{"meta":{"query_hash":"26dc4f00af43","filters":{"venue":"eTransportation"},"cohort_total":12,"direct_labels_cover":0,"predictions_cover":12,"exported":12,"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/26dc4f00af43","api":"https://metacan.xera.ac/api/v1/cohort?venue=eTransportation"},"results":[{"id":"W2965189910","doi":"10.1016/j.etran.2019.100009","title":"Comparing four model-order reduction techniques, applied to lithium-ion battery-cell internal electrochemical transfer functions","year":2019,"lang":"en","type":"article","venue":"eTransportation","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"General Motors of Canada; Advanced Research Projects Agency - Energy; General Motors Corporation; U.S. Department of Energy","keywords":"Electrochemistry; Reduction (mathematics); Battery (electricity); Lithium (medication); Lithium-ion battery; Ion; Model order reduction; Transfer function; Order (exchange); Materials science; Computer science; Electrode; Chemistry; Electrical engineering; Mathematics; Thermodynamics; Engineering; Physics; Algorithm; Power (physics); Medicine; Physical chemistry","score_opus":0.01387330600094852,"score_gpt":0.23392602994089207,"score_spread":0.22005272393994355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965189910","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":[0.4494683,0.000010218509,0.54654974,0.00006407512,0.00010173397,0.00033869964,0.000003627238,0.00061615935,0.0028474107],"genre_scores_gemma":[0.98723006,0.000027406353,0.011782271,0.00003920981,0.00005927043,0.00017184138,0.00012052117,0.000062255975,0.0005071603],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99873304,0.000007068122,0.0002979539,0.0003291037,0.00027190775,0.00036091224],"domain_scores_gemma":[0.99955225,0.000016213631,0.000015960524,0.00026973384,0.00007552906,0.000070332426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009325155,0.00019802217,0.00019828405,0.0002890143,0.00004501717,0.000024827887,0.00019109006,0.00017939263,0.00008997741],"category_scores_gemma":[0.0000038296453,0.00022402495,0.00005134635,0.00046342905,0.000021155618,0.00022478562,0.000008377862,0.00055976957,0.00014001307],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059147023,0.000023860017,0.00053082645,0.00007085093,0.00001307073,8.789534e-7,0.0001596939,0.12641923,0.8696254,0.00013831523,0.00021804977,0.0027406616],"study_design_scores_gemma":[0.0003242324,0.00007279102,0.0013473507,0.00003606335,0.000014293871,0.000005567451,0.00013262915,0.05133673,0.9454543,0.00026215936,0.0007141205,0.00029978028],"about_ca_topic_score_codex":0.000008024889,"about_ca_topic_score_gemma":0.000020787234,"teacher_disagreement_score":0.53776175,"about_ca_system_score_codex":0.00020128793,"about_ca_system_score_gemma":0.000017740822,"threshold_uncertainty_score":0.9135472},"labels":[],"label_agreement":null},{"id":"W3029498025","doi":"10.1016/j.etran.2020.100066","title":"Comparison of common DC and AC bus architectures for EV fast charging stations and impact on power quality","year":2020,"lang":"en","type":"article","venue":"eTransportation","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Harmonics; Transformer; Electrical engineering; Distribution transformer; Converters; AC power; Voltage; Engineering; Electronic engineering; Grid; Computer science","score_opus":0.04549840443829609,"score_gpt":0.3861737777564354,"score_spread":0.3406753733181393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029498025","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":[0.9537638,0.00014749699,0.045226,0.00023374625,0.00001563899,0.00024923857,0.0001830643,0.00013242556,0.000048584312],"genre_scores_gemma":[0.9983798,0.000017492759,0.0014696525,0.000022335837,0.0000060551506,0.000017873703,0.00006982764,0.00001558408,0.0000013417056],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.99943316,0.00001091088,0.00019808985,0.000118137184,0.000113963375,0.00012572734],"domain_scores_gemma":[0.9996428,0.00016877998,0.000039342885,0.00007818689,0.000027390302,0.00004349155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