{"meta":{"query_hash":"f6c38e30195b","filters":{"venue":"IEEE Transactions on Sustainable Energy"},"cohort_total":149,"direct_labels_cover":0,"predictions_cover":149,"exported":149,"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/f6c38e30195b","api":"https://metacan.xera.ac/api/v1/cohort?venue=IEEE+Transactions+on+Sustainable+Energy"},"results":[{"id":"W1491033459","doi":"10.1109/tste.2015.2436333","title":"Real-Time HIL Implementation of Sliding Mode Control for Standalone System Based on PV Array Without Using Dumpload","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":80,"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 de Technologie Supérieure","funders":"","keywords":"Photovoltaic system; Control theory (sociology); Robustness (evolution); Voltage; Voltage source; Sliding mode control; Engineering; Computer science; Energy storage; Control engineering; Power (physics); Control (management); Electrical engineering","score_opus":0.018938403390366034,"score_gpt":0.2874849584660197,"score_spread":0.26854655507565367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1491033459","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":[0.010150587,0.0000102631375,0.98544455,0.00003694838,0.00021732027,0.00088413316,0.00016905187,0.0005692102,0.002517959],"genre_scores_gemma":[0.98797226,0.0000068278055,0.009565494,0.00006118161,0.00006678651,0.00070351834,0.00003670363,0.00012397108,0.0014632592],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9973043,0.00027259442,0.000782103,0.00047003024,0.0005829306,0.00058800954],"domain_scores_gemma":[0.9975262,0.0002173382,0.00042471083,0.0005505043,0.0010793065,0.00020190947],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00068995834,0.00035952355,0.0006237175,0.0008294486,0.00029365165,0.00006306658,0.0002072738,0.0001986645,0.000054392916],"category_scores_gemma":[0.000021101156,0.00037350156,0.00020152389,0.0006368459,0.000040278403,0.00033562517,0.000001398816,0.00009717796,0.0000025442312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086318236,0.00013828013,0.000011066562,0.00020644335,0.00011151433,0.0000068666636,0.00023466218,0.92709917,0.06254651,0.008157517,0.0001424461,0.00048233298],"study_design_scores_gemma":[0.003627637,0.0005048088,7.8146974e-7,0.00012630568,0.00013107846,0.0000058791697,0.004071624,0.4263592,0.56376934,0.00019719882,0.00090662384,0.00029951613],"about_ca_topic_score_codex":0.021508403,"about_ca_topic_score_gemma":0.00025543498,"teacher_disagreement_score":0.97782165,"about_ca_system_score_codex":0.001968334,"about_ca_system_score_gemma":0.00059401325,"threshold_uncertainty_score":0.9998717},"labels":[],"label_agreement":null},{"id":"W1515633367","doi":"10.1109/tste.2015.2460014","title":"Impact of Second-Generation Plug-In Battery Electric Vehicles on the Aging of Distribution Transformers Considering TOU Prices","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":44,"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":"Transformer; Distribution transformer; Automotive engineering; Electrical engineering; Electric vehicle; Engineering; Computer science; Voltage; Power (physics); Physics","score_opus":0.010400427352863782,"score_gpt":0.21465048984002438,"score_spread":0.2042500624871606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1515633367","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":[0.82734174,0.00017889049,0.17159712,0.00004377339,0.00009227063,0.000121753204,0.000019552535,0.000046809557,0.0005580747],"genre_scores_gemma":[0.9996402,0.00009287288,0.000025767238,0.000021248501,0.00003448987,0.000028171007,0.000009599227,0.000025092593,0.00012253886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989061,0.000048916838,0.0003333859,0.00015062094,0.00019682884,0.00036415536],"domain_scores_gemma":[0.9994928,0.000106386724,0.000062348554,0.00015741862,0.000117073796,0.000063939435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022433372,0.00018518222,0.00022448596,0.00026366243,0.000075626755,0.000023349827,0.0001016879,0.00010345111,0.000048472793],"category_scores_gemma":[0.000008372491,0.0001468151,0.00012326564,0.0007578877,0.000030026273,0.00023170661,6.7631976e-7,0.0002326216,5.270805e-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":[0.000053043183,0.000059905098,0.000068209054,0.0000666201,0.000086881366,0.0000054944035,0.00025159508,0.9355604,0.04657535,0.00070915377,0.00041160692,0.01615176],"study_design_scores_gemma":[0.0008840187,0.00053942535,0.0013469633,0.000046164005,0.00003600766,0.000012908095,0.0007884669,0.15029664,0.8446514,0.00052291795,0.000597423,0.00027765296],"about_ca_topic_score_codex":0.00049298996,"about_ca_topic_score_gemma":0.00013850947,"teacher_disagreement_score":0.79807603,"about_ca_system_score_codex":0.00048432805,"about_ca_system_score_gemma":0.00014020383,"threshold_uncertainty_score":0.5986946},"labels":[],"label_agreement":null},{"id":"W1517262872","doi":"10.1109/tste.2015.2455554","title":"Probabilistic Impact of Transportation Electrification on the Loss-of-Life of Distribution Transformers in the Presence of Rooftop Solar Photovoltaic","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":80,"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":"Photovoltaic system; Transformer; Environmental science; Rooftop photovoltaic power station; Automotive engineering; Electrification; Solar irradiance; Distribution transformer; Electrical