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96514726,0.00043750415,0.032994412,0.00017606012,0.000114629394,0.00024408405,0.000021430842,0.0001796192,0.000684982],"genre_scores_gemma":[0.99569136,0.00008461113,0.0041264263,0.00003248943,0.000019575536,0.000028674545,0.000006578693,0.000005960711,0.000004302089],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99883693,0.000095987896,0.000347604,0.0002590687,0.00027138146,0.0001890116],"domain_scores_gemma":[0.9993869,0.00005271614,0.000065773165,0.0003555379,0.00004719612,0.000091891685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034498548,0.0001443558,0.00018727312,0.00017012305,0.00007764083,0.00020052944,0.00020007354,0.00006088237,0.0000039546603],"category_scores_gemma":[0.0000028123861,0.000118389726,0.000055314187,0.00024174394,0.000030654028,0.00067484815,0.0000571194,0.00008927498,0.0000063197585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005480231,0.0009819434,0.026562376,0.00053612434,0.000121965306,0.00011973131,0.0225905,0.030426234,0.0005372694,0.45462543,0.000046516583,0.4633971],"study_design_scores_gemma":[0.0006035066,0.0002566746,0.004473483,0.00007835078,0.000011610354,0.0000038246912,0.00046459996,0.9909561,0.0018837396,0.0008984738,0.00024541438,0.00012417532],"about_ca_topic_score_codex":0.00087877305,"about_ca_topic_score_gemma":0.00017190703,"teacher_disagreement_score":0.9605299,"about_ca_system_score_codex":0.00027484627,"about_ca_system_score_gemma":0.00015662127,"threshold_uncertainty_score":0.4827793},"labels":[],"label_agreement":null},{"id":"W4400975139","doi":"10.3390/vehicles6030059","title":"Impacts of a Toll Information Sign and Toll Lane Configuration on Queue Length and Collision Risk at a Toll Plaza with a High Percentage of Heavy Vehicles","year":2024,"lang":"en","type":"article","venue":"Vehicles","topic":"Traffic and Road Safety","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Toll; Electronic toll collection; Queue; Sign (mathematics); Collision; Transport engineering; Engineering; Computer science; Computer security; Mathematics; Computer network; Medicine","score_opus":0.0040150630802542366,"score_gpt":0.18593976254836211,"score_spread":0.18192469946810788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400975139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997972,0.00072696555,0.0002332674,0.000090578236,0.00005965795,0.0002533825,0.00018914834,0.00012765593,0.00034735698],"genre_scores_gemma":[0.99858147,0.0010670847,0.00023532886,0.000014263191,0.000022041226,0.000005937393,0.00003889781,0.000016031403,0.000018971012],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99927765,0.000029238625,0.0002642724,0.00011715102,0.00017668195,0.00013501932],"domain_scores_gemma":[0.9996078,0.00013484416,0.000057682806,0.00010954923,0.000024321947,0.00006582597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013256975,0.0001474849,0.00021508025,0.00012567533,0.00005605697,0.000037528644,0.000040069943,0.00009535477,0.000008322182],"category_scores_gemma":[0.00001038116,0.00011049588,0.000024865718,0.00008807198,0.00005798586,0.00031250308,0.000018125891,0.00011517904,0.000006223646],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009980052,0.0006032289,0.058169853,0.013068227,0.001434628,0.000117502605,0.06876401,0.22535935,0.1966801,0.018858964,0.012437834,0.39452624],"study_design_scores_gemma":[0.0057880688,0.0028265594,0.56219083,0.0024821716,0.00028384032,0.00009783781,0.0033189228,0.20150241,0.21054396,0.00021255961,0.009843185,0.00090964866],"about_ca_topic_score_codex":0.00038723098,"about_ca_topic_score_gemma":0.00019140933,"teacher_disagreement_score":0.504021,"about_ca_system_score_codex":0.000047832604,"about_ca_system_score_gemma":0.000022665856,"threshold_uncertainty_score":0.45058912},"labels":[],"label_agreement":null},{"id":"W4401581373","doi":"10.3390/vehicles6030066","title":"Urban Air Mobility for Last-Mile Transportation: A Review","year":2024,"lang":"en","type":"review","venue":"Vehicles","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École Nationale d'Administration Publique; Université du Québec à Montréal; Concordia University","funders":"","keywords":"Mile; Transport engineering; Aeronautics; Engineering; Geography","score_opus":0.03387257278252261,"score_gpt":0.3050888600472154,"score_spread":0.2712162872646928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401581373","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007762913,0.99730664,0.000063372194,0.000028755543,0.000308134,0.0010349386,0.00054906914,0.0004041084,0.0002972198],"genre_scores_gemma":[0.00001597044,0.9975963,0.00024177316,0.00004525915,0.00032336646,0.0007829546,0.00032923746,0.00009694053,0.00056819315],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987775,0.000017517365,0.0005571076,0.0002881359,0.0001178441,0.00024189112],"domain_scores_gemma":[0.9994049,0.0000741716,0.000050421375,0.0003448851,0.000032478012,0.000093108596],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020866902,0.00034995298,0.0009812623,0.00007049714,0.000053502492,0.000018865308,0.00021162577,0.00019925494,0.00008104621],"category_scores_gemma":[0.000009136928,0.00026299586,0.00054