006204791,0.00009153389,0.00017276079,0.000076131684,0.000038960097,0.000009230411,0.00005083933,0.00004675616,0.000008284381],"category_scores_gemma":[0.000040498733,0.00008464878,0.000024469824,0.00011721066,0.000045784232,0.00004069855,0.0000021505039,0.00015073329,4.4137533e-7],"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":[0.00039431837,0.00008535633,0.2903424,0.0010633671,0.00013094375,0.0000025287807,0.018899104,0.4035078,0.2045714,0.0013827222,0.00012419105,0.07949589],"study_design_scores_gemma":[0.00047605892,0.00032605522,0.9048703,0.0000300338,0.000010356791,2.6731726e-7,0.0010536317,0.023914369,0.068570726,0.00053053966,0.00007424307,0.00014343433],"about_ca_topic_score_codex":0.000015044285,"about_ca_topic_score_gemma":0.00005725236,"teacher_disagreement_score":0.6145279,"about_ca_system_score_codex":0.000016852973,"about_ca_system_score_gemma":0.0000044599715,"threshold_uncertainty_score":0.34518772},"labels":[],"label_agreement":null},{"id":"W4200436037","doi":"10.1016/j.etran.2021.100152","title":"Recent progress and perspectives on designing high-performance thick electrodes for all-solid-state lithium batteries","year":2021,"lang":"en","type":"article","venue":"eTransportation","topic":"Advancements in Battery Materials","field":"Engineering","cited_by":117,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Research Chairs; Canada Foundation for Innovation; Ontario Research Foundation","keywords":"Electrode; Tortuosity; Materials science; Lithium (medication); Electrochemistry; Cathode; Nanotechnology; Battery (electricity); Electrochemical kinetics; Anode; Engineering physics; Composite material; Chemistry; Power (physics); Electrical engineering; Porosity; Engineering; Thermodynamics","score_opus":0.017848806663611622,"score_gpt":0.2628899657255491,"score_spread":0.2450411590619375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200436037","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":[0.9793942,0.00086244853,0.018611696,0.0002823966,0.0003252173,0.00026718513,0.000032128195,0.00016555506,0.000059196434],"genre_scores_gemma":[0.98549145,0.0026102152,0.011315108,0.000113213544,0.000069094385,0.00013583487,0.00013908325,0.000040865107,0.000085118736],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992223,0.00001767629,0.00020757609,0.00021856108,0.000115853014,0.00021806415],"domain_scores_gemma":[0.9996902,0.000043610624,0.000039376762,0.00010801174,0.000090891066,0.000027935163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000112934176,0.00014519446,0.00014721349,0.0000453428,0.00006918257,0.000049203325,0.000043236036,0.000042237592,0.000041067382],"category_scores_gemma":[0.000013361344,0.00015236868,0.000011899441,0.000078786354,0.000035967812,0.00026716484,0.000002504775,0.00007392389,0.0000037930138],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005122575,0.00014731458,0.009316885,0.0014923897,0.00034895027,0.000030987718,0.024468308,0.054531988,0.8528328,0.00247551,0.0005777262,0.053264868],"study_design_scores_gemma":[0.00044850304,0.00016494642,0.027667768,0.00010470194,0.000031196178,0.000002631218,0.0004024861,0.00057544786,0.96802074,0.0006323225,0.0016919675,0.00025726418],"about_ca_topic_score_codex":7.22657e-7,"about_ca_topic_score_gemma":0.0000072388825,"teacher_disagreement_score":0.11518795,"about_ca_system_score_codex":0.000052042935,"about_ca_system_score_gemma":0.00001349922,"threshold_uncertainty_score":0.6213414},"labels":[],"label_agreement":null},{"id":"W4384206980","doi":"10.1016/j.etran.2023.100264","title":"Molecular regulated polymer electrolytes for solid-state lithium metal batteries: Mechanisms and future prospects","year":2023,"lang":"en","type":"article","venue":"eTransportation","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National University's Basic Research Foundation of China; Fundamental Research Funds for the Central Universities; Huazhong University of Science and Technology; National Natural Science Foundation of China; Strategic Innovation Fund","keywords":"Materials