engineering; Engineering; Electricity; Voltage; Meteorology; Maximum power point tracking; Inverter; Physics","score_opus":0.009515713560029317,"score_gpt":0.22038200258831725,"score_spread":0.21086628902828794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1517262872","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":[0.7310753,0.00010797063,0.26824304,0.00003295544,0.00003108988,0.00029746248,0.000085083295,0.000014728723,0.000112361326],"genre_scores_gemma":[0.99974805,0.00011040197,0.000014929339,0.000004910514,0.0000071589434,0.00005353059,0.000026409605,0.00001394494,0.000020677646],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988247,0.00008462341,0.00045418853,0.000114598566,0.00029535554,0.00022651516],"domain_scores_gemma":[0.99916834,0.00019883236,0.000120312725,0.00022340255,0.00024937443,0.00003976281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037778873,0.00014009439,0.00022705615,0.0001365708,0.000037428807,0.0000052752384,0.00018299157,0.00010014987,0.000013791991],"category_scores_gemma":[0.000029954414,0.000092814254,0.00013908195,0.0009780354,0.00008739194,0.00013664186,1.02171896e-7,0.00019405717,1.0726799e-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":[0.00028655474,0.0001741972,0.00008792044,0.00021629836,0.00006154028,9.599668e-7,0.0010981592,0.9657361,0.025503797,0.0031137986,0.00008743712,0.0036332263],"study_design_scores_gemma":[0.0010301938,0.0013722654,0.0043639652,0.00008369137,0.000099284676,0.0000029242185,0.0027133327,0.087690346,0.898826,0.0033946258,0.00021202522,0.00021135443],"about_ca_topic_score_codex":0.0014368586,"about_ca_topic_score_gemma":0.00012426851,"teacher_disagreement_score":0.87804574,"about_ca_system_score_codex":0.00017165893,"about_ca_system_score_gemma":0.00022131127,"threshold_uncertainty_score":0.37848553},"labels":[],"label_agreement":null},{"id":"W1550958126","doi":"10.1109/tste.2015.2456752","title":"Optimal Design of Solar PV Farms With Storage","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":76,"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":"Energy storage; Mathematical optimization; Solar power; Provisioning; Computer science; Solar energy; Context (archaeology); Distributed generation; Photovoltaic system; Thermal energy storage; Power (physics); Reliability engineering; Renewable energy; Engineering; Electrical engineering; Mathematics; Telecommunications","score_opus":0.018489215830228337,"score_gpt":0.21892815333797772,"score_spread":0.20043893750774938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550958126","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":[0.0108436,0.00017644996,0.97647464,0.00006370385,0.00049176416,0.00020882765,0.0000091598295,0.0002933943,0.01143847],"genre_scores_gemma":[0.92877054,0.00003131283,0.0035886827,0.00007439147,0.00012764598,0.00021769159,0.000007630938,0.00014375953,0.06703836],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9967968,0.00035922846,0.00056226534,0.0005897289,0.00076514244,0.0009268733],"domain_scores_gemma":[0.9976106,0.00015652174,0.00022229449,0.0008710502,0.00070298696,0.0004365254],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005685966,0.00047229783,0.0006096247,0.0005623676,0.00023200404,0.00006996655,0.00044259065,0.0002319018,0.00016773127],"category_scores_gemma":[0.000019462499,0.0004089497,0.00015805865,0.0010220734,0.00018966867,0.00045355837,0.000004572709,0.00025739527,0.000026780359],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006952818,0.00034077742,0.000002042744,0.00005290229,0.00022985588,0.00033279072,0.0003901278,0.9882937,0.0010279216,0.004990708,0.0007874744,0.0028564378],"study_design_scores_gemma":[0.007652965,0.0040235654,0.000004936134,0.00017467365,0.000333756,0.00036057315,0.018613169,0.13882345,0.5775677,0.00083516486,0.24970423,0.0019058008],"about_ca_topic_score_codex":0.020975912,"about_ca_topic_score_gemma":0.00051501143,"teacher_disagreement_score":0.97288597,"about_ca_system_score_codex":0.0006014779,"about_ca_system_score_gemma":0.0008093575,"threshold_uncertainty_score":0.9998362},"labels":[],"label_agreement":null},{"id":"W1975265573","doi":"10.1109/tste.2013.2284573","title":"A Comprehensive Study of the Impacts of PHEVs on Residential Distribution Networks","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":181,"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":"Monte Carlo method; Probabilistic logic; Benchmark (surveying); Computer science; Process (computing); Probability distribution; Reliability engineering; Engineering; Artificial intelligence; Mathematics; Statistics","score_opus":0.003417142570380995,"score_gpt":0.19063264789744197,"score_spread":0.18721550532706097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975265573","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":[0.6638632,0.00003929148,0.3353271,0.000015562917,0.00025913308,0.00014483916,0.000007791419,0.000047529065,0.00029561803],"genre_scores_gemma":[0.9996511,0.000028676766,0.0000061115998,0.000021976699,0.000049686038,0.000014627433,0.0000025656382,0.000020237367,0.00020506262],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907327,0.00007873649,0.0002539792,0.00012226871,0.00020636925,0.0002653791],"domain_scores_gemma":[0.9993463,0.00008878926,0.00006751277,0.00031016849,0.00014271964,0.00004451624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057640522,0.00014182662,0.00021314542,0.00007554238