562464,0.00033476527,0.00002137488,0.00007369908,0.000008060647,0.00031928258,0.0001930312],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[3.7569325e-7,0.000007924377,8.5222655e-7,0.27240622,0.000053285286,0.0000023128873,0.00001920502,0.000011906043,2.5648637e-7,0.000041405372,0.10040394,0.6270523],"study_design_scores_gemma":[0.00003742442,0.000016223825,0.0000032995779,0.08350162,0.0006196999,0.0000046943687,0.0000017896839,0.0003334858,0.0000018811951,0.000018481529,0.915191,0.00027043023],"about_ca_topic_score_codex":0.0000017871499,"about_ca_topic_score_gemma":0.0000074130194,"teacher_disagreement_score":0.81478703,"about_ca_system_score_codex":0.00005936008,"about_ca_system_score_gemma":0.000078759665,"threshold_uncertainty_score":0.99998224},"labels":[],"label_agreement":null},{"id":"W4411154120","doi":"10.3390/vehicles7020057","title":"Navigating Uncertainty: Advanced Techniques in Pedestrian Intention Prediction for Autonomous Vehicles—A Comprehensive Review","year":2025,"lang":"en","type":"article","venue":"Vehicles","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Pedestrian; Computer science; Data science; Artificial intelligence; Human–computer interaction; Transport engineering; Engineering","score_opus":0.011890064908191071,"score_gpt":0.27879391451536395,"score_spread":0.2669038496071729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411154120","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9318576,0.03729251,0.018110305,0.0029776562,0.00055313174,0.0031040062,0.000097277305,0.004556903,0.0014506434],"genre_scores_gemma":[0.9876217,0.007118412,0.0040789917,0.00041012838,0.0000320827,0.0005648308,0.00008139409,0.000034628487,0.00005783413],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987128,0.000040278996,0.0005491733,0.00029592562,0.0000773228,0.00032453978],"domain_scores_gemma":[0.9993839,0.00013833727,0.000075449294,0.00027371917,0.00009507596,0.000033497567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026231233,0.0002176548,0.00037329574,0.00011178975,0.00012011184,0.000016558739,0.0002079212,0.0002410274,0.0000054545585],"category_scores_gemma":[0.00007800432,0.00023525218,0.00010499833,0.00043851652,0.000079399666,0.00017053804,0.000050802402,0.0004955983,0.000006247893],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004199804,0.00004560089,0.002470062,0.0023007207,0.00005407141,0.000004680589,0.00008966333,0.0027944797,0.013202975,0.0013769466,0.0008675848,0.9767512],"study_design_scores_gemma":[0.005883168,0.00075209345,0.049182605,0.0385563,0.00039026572,0.00004880959,0.001717905,0.37753868,0.1365775,0.030978186,0.35621342,0.0021610828],"about_ca_topic_score_codex":0.000038513175,"about_ca_topic_score_gemma":0.00004451858,"teacher_disagreement_score":0.9745901,"about_ca_system_score_codex":0.00026380343,"about_ca_system_score_gemma":0.000042605523,"threshold_uncertainty_score":0.9593306},"labels":[],"label_agreement":null},{"id":"W4415402430","doi":"10.3390/vehicles7040121","title":"A Systematic Review of Sustainable Ground-Based Last-Mile Delivery of Parcels: Insights from Operations Research","year":2025,"lang":"en","type":"review","venue":"Vehicles","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École Nationale d'Administration Publique; Université du Québec à Montréal; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Sustainability; Supply chain; Urban sustainability; Supply chain management; Systematic review; Sustainable transport","score_opus":0.04315415483972633,"score_gpt":0.3270911475486812,"score_spread":0.28393699270895484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415402430","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001614533,0.9964889,0.0003221118,0.000011102253,0.000047853588,0.002269496,0.00027412456,0.00007401439,0.00035091004],"genre_scores_gemma":[0.0009400768,0.99711955,0.00034595773,0.000022942993,0.000014096299,0.00059389195,0.0006879437,0.000026530759,0.0002490271],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9976785,0.00028268865,0.0013343,0.0001943565,0.00033005184,0.0001800874],"domain_scores_gemma":[0.9976906,0.0007960136,0.00009759307,0.0005703051,0.000807693,0.00003776934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004692641,0.00020571069,0.0015113346,0.0005345705,0.000074046024,0.000021693864,0.00030789615,0.00015712109,0.000048615497],"category_scores_gemma":[0.00026795384,0.00017518799,0.0002654171,0.0015808572,0.00007491096,0.00009218345,0.00002060099,0.00028636892,0.000012912223],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.7056707e-7,0.000047640642,3.127264e-7,0.9920728,0.00016873021,0.0000029272958,0.000089995425,0.00019684072,0.000007984906,0.0057140132,0.00021727425,0.0014809783],"study_design_scores_gemma":[0.000103548555,0.000019676047,0.000006375353,0.93690574,0.0009566626,2.77324e-7,0.00031862172,0.00028879862,0.000034534634,0.00008117252,0.061107103,0.00017749859],"about_ca_topic_score_codex":0.0002995103,"about_ca_topic_score_gemma":0.00021785413,"teacher_disagreement_score":0.06088983,"about_ca_system_score_codex":0.000115011695,"about_ca_system_score_gemma":0.0006381707,"threshold_uncertainty_score":0.71439594},"labels":[],"label_agreement":null}]}