science; Polymer; Electrolyte; Ionic conductivity; Nanotechnology; Agglomerate; Composite material; Chemistry; Electrode","score_opus":0.0043642385907211555,"score_gpt":0.2088146446537449,"score_spread":0.20445040606302375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384206980","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":[0.95291305,0.00033586312,0.04441105,0.00033833671,0.00029019688,0.00029453394,0.000064402004,0.0013343435,0.00001825285],"genre_scores_gemma":[0.9975993,0.00024413591,0.0016207428,0.00003882234,0.000044580727,0.00012017687,0.00021069124,0.000046498382,0.00007505902],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99935776,0.0000038354265,0.00016490165,0.00016709614,0.000078555255,0.00022787442],"domain_scores_gemma":[0.9998105,0.000011853804,0.000027866863,0.00010199349,0.000024433682,0.00002334809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005276082,0.00014111574,0.00015097439,0.00009763181,0.000049967868,0.000025691064,0.00005081765,0.000084247666,0.000011977951],"category_scores_gemma":[0.0000033693323,0.00013574964,0.00003163631,0.00020133375,0.000019949484,0.00014952508,0.0000031828522,0.000057179022,0.0000042625634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001829846,0.0000032171874,0.000019468991,0.00011908426,0.00004118602,0.000010522672,0.00021005017,0.0015505193,0.9912001,0.00450366,0.00003674954,0.002287135],"study_design_scores_gemma":[0.00023479339,0.00006610175,0.0024452927,0.0000110773135,0.00002351178,0.0000019333522,0.00009129722,0.0016046343,0.9805013,0.014355177,0.00049588113,0.00016900747],"about_ca_topic_score_codex":0.0000018215704,"about_ca_topic_score_gemma":0.000009143597,"teacher_disagreement_score":0.044686273,"about_ca_system_score_codex":0.000009958729,"about_ca_system_score_gemma":0.0000044023136,"threshold_uncertainty_score":0.5535709},"labels":[],"label_agreement":null},{"id":"W4384563758","doi":"10.1016/j.etran.2023.100265","title":"Improve multi-energy supply microgrid resilience using mobile hydrogen trucks based on transportation network","year":2023,"lang":"en","type":"article","venue":"eTransportation","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; Shenzhen University","keywords":"Microgrid; Resilience (materials science); Energy supply; Grid; Computer science; Energy storage; Truck; Engineering; Renewable energy; Automotive engineering; Energy (signal processing); Power (physics); Electrical engineering","score_opus":0.005929864281665327,"score_gpt":0.20247344155722188,"score_spread":0.19654357727555655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384563758","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":[0.7673361,0.00081863964,0.22880478,0.000026407924,0.0009042015,0.00057252916,0.0002222836,0.0012497524,0.0000653304],"genre_scores_gemma":[0.9926122,0.0003793035,0.004753799,0.000105446474,0.00017676133,0.00011643476,0.0017412874,0.00007306111,0.000041711082],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99862534,0.000024701403,0.00040659375,0.00031863435,0.00023142179,0.0003933001],"domain_scores_gemma":[0.99952847,0.000045863315,0.00007174904,0.00020665205,0.00006164689,0.000085633714],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015522896,0.00023474533,0.0001983207,0.00019082859,0.00012745043,0.00003157659,0.000117683274,0.00015015206,0.00006009568],"category_scores_gemma":[0.0000039349184,0.0002609465,0.00011391959,0.00078001514,0.000025796957,0.00021103278,6.755277e-7,0.00013224095,0.000022690383],"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":[0.00004126281,0.000021555017,0.0033248435,0.000039909584,0.00001781698,0.0000137345605,0.00020614035,0.94629157,0.03994612,0.000030293362,0.0001149977,0.009951732],"study_design_scores_gemma":[0.00085927243,0.000064436135,0.025229592,0.00004694717,0.00004806742,3.602112e-7,0.000037775466,0.9531316,0.0189125,0.000028976432,0.0013572742,0.00028318388],"about_ca_topic_score_codex":0.0001067662,"about_ca_topic_score_gemma":0.00046301426,"teacher_disagreement_score":0.22527611,"about_ca_system_score_codex":0.00006322476,"about_ca_system_score_gemma":0.000033744203,"threshold_uncertainty_score":0.99998426},"labels":[],"label_agreement":null},{"id":"W4386401674","doi":"10.1016/j.etran.2023.100280","title":"Local