,0.00012561069,0.000013326902,0.00015181785,0.00009021791,0.000020147641],"category_scores_gemma":[0.0000048670627,0.00011007678,0.00009498256,0.00048447537,0.000032639964,0.0000701534,0.0000017579412,0.00021272343,3.191733e-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":[0.000069570284,0.00012547997,0.000015780051,0.000046508932,0.00006939939,0.0000014387633,0.00012384677,0.9922851,0.0011436585,0.0009641168,0.0004898276,0.0046653156],"study_design_scores_gemma":[0.005447972,0.004965501,0.018970652,0.00018995909,0.0003665169,0.000019322739,0.007034472,0.538122,0.41131786,0.0018553272,0.010842942,0.0008675002],"about_ca_topic_score_codex":0.0007817369,"about_ca_topic_score_gemma":0.00010337661,"teacher_disagreement_score":0.45416307,"about_ca_system_score_codex":0.00011127929,"about_ca_system_score_gemma":0.000022601962,"threshold_uncertainty_score":0.44888008},"labels":[],"label_agreement":null},{"id":"W1978813851","doi":"10.1109/tste.2015.2410760","title":"Flexibility Envelopes for Power System Operational Planning","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Power System Optimization","field":"Engineering","cited_by":220,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Flexibility (engineering); Computer science; Electric power system; Power (physics); Systems engineering; Reliability engineering; Engineering","score_opus":0.017049234759853663,"score_gpt":0.23245409634055342,"score_spread":0.21540486158069977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978813851","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":[0.0020065543,0.00021166219,0.98702013,0.000034738074,0.0008589654,0.00028079582,0.000015377509,0.0006522547,0.008919503],"genre_scores_gemma":[0.9917296,0.0000034915695,0.0022258314,0.00003871346,0.000062896426,0.00038386523,0.000014357839,0.000056219855,0.0054850047],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987641,0.000041399362,0.00030295792,0.00024890873,0.00022834388,0.00041428301],"domain_scores_gemma":[0.999136,0.000086026885,0.000029899213,0.0002479919,0.0003529269,0.00014719063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003164195,0.00019654991,0.00020385487,0.00023267086,0.00018896752,0.000080137004,0.00013185505,0.00013029948,0.000018117256],"category_scores_gemma":[0.000013255211,0.00020721687,0.000071358896,0.0003792061,0.000016657603,0.0003350046,8.3592306e-7,0.00010198895,0.00000843482],"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":[0.000049053382,0.00003123326,0.0000021942876,0.00010199915,0.00005117481,0.000009592416,0.00027457438,0.9906989,0.00007721558,0.0059914743,0.0022911676,0.00042142597],"study_design_scores_gemma":[0.0016677779,0.00032929148,0.0000073624133,0.00007842394,0.000051128965,0.000055357443,0.004820285,0.8910148,0.03825832,0.00029974667,0.06276646,0.00065101543],"about_ca_topic_score_codex":0.000089514644,"about_ca_topic_score_gemma":0.00000771908,"teacher_disagreement_score":0.9897231,"about_ca_system_score_codex":0.00095095206,"about_ca_system_score_gemma":0.00018771683,"threshold_uncertainty_score":0.8450059},"labels":[],"label_agreement":null},{"id":"W1987271412","doi":"10.1109/tste.2012.2208206","title":"Long-Term Statistical Assessment of Frequency Regulation Reserves Policies in the Québec Interconnection","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Integrated Energy Systems Optimization","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":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Automatic Generation Control; Wind power; Interconnection; Automatic frequency control; Term (time); Electric power system; Grid; Call for bids; Computer science; Reliability engineering; Power (physics); Engineering; Procurement; Electrical engineering; Telecommunications; Mathematics; Economics","score_opus":0.009984001448414262,"score_gpt":0.25336329752624603,"score_spread":0.24337929607783176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987271412","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":[0.13745803,0.000091978145,0.8570925,0.00006220532,0.00033733677,0.00012078667,0.0000070201045,0.00009801296,0.004732124],"genre_scores_gemma":[0.9983059,0.000044300148,0.0004962622,0.000017106311,0.00006173955,0.00014140754,0.000018294373,0.00003368021,0.0008813223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987539,0.00016361412,0.00038042746,0.000119638215,0.0002185733,0.0003638683],"domain_scores_gemma":[0.9993407,0.00016358227,0.0000525829,0.00026809153,0.00012968322,0.000045335397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032626637,0.00016410544,0.00017267151,0.00038025252,0.0000996977,0.0000341708,0.00013673493,0.00012045554,0.000114403694],"category_scores_gemma":[0.000012020919,0.00013673012,0.000052262403,0.00051951315,0.000049713173,0.00047209114,9.625754e-7,0.00019309894,0.0000017334936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013594021,0.00014777861,0.0012217782,0.00011792313,0.00004376078,0.000003994043,0.0009997757,0.94398946,0.0011900285,0.050823823,0.000111051,0.0013370643],"study_design_scores_gemma":[0.0031772016,0.0011674868,0.29661945,0.0006964668,0.0003496029,0.00017667656,0.031117782,0.515121,0.14379987,0.0027760586,0.0027991855,0.0021992233],"about_ca_topic_score_codex":0.03188138,"about_ca_topic_score_gemma":0.013834517,"teacher_disagreement_score":0.8608479,"about_ca_system_score_codex":0.00066703715,"about_ca_system_score_gemma":0.0000906246,"threshold_uncertainty_score":0.9745654},"labels":[],"label_agreement":null},{"id":"W1995369359","doi":"10.1109/tste.2012.2234154","title":"Renewable