demand management of charging stations using vehicle-to-vehicle service: A welfare maximization-based soft actor-critic model","year":2023,"lang":"en","type":"article","venue":"eTransportation","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Electric System Operator","keywords":"Maximization; Electric vehicle; Demand response; Electrification; Computer science; Transformer; Dynamic pricing; Automotive engineering; Incentive; Operations research; Electricity; Engineering; Voltage; Microeconomics; Economics; Electrical engineering; Power (physics)","score_opus":0.011619902009264034,"score_gpt":0.23043063821057433,"score_spread":0.2188107362013103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386401674","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":[0.52173424,0.000026582507,0.47753683,0.00018395434,0.0000515827,0.00017188086,0.0000500107,0.00020309411,0.000041827006],"genre_scores_gemma":[0.9935648,0.000017070153,0.005906036,0.000112795075,0.000015544938,0.000022673637,0.00029785204,0.00004964781,0.0000136129875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998965,0.000010246095,0.00031468575,0.00018118453,0.00026331513,0.00026553596],"domain_scores_gemma":[0.9996025,0.00001880934,0.00003063415,0.00014932133,0.00011875969,0.00007999769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008591666,0.00014922039,0.00014706638,0.00023829247,0.000119738244,0.000019847299,0.000103972925,0.00007702872,0.000047377194],"category_scores_gemma":[0.0000023082769,0.0001725355,0.00004616177,0.0012429366,0.000012134545,0.00017858618,0.0000042606343,0.000109449546,0.000009917053],"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":[0.000010252813,0.000010515476,0.0010899729,0.0005327102,0.000035323123,0.0000063244192,0.00063534314,0.98480815,0.009119413,0.00086315064,0.000032140422,0.0028567268],"study_design_scores_gemma":[0.0004004961,0.000013961313,0.040073402,0.000094859926,0.000056270204,2.7265753e-7,0.00035549104,0.9541783,0.0043052537,0.0003161596,0.000037274076,0.00016826206],"about_ca_topic_score_codex":0.00003771388,"about_ca_topic_score_gemma":0.00006538705,"teacher_disagreement_score":0.47183052,"about_ca_system_score_codex":0.00007865628,"about_ca_system_score_gemma":0.000024706987,"threshold_uncertainty_score":0.7035793},"labels":[],"label_agreement":null},{"id":"W4387079282","doi":"10.1016/j.etran.2023.100289","title":"A renewable and hydrogen based multigeneration system designed for ferry applications","year":2023,"lang":"en","type":"article","venue":"eTransportation","topic":"Maritime Transport Emissions and Efficiency","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Exergy; Renewable energy; Energy carrier; Process engineering; Environmental science; Photovoltaic system; Fossil fuel; Hydrogen fuel; Proton exchange membrane fuel cell; Automotive engineering; Waste management; Engineering; Fuel cells; Electrical engineering; Chemical engineering","score_opus":0.012088302102487125,"score_gpt":0.22838945929114643,"score_spread":0.2163011571886593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387079282","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":[0.56423944,0.000025910453,0.4321267,0.00014147641,0.000024742294,0.0011119971,0.00004103082,0.00030282675,0.0019858554],"genre_scores_gemma":[0.9915271,0.000008315794,0.0066066184,0.000039243005,0.000020155861,0.0005288482,0.000488363,0.0000138734995,0.0007675051],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992438,0.000011533738,0.0001873648,0.00025282757,0.00014367979,0.00016082556],"domain_scores_gemma":[0.9997075,0.000040399227,0.00004351349,0.000121008,0.00001113459,0.000076450175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025494827,0.0000839952,0.000079808604,0.000051491497,0.00027190542,0.000014139519,0.00005945543,0.000058390633,0.00016241136],"category_scores_gemma":[0.000004479311,0.00008307236,0.000035345874,0.00035765773,0.000033976892,0.00009956668,0.0000022295958,0.00002594366,0.000052428466],"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":[0.00009275461,0.00016631972,0.06992816,0.00042208185,0.000016786513,0.0000077864215,0.0010444318,0.5158455,0.38746685,0.0013901389,0.0021896346,0.021429572],"study_design_scores_gemma":[0.0013729646,0.00011859142,0.24607296,0.000048027334,0.000089797366,0.0000017429874,0.0003666481,0.6987833,0.025510976,0.00031965188,0.026853142,0.00046223868],"about_ca_topic_score_codex":0.00039743495,"about_ca_topic_score_gemma":0.00035306026,"teacher_disagreement_score":0.4272876,"about_ca_system_score_codex":0.00003837923,"about_ca_system_score_gemma":0.000013656828,"threshold_uncertainty_score":0.33875924},"labels":[],"label_agreement":null},{"id":"W4390588173","doi":"10.1016/j.etran.2024.100311","title":"Solid-state electrolytes based on metal-organic frameworks for enabling high-performance lithium-metal batteries: Fundamentals, progress, and perspectives","year":2024,"lang":"en","type":"article","venue":"eTransportation","topic":"Advanced Battery Materials and Technologies","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nanotechnology; Materials science; Lithium metal; Energy density; Metal-organic framework; Lithium (medication); Fast ion conductor; Electrolyte; Engineering physics; Engineering; Chemistry; Electrode","score_opus":0.007530702851299886,"score_gpt":0.23788872613278134,"score_spread":0.23035802328148144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390588173","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":[0.93942934,0.0026088033,0.056019973,0.00029011883,0.00031538523,0.00030850072,0.00006765108,0.00095000846,0.000010197608],"genre_scores_gemma":[0.995322,0.0007766306,0.0034528761,0.000042308522,0.00006835254,0.00015270714,0.00010072421,0.000059082246,0.000025338959],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991638,0.000005979104,0.00020796324,0.0002669152,0.00010967786,0.00024565138],"domain_scores_gemma":[0.9997392,0.00006558199,0.000027204898,0.00011588707,0.000027792146,0.000024302735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000091876194,0.00019912075,0.00018757167,0.00014686017,0.00008387914,0.00010840655,0.00006509988,0.00012909736,0.00004938819],"category_scores_gemma":[0.000010220966,0.00018169773,0.00003753441,0.00017935036,0.00006948598,0.0003573306,0.0000031137547,0.00022414954,0.000005054162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002998543,0.000118163916,0.0015446065,0.003687946,0.00045015683,0.000033207965,0.003934084,0.05147775,0.8685305,0.0035015375,0.00008954125,0.06633263],"study_design_scores_gemma":[0.00046833447,0.00052067626,0.011636387,0.00039666425,0.0000972763,0.0000028781024,0.0005192051,0.05113993,0.9310962,0.0025082047,0.001118425,0.0004958404],"about_ca_topic_score_codex":0.000001610278,"about_ca_topic_score_gemma":0.000006480913,"teacher_disagreement_score":0.06583679,"about_ca_system_score_codex":0.000049802402,"about_ca_system_score_gemma":0.000012829944,"threshold_uncertainty_score":0.7409418},"labels":[],"label_agreement":null},{"id":"W4402737902","doi":"10.1016/j.etran.2024.100364","title":"Battery engineering safety technologies (BEST): M5 framework of mechanisms, modes, metrics, modeling, and mitigation","year":2024,"lang":"en","type":"article","venue":"eTransportation","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Battery (electricity); Computer science; Engineering; Systems engineering; Reliability