Energy Alternatives for Remote Communities in Northern Ontario, Canada","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":182,"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":"Renewable energy; Environmental economics; Electricity; Market penetration; Diesel fuel; Capital cost; Environmental science; Computer science; Engineering; Automotive engineering; Electrical engineering; Economics","score_opus":0.01042210763305816,"score_gpt":0.20546476677745304,"score_spread":0.1950426591443949,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995369359","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":[0.124468684,0.00046839422,0.77253366,0.0006321396,0.0026742332,0.0008170148,0.000047074052,0.0004467665,0.09791206],"genre_scores_gemma":[0.7435283,0.00005098006,0.00031135994,0.00039802532,0.000115602896,0.0006613398,0.000051201576,0.00012534739,0.25475785],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962581,0.00030530948,0.00084492646,0.0005807078,0.0005381982,0.0014728003],"domain_scores_gemma":[0.997345,0.00051165343,0.00021944533,0.0010383517,0.0005764205,0.0003091592],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026783725,0.00060329516,0.00069107267,0.00060520903,0.0005999563,0.00017081438,0.0007237434,0.00022842432,0.00088822126],"category_scores_gemma":[0.000015387246,0.00062068016,0.00021916468,0.0006330909,0.00012135988,0.0005590521,0.00000996451,0.00030577838,0.000007798471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010949845,0.00016501767,0.0001054806,0.00005993252,0.00017231905,0.00007388396,0.0005901263,0.98195827,0.00019430187,0.0028108128,0.0033074904,0.010452853],"study_design_scores_gemma":[0.0027111406,0.00033470115,0.000090315785,0.00016496268,0.000053128613,0.000041594598,0.01523807,0.027041331,0.046268575,0.008537445,0.8981653,0.0013534545],"about_ca_topic_score_codex":0.99996173,"about_ca_topic_score_gemma":0.9999871,"teacher_disagreement_score":0.95491695,"about_ca_system_score_codex":0.0042076604,"about_ca_system_score_gemma":0.0022360175,"threshold_uncertainty_score":0.99962443},"labels":[],"label_agreement":null},{"id":"W2002847944","doi":"10.1109/tste.2012.2190999","title":"A Simplified Risk-Based Method for Short-Term Wind Power Commitment","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":65,"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 Saskatchewan","funders":"","keywords":"Wind power; Electric power system; Wind power forecasting; Reliability engineering; Wind speed; Power system simulation; Renewable energy; Probabilistic logic; Computer science; Engineering; Power (physics); Meteorology; Electrical engineering","score_opus":0.010805948250849882,"score_gpt":0.24738771967049944,"score_spread":0.23658177141964956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002847944","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":[0.005083701,0.00023183668,0.9904716,0.000058351627,0.0011269565,0.00044804098,0.00006729106,0.00035783037,0.0021543675],"genre_scores_gemma":[0.9930213,0.000026955266,0.00364831,0.00012482738,0.00006708237,0.0004621047,0.000006446975,0.000069598565,0.0025733616],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99830574,0.000087726396,0.0003179867,0.0002464186,0.00017304531,0.0008690956],"domain_scores_gemma":[0.9988024,0.00031486616,0.00003618342,0.0004984197,0.0001243493,0.00022373469],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00053473335,0.00027928475,0.00030563292,0.00017987446,0.00025338514,0.000039096813,0.00017266115,0.00016970222,0.000092189344],"category_scores_gemma":[0.000011799608,0.00027185635,0.00023384302,0.00024050089,0.00003329043,0.00023067229,0.0000012731507,0.00019721198,0.000008415722],"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":[0.00021290957,0.0005629884,0.00004816899,0.00044212866,0.00026799235,0.000009481013,0.0005387763,0.9763543,0.00120305,0.0047599003,0.0030740644,0.012526269],"study_design_scores_gemma":[0.0026467755,0.0006024564,0.00029058036,0.00010333339,0.0003298143,0.000020980484,0.0024894148,0.09929492,0.19193307,0.00093531015,0.69997084,0.001382501],"about_ca_topic_score_codex":0.00018083709,"about_ca_topic_score_gemma":0.000041490533,"teacher_disagreement_score":0.9879376,"about_ca_system_score_codex":0.00045726178,"about_ca_system_score_gemma":0.00005267364,"threshold_uncertainty_score":0.99997336},"labels":[],"label_agreement":null},{"id":"W2010137173","doi":"10.1109/tste.2013.2252209","title":"Type-III Wind Power Plant Harmonic Emissions: Field Measurements and Aggregation Guidelines for Adequate Representation of Harmonics","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Harmonics; Wind power; Voltage; Harmonic; Transient (computer programming); Representation (politics); Harmonic analysis; Electronic engineering; Interconnection; Time domain; Power (physics); Field (mathematics); Control theory (sociology); Electric power system; Computer science; Engineering; Electrical