engineering","score_opus":0.010219234506590754,"score_gpt":0.2450317890923634,"score_spread":0.23481255458577263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402737902","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":[0.10099151,0.0047333892,0.89181554,0.000107450105,0.00015722215,0.00016917664,0.00003854885,0.0019326848,0.000054481952],"genre_scores_gemma":[0.91258657,0.0028615184,0.08440787,0.000003441779,0.000012187729,0.000031734013,0.00004379139,0.000044565248,0.000008338448],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989807,0.0000048726465,0.0003154881,0.00023312475,0.00024100413,0.00022480245],"domain_scores_gemma":[0.9995766,0.00011868801,0.000018695671,0.0002126752,0.000048893537,0.00002440925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013831003,0.00016431957,0.00017676761,0.00062593387,0.00002911876,0.000028987135,0.00014310036,0.00026707264,0.000012651411],"category_scores_gemma":[0.00010301046,0.00017527262,0.000040367097,0.0008024498,0.00003890147,0.00033109452,0.000014714755,0.00043499618,0.0000053356616],"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":[0.000005911966,0.000008659715,0.00014071898,0.0007740433,0.00005952436,0.000014522122,0.00017472214,0.8687434,0.036288038,0.034162965,0.000015579722,0.059611905],"study_design_scores_gemma":[0.000063243555,0.000031862073,0.00012288752,0.00026929978,0.000020156605,0.0000025459306,0.00032109764,0.9183926,0.058785908,0.021659402,0.00015593591,0.00017508055],"about_ca_topic_score_codex":0.0000083634395,"about_ca_topic_score_gemma":0.0000056459894,"teacher_disagreement_score":0.811595,"about_ca_system_score_codex":0.00007853947,"about_ca_system_score_gemma":0.000011664413,"threshold_uncertainty_score":0.714741},"labels":[],"label_agreement":null},{"id":"W4406080131","doi":"10.1016/j.etran.2024.100390","title":"Advances and perspectives in fire safety of lithium-ion battery energy storage systems","year":2025,"lang":"en","type":"article","venue":"eTransportation","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":97,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; Youth Innovation Promotion Association of the Chinese Academy of Sciences; China Scholarship Council; Concordia University; National Natural Science Foundation of China","keywords":"Energy storage; Battery (electricity); Lithium (medication); Lithium-ion battery; Computer science; Systems engineering; Materials science; Environmental science; Engineering; Medicine; Physics; Psychiatry","score_opus":0.010200803715483603,"score_gpt":0.24886723488957618,"score_spread":0.23866643117409259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406080131","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":[0.79927075,0.02544629,0.17151138,0.00016187696,0.000274996,0.00022117457,0.000028822604,0.0002916097,0.00279311],"genre_scores_gemma":[0.99318534,0.006424273,0.00024027767,0.000003723178,0.00000774958,0.000024485476,0.000015691812,0.00000886524,0.00008959705],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9994465,0.000013817377,0.00019699355,0.00013261719,0.00009497538,0.000115106035],"domain_scores_gemma":[0.99975735,0.000065115884,0.000022229648,0.00011088773,0.000032990527,0.0000113996275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000068073394,0.00007863434,0.00013394284,0.00019964794,0.000018731074,0.000005964202,0.00006799546,0.000072363444,0.000005798344],"category_scores_gemma":[0.000017284885,0.00008263523,0.0000145817185,0.00033328473,0.000050582992,0.00021896505,0.0000046563528,0.000113941875,3.0142587e-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":[0.00014383523,0.000072741605,0.055717442,0.0024876797,0.000060336955,0.000033601562,0.0031673617,0.7325528,0.02693069,0.017330281,0.00011928117,0.16138394],"study_design_scores_gemma":[0.002080429,0.00019101199,0.7558543,0.0015464908,0.000030628453,0.0000037704458,0.020628694,0.15124586,0.043805502,0.0037201585,0.020142047,0.0007510865],"about_ca_topic_score_codex":0.000049033155,"about_ca_topic_score_gemma":0.00012566458,"teacher_disagreement_score":0.7001369,"about_ca_system_score_codex":0.00007368962,"about_ca_system_score_gemma":0.0000085384345,"threshold_uncertainty_score":0.3369767},"labels":[],"label_agreement":null},{"id":"W4408514302","doi":"10.1016/j.etran.2025.100417","title":"A survey of machine learning applications in advanced transportation systems: Trends, techniques, and future directions","year":2025,"lang":"en","type":"article","venue":"eTransportation","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":15,"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 Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Data