engineering; Physics; Mathematics; Telecommunications; Acoustics","score_opus":0.04140726350912537,"score_gpt":0.2674451014413629,"score_spread":0.22603783793223753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010137173","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":[0.13292833,0.0018420524,0.8607118,0.000739966,0.0013123356,0.001140386,0.000021794229,0.00024358684,0.0010597559],"genre_scores_gemma":[0.99558616,0.00012691878,0.00038034402,0.00007371354,0.000049612456,0.00019359328,0.000008852579,0.00003651837,0.0035442677],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988581,0.000028038558,0.00042936503,0.00020335359,0.0002006084,0.00028056063],"domain_scores_gemma":[0.998783,0.00013183511,0.00007929068,0.00024115521,0.0006779028,0.00008684483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013755832,0.000169181,0.00022805395,0.00018577428,0.00010936419,0.00004299842,0.00009010535,0.00012219885,0.00009291843],"category_scores_gemma":[0.000056407964,0.0001619101,0.00007270469,0.00023533952,0.00001473097,0.00029499253,0.0000014452571,0.000086110136,0.0000032266782],"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":[0.0005620358,0.00025683167,0.00008383608,0.0007107934,0.0010274205,0.000014813711,0.0016461064,0.7924772,0.07815693,0.0013605164,0.05007357,0.07362995],"study_design_scores_gemma":[0.005047984,0.0007656887,0.00019213451,0.00037471662,0.00025435435,0.000025415397,0.005626528,0.26450178,0.70345896,0.0017842936,0.017108157,0.00086001423],"about_ca_topic_score_codex":0.000961902,"about_ca_topic_score_gemma":0.00002055084,"teacher_disagreement_score":0.86265785,"about_ca_system_score_codex":0.00009640594,"about_ca_system_score_gemma":0.000045699515,"threshold_uncertainty_score":0.66025025},"labels":[],"label_agreement":null},{"id":"W2012331822","doi":"10.1109/tste.2014.2359795","title":"Solar Power Shaping: An Analytical Approach","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":44,"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":"Dimensioning; Energy storage; Sizing; Computer science; Solar power; Electric power system; Grid; Key (lock); Reliability engineering; Distributed generation; Renewable energy; Power (physics); Engineering; Electrical engineering; Aerospace engineering","score_opus":0.00842325861250808,"score_gpt":0.19821393512224836,"score_spread":0.18979067650974027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012331822","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":[0.0016878252,0.00008328572,0.9834979,0.000032597167,0.0001785898,0.00006543531,0.000002356058,0.00041123846,0.014040757],"genre_scores_gemma":[0.9958695,0.000054639026,0.0011601354,0.00014387131,0.00007399304,0.00004467951,0.000008719065,0.000052455674,0.0025920034],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989613,0.000041266652,0.0001846574,0.00023856813,0.00014479984,0.000429404],"domain_scores_gemma":[0.99941486,0.000025822568,0.000015360292,0.00030466195,0.00008891349,0.00015039835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013740246,0.00018601,0.00018261121,0.0002121128,0.0001647411,0.00008331161,0.00014192965,0.00013113866,0.000171728],"category_scores_gemma":[0.0000033324523,0.00018895046,0.0000894623,0.00029718856,0.000029601308,0.00028503238,7.505354e-7,0.00016982078,0.000011464639],"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":[0.000020095691,0.00010292174,7.472846e-7,0.000023601515,0.000041062303,0.0000038455614,0.00008197939,0.9821251,0.00018621427,0.0053074076,0.0001975702,0.011909424],"study_design_scores_gemma":[0.00041047618,0.00010456823,0.000007902844,0.0000035966395,0.000032350905,0.000006509408,0.00029444188,0.95756584,0.0029317725,0.00022907229,0.038175754,0.00023773189],"about_ca_topic_score_codex":0.000063606734,"about_ca_topic_score_gemma":0.000009635884,"teacher_disagreement_score":0.9941817,"about_ca_system_score_codex":0.00008249394,"about_ca_system_score_gemma":0.000021681475,"threshold_uncertainty_score":0.77051765},"labels":[],"label_agreement":null},{"id":"W2021620876","doi":"10.1109/tste.2012.2225078","title":"Sensitivity-Indices-Based Risk Assessment of Large-Scale Solar PV Investment Projects","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Power System Optimization","field":"Engineering","cited_by":9,"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":"Photovoltaic system; Sensitivity (control systems); Profit (economics); Monte Carlo method; Environmental economics; Solar power; Solar energy; Karush–Kuhn–Tucker conditions; Reliability engineering; Mathematical optimization; Econometrics; Computer science; Microeconomics; Economics; Engineering; Mathematics; Power (physics); Electrical engineering; Electronic engineering; Statistics","score_opus":0.00566346111631379,"score_gpt":0.22336411073170565,"score_spread":0.21770064961539184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021620876","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":[0.019320501,0.00013319791,0.9746162,0.000017547844,0.0004512232,0.00030353016,0.000028923883,0.00030782836,0.0048210314],"genre_scores_gemma":[0.99511474,0.000058615045,0.0034932715,0.00008127958,0.000053965116,0.00015773556,0.000013102559,0.00006879957,0.000958512],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812305,0.0002228704,0.00034069334,0.00021433551,0.0003529143,0.0007461258],"domain_scores_gemma":[0.9990425,0.00013143024,0.00011093079,0.00038443934,0.00016782516,0.0001628918],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006648245,0.0002554098,0.00029922527,0.0004668462,0.00019551713,0.00002902113,0.00008684162,0.00015674449,0.00004578471],"category_scores_gemma":[0.0000074057575,0.00027099816,0.00012067907,0.00075515115,0.000025538167,0.00040678345,0.0000014799673,0.00024858236,0.00000418839],"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":[0.000015097785,0.0004331506,0.00024357035,0.00021554843,0.00011302969,0.000010220885,0.00036030842,0.99616504,0.00092140055,0.00052565703,0.00023156706,0.000765416],"study_design_scores_gemma":[0.0011752964,0.00022680503,0.00039621355,0.00005387129,0.00016117335,0.00001029714,0.0011004438,0.7693875,0.22022007,0.000029148974,0.0067905756,0.00044861867],"about_ca_topic_score_codex":0.0004411259,"about_ca_topic_score_gemma":0.00013389149,"teacher_disagreement_score":0.9757942,"about_ca_system_score_codex":0.0006449195,"about_ca_system_score_gemma":0.00017592119,"threshold_uncertainty_score":0.9999742},"labels":[],"label_agreement":null},{"id":"W2022979892","doi":"10.1109/tste.2014.2319239","title":"Energy Provisioning and Operating Costs in Hybrid Solar-Powered Infrastructure","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Operating expense; Provisioning; Solar power; Computer science; Operating cost; Grid parity; Solar energy; Capital cost; Grid; Scheduling (production processes); Reliability engineering; Photovoltaic system; Automotive engineering; Electrical engineering; Power (physics); Engineering; Photovoltaics; Computer network; Operations management","score_opus":0.0024211013398553766,"score_gpt":0.17493618356518043,"score_spread":0.17251508222532505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022979892","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":[0.03899119,0.000113250855,0.95167863,0.00006856142,0.00047676367,0.00009824524,0.0000031576112,0.00034207775,0.008228102],"genre_scores_gemma":[0.9961975,0.00014118246,0.00068674405,0.00022391885,0.000079915306,0.00012733442,0.0000064149626,0.000081752245,0.002455241],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984127,0.00006698065,0.00032027307,0.00037542044,0.00021206429,0.0006125585],"domain_scores_gemma":[0.9993558,0.00008263067,0.000031003172,0.00033661543,0.00006259315,0.00013135931],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017846847,0.00031278672,0.0002799724,0.000461077,0.00022675369,0.00013793189,0.00016839888,0.00010672308,0.00006830003],"category_scores_gemma":[0.00001002068,0.00033293592,0.00005047644,0.0003954509,0.00004093674,0.00035592992,0.000007055563,0.000249081,0.0000020773562],"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":[0.000012512864,0.000026194613,0.000014825562,0.000055041924,0.00003934525,0.000040729312,0.000077942816,0.9541786,0.00049336016,0.004418358,0.00039864567,0.04024449],"study_design_scores_gemma":[0.0012610683,0.0001582735,0.00017139786,0.000057833735,0.000046173398,0.000027995538,0.0010543807,0.87677807,0.043315027,0.00086742843,0.075576894,0.00068546715],"about_ca_topic_score_codex":0.000995693,"about_ca_topic_score_gemma":0.00030650749,"teacher_disagreement_score":0.9572063,"about_ca_system_score_codex":0.0004734707,"about_ca_system_score_gemma":0.00003599173,"threshold_uncertainty_score":0.99991226},"labels":[],"label_agreement":null},{"id":"W2038808792","doi":"10.1109/tste.2012.2227981","title":"Analysis and Active-Impedance-Based Stabilization of Voltage-Source-Rectifier Loads in Grid-Connected and Isolated Microgrid Applications","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":78,"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":"Nyquist stability criterion; Control theory (sociology); Voltage source; Admittance; Microgrid; Electrical impedance; Rectifier (neural networks); Grid; Output impedance; Engineering; Nyquist frequency; Voltage; Electronic engineering; Computer science; Electrical engineering; Mathematics","score_opus":0.0021304130258162036,"score_gpt":0.16639187333315805,"score_spread":0.16426146030734184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038808792","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":[0.12411589,0.00046720396,0.87479985,0.000035016637,0.000048430727,0.0003321949,0.000017687405,0.00012366902,0.00006007814],"genre_scores_gemma":[0.9983832,0.0005439727,0.0003314222,0.000027092354,0.000020759962,0.00038529132,0.000034625307,0.00003153818,0.00024208437],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901265,0.0000395786,0.00031149475,0.0002680361,0.000091695205,0.0002765405],"domain_scores_gemma":[0.99932235,0.00010877524,0.000058894475,0.00021089177,0.00021931036,0.00007974976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000717124,0.00018920965,0.00028462076,0.0007820254,0.00010420661,0.000052167772,0.00006608526,0.0001339346,0.00012737479],"category_scores_gemma":[0.00000500416,0.00020325891,0.00006707339,0.0016275165,0.000060986924,0.0002577148,0.0000014722949,0.0001278323,0.0000010707131],"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":[0.00004891526,0.00008880834,0.00018130103,0.00008981103,0.0001753431,8.5332215e-7,0.00016172354,0.911276,0.012965478,0.000031743766,0.0000146343855,0.0749654],"study_design_scores_gemma":[0.0010282015,0.00007352142,0.0010242729,0.0000146487955,0.00024007163,0.0000015464174,0.00068404,0.93903273,0.05569634,0.000071468574,0.0018568079,0.00027633598],"about_ca_topic_score_codex":0.0017804413,"about_ca_topic_score_gemma":0.00063844246,"teacher_disagreement_score":0.8744684,"about_ca_system_score_codex":0.00011417559,"about_ca_system_score_gemma":0.000032887347,"threshold_uncertainty_score":0.82886577},"labels":[],"label_agreement":null},{"id":"W2041766192","doi":"10.1109/tste.2012.2202325","title":"An Optimal Total Cross Tied