science","score_opus":0.004587560993007536,"score_gpt":0.22606628660996483,"score_spread":0.2214787256169573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408514302","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":[0.3928141,0.031173725,0.53727525,0.0002533985,0.0010264968,0.0031095638,0.0008430133,0.015554734,0.017949756],"genre_scores_gemma":[0.9937932,0.0043705427,0.00061453955,0.000003031528,0.000010926354,0.00022333697,0.00088836346,0.000011781444,0.00008426666],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99941796,0.000023343675,0.00028819547,0.0001248626,0.00006890026,0.00007671549],"domain_scores_gemma":[0.9997981,0.000025638345,0.000040201994,0.00007965462,0.00003891433,0.000017466404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014603538,0.000092717724,0.00013402815,0.0004507961,0.00003525164,0.000007261119,0.000041491054,0.00007338931,0.0000032660741],"category_scores_gemma":[0.0000020013351,0.00010363565,0.00002001608,0.0008185459,0.000015004508,0.00012000733,7.126662e-7,0.00012934912,1.2679108e-7],"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":[0.000044813416,0.000115680356,0.1873079,0.0008844865,0.00008342611,0.0000027231285,0.001186715,0.01866965,0.0011347829,0.014221946,0.00037262318,0.7759753],"study_design_scores_gemma":[0.00025221438,0.000018890123,0.9034093,0.000058104295,0.00002473812,1.658949e-7,0.00017029284,0.00883332,0.00041501026,0.000013272562,0.08670755,0.000097130105],"about_ca_topic_score_codex":0.0004917784,"about_ca_topic_score_gemma":0.0048739864,"teacher_disagreement_score":0.77587813,"about_ca_system_score_codex":0.00002680329,"about_ca_system_score_gemma":0.000006638003,"threshold_uncertainty_score":0.42261392},"labels":[],"label_agreement":null},{"id":"W4415219652","doi":"10.1016/j.etran.2025.100500","title":"Machine learning-assisted optimization of NbTa alloy coating thickness via DC magnetron sputtering for SS316L bipolar plates in PEMFCs","year":2025,"lang":"en","type":"article","venue":"eTransportation","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":5,"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 Waterloo; Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Research Chairs","keywords":"Proton exchange membrane fuel cell; Coating; Corrosion; Alloy; Sputter deposition; Titanium alloy; Physical vapor deposition","score_opus":0.0059809580544768655,"score_gpt":0.20763543738067924,"score_spread":0.20165447932620237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415219652","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":[0.75485903,0.004917605,0.23693198,0.00007270614,0.0012040837,0.00072252064,0.00005031431,0.00033893852,0.0009028205],"genre_scores_gemma":[0.99043995,0.00086341,0.008022489,0.000009238878,0.000020623253,0.000024788034,0.00048799004,0.000031869746,0.000099628385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991574,0.000021288099,0.00043635973,0.0001413757,0.00008603212,0.00015752974],"domain_scores_gemma":[0.9997045,0.0000702712,0.00008107304,0.000075793214,0.00004973039,0.000018634522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021831329,0.00013199003,0.00021074036,0.00020169311,0.000046156583,0.000017830927,0.00006490478,0.00016175199,0.000050032097],"category_scores_gemma":[0.000021728289,0.00013930723,0.000045489563,0.00026535243,0.000014011846,0.00012094924,0.0000033381732,0.00014356326,9.873283e-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":[0.000036367117,0.000016891117,0.0032659734,0.0013558608,0.000023131519,0.0000015501508,0.0003471158,0.8347691,0.15921415,0.000046740868,0.0000044246412,0.0009186578],"study_design_scores_gemma":[0.0011209054,0.00006414785,0.013320546,0.0002930058,0.00006197661,9.106806e-7,0.00007536448,0.9320282,0.052096676,0.00008626543,0.00065421534,0.00019782156],"about_ca_topic_score_codex":0.00018861616,"about_ca_topic_score_gemma":0.0001717083,"teacher_disagreement_score":0.23558094,"about_ca_system_score_codex":0.000035632573,"about_ca_system_score_gemma":0.000011808024,"threshold_uncertainty_score":0.5680784},"labels":[],"label_agreement":null}]}