Interconnection for Reducing Mismatch Losses in Photovoltaic Arrays","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":98,"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":"Interconnection; Photovoltaic system; Notation; Computer science; Topology (electrical circuits); Electronic engineering; Energy (signal processing); Electrical engineering; Mathematics; Engineering; Telecommunications; Arithmetic; Statistics","score_opus":0.014043610979895487,"score_gpt":0.27820857152427475,"score_spread":0.26416496054437927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041766192","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":[0.25229445,0.00007517307,0.744273,0.000016893307,0.0006996614,0.0004688765,0.000016118236,0.00056162855,0.0015941947],"genre_scores_gemma":[0.9849633,0.000034540026,0.0061044754,0.00010223338,0.00023159663,0.001626132,0.00003628929,0.00013691103,0.006764515],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99716663,0.00017470817,0.0006917667,0.00057671964,0.00028391782,0.0011062381],"domain_scores_gemma":[0.99837273,0.00019391738,0.00017962602,0.00061960093,0.00037879054,0.00025533233],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00061071315,0.00041173652,0.0004388171,0.00076964335,0.00041533847,0.00017259385,0.0002723496,0.00035350904,0.00032693474],"category_scores_gemma":[0.00003880089,0.00045571077,0.00020470591,0.000777893,0.0000837608,0.0016338805,0.0000035743972,0.00024591148,0.0000089155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000669779,0.0008894205,0.00003596604,0.00013761257,0.000064547894,0.000011093908,0.0017860483,0.93811,0.051287662,0.0021236225,0.00021280305,0.0046714344],"study_design_scores_gemma":[0.0012455208,0.000429656,0.000031514617,0.00007269272,0.000035103134,0.00006143888,0.005826862,0.06343426,0.9214936,0.00033538346,0.006452843,0.00058111764],"about_ca_topic_score_codex":0.01348105,"about_ca_topic_score_gemma":0.000576038,"teacher_disagreement_score":0.87467575,"about_ca_system_score_codex":0.0009598321,"about_ca_system_score_gemma":0.00015338586,"threshold_uncertainty_score":0.9997895},"labels":[],"label_agreement":null},{"id":"W2054699739","doi":"10.1109/tste.2012.2200304","title":"Hydro-Québec Strategy to Evaluate Electrical Transients Following Wind Power Plant Integration in the Gaspésie Transmission System","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Wind power; Transient (computer programming); Electric power system; Electric power transmission; Engineering; Transmission system; Transmission (telecommunications); Electrical engineering; Environmental science; Computer science; Power (physics); Systems engineering; Automotive engineering; Physics","score_opus":0.008339915291497161,"score_gpt":0.22368758937225264,"score_spread":0.21534767408075547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054699739","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":[0.20669381,0.00037090102,0.78239584,0.00009470562,0.00048622885,0.0006297565,0.0000055603055,0.00027726148,0.00904593],"genre_scores_gemma":[0.9987092,0.000010648431,0.00002186266,0.00007228036,0.00006242313,0.00012135045,0.000007131355,0.00005088863,0.00094420667],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997832,0.00023176966,0.00047716874,0.00023821933,0.00048302463,0.00073781615],"domain_scores_gemma":[0.9992928,0.00013754792,0.000031341886,0.00027881714,0.000054629374,0.00020485374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061248813,0.00029389502,0.00030571147,0.00040417732,0.00021260799,0.00010576557,0.00020043377,0.00016216908,0.000054722845],"category_scores_gemma":[0.0000039736515,0.00022519416,0.00019758253,0.0007567995,0.000010179262,0.00045685878,4.6454485e-7,0.000277333,0.000026109805],"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":[0.00013501878,0.0001866635,0.000007484804,0.00004762346,0.00006694421,0.000039845363,0.0029510248,0.96362525,0.0040450613,0.0012220548,0.00013937838,0.027533632],"study_design_scores_gemma":[0.004197186,0.0008003187,0.0007452879,0.00035356235,0.00024431347,0.000104904146,0.023563834,0.9268996,0.019172812,0.000058946425,0.022692552,0.0011666734],"about_ca_topic_score_codex":0.0026630715,"about_ca_topic_score_gemma":0.00039604327,"teacher_disagreement_score":0.7920154,"about_ca_system_score_codex":0.0006867268,"about_ca_system_score_gemma":0.000092053924,"threshold_uncertainty_score":0.9183151},"labels":[],"label_agreement":null},{"id":"W2056158542","doi":"10.1109/tste.2012.2208128","title":"Optimal Photovoltaic Array Reconfiguration to Reduce Partial Shading Losses","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":344,"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":"Shading; Photovoltaic system; Control reconfiguration; Computer science; Electrical engineering; Electronic engineering; Engineering; Embedded system","score_opus":0.017262518171645952,"score_gpt":0.25939081834212685,"score_spread":0.2421283001704809,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056158542","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":[0.026087878,0.00007400698,0.951287,0.00012439456,0.0009785893,0.0004714087,0.000012835336,0.0009478002,0.020016115],"genre_scores_gemma":[0.9680054,0.00005190524,0.006021644,0.0004821567,0.00038855275,0.0011142263,0.000019053214,0.00012200564,0.023795063],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9969488,0.00019719318,0.0006530098,0.00055853516,0.00045781484,0.0011846642],"domain_scores_gemma":[0.99813205,0.00014538007,0.00017360131,0.0006736285,0.0003930505,0.00048226706],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00048674466,0.00043314978,0.00041291365,0.0006981327,0.00056099024,0.00015927029,0.00031483,0.0002820026,0.0012904914],"category_scores_gemma":[0.000053466312,0.00046691074,0.00019332886,0.0011215147,0.00006143084,0.0010878094,0.0000035832245,0.00023782255,0.00014221648],"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":[0.0004241751,0.0005888382,0.000015653452,0.000077168304,0.00015281499,0.000023552473,0.0015161309,0.6364803,0.3367212,0.01043818,0.0042259106,0.009336062],"study_design_scores_gemma":[0.0003385016,0.00017141862,0.000006692575,0.000040607996,0.000042338797,0.000033620505,0.0015969505,0.0019445465,0.85183424,0.00010789384,0.1434171,0.0004660604],"about_ca_topic_score_codex":0.0058811163,"about_ca_topic_score_gemma":0.00015079693,"teacher_disagreement_score":0.94526535,"about_ca_system_score_codex":0.00077857287,"about_ca_system_score_gemma":0.00016813676,"threshold_uncertainty_score":0.9997783},"labels":[],"label_agreement":null},{"id":"W2059605169","doi":"10.1109/tste.2015.2403845","title":"An Optimal Maximum Power Point Tracking Algorithm for PV Systems With Climatic Parameters Estimation","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":100,"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 de Technologie Supérieure","funders":"","keywords":"Maximum power point tracking; Photovoltaic system; Maximum power principle; Voltage; Control theory (sociology); Computer science; Electronic engineering; Power (physics); Noise (video); Algorithm; Engineering; Electrical engineering; Inverter; Artificial intelligence; Physics","score_opus":0.017398413416683696,"score_gpt":0.2550071060257386,"score_spread":0.23760869260905493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059605169","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":[0.001955098,0.000054182303,0.99429876,0.000049172566,0.00040780622,0.0009079618,0.00003028861,0.0009357249,0.001361022],"genre_scores_gemma":[0.8359812,0.00000995031,0.16016419,0.00011037686,0.000038872407,0.0017632195,0.000053652653,0.00015258392,0.0017259619],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971905,0.0002205305,0.00065195427,0.00060916285,0.0005541393,0.00077373796],"domain_scores_gemma":[0.99751294,0.00017871075,0.0002782052,0.0007287062,0.00094253314,0.00035892817],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00068668433,0.0004418222,0.0005080235,0.0005795529,0.00034643672,0.0003362479,0.00031439855,0.00025807178,0.000038390666],"category_scores_gemma":[0.000025369882,0.00041115988,0.00013929023,0.00062886387,0.0000889459,0.0012270398,0.0000021917801,0.00017277105,0.000007807045],"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":[0.00024943094,0.00029219734,5.662351e-7,0.00007887591,0.000102624756,0.00003516623,0.0005339294,0.9764894,0.00009273872,0.002594835,0.00022576685,0.019304443],"study_design_scores_gemma":[0.0016035534,0.0016308763,6.952559e-7,0.00010101803,0.00010802169,0.00010722773,0.009295265,0.9380451,0.04483362,0.0010275579,0.0026778067,0.00056928716],"about_ca_topic_score_codex":0.003293056,"about_ca_topic_score_gemma":0.00004976653,"teacher_disagreement_score":0.8341346,"about_ca_system_score_codex":0.0008910371,"about_ca_system_score_gemma":0.00028240486,"threshold_uncertainty_score":0.999834},"labels":[],"label_agreement":null},{"id":"W2060473677","doi":"10.1109/tste.2013.2282077","title":"Modeling, Prediction, and Experimental Validations of Power Peaks of PV Arrays Under Partial Shading Conditions","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":138,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Shading; Irradiance; Photovoltaic system; Power (physics); Series (stratigraphy); Solar irradiance; Maximum power principle; Electronic engineering; Computer science; Engineering; Electrical engineering; Optics; Physics; Meteorology","score_opus":0.010785582699534505,"score_gpt":0.24295623377215217,"score_spread":0.23217065107261767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060473677","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":[0.06284316,0.000036927966,0.9312065,0.00003396546,0.00016718918,0.00016815016,0.000042921994,0.00020719874,0.0052939826],"genre_scores_gemma":[0.99716914,0.000027045546,0.0010981576,0.000057884954,0.000030554213,0.00023125691,0.000027402508,0.000047888054,0.0013106772],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99834806,0.00013739173,0.0006033712,0.00032290665,0.0002916212,0.00029664955],"domain_scores_gemma":[0.99883693,0.000096436364,0.00015930411,0.0003939888,0.00040017106,0.00011318509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021888122,0.00021227883,0.0003202179,0.00044116058,0.00028733857,0.000029018725,0.00013824142,0.00016386855,0.0004054737],"category_scores_gemma":[0.00001786007,0.00023217454,0.00012002724,0.00038218536,0.00014509296,0.0003430939,0.000004332896,0.00010709741,0.0000014024874],"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":[0.00003799855,0.0002454085,0.000005921409,0.000030379457,0.00007259879,7.277739e-7,0.000521606,0.88945884,0.026061978,0.083410814,0.00010155025,0.00005215783],"study_design_scores_gemma":[0.0006621532,0.00026902521,0.000004694477,0.000046848567,0.00005772125,0.000010005885,0.005277023,0.29095054,0.69876903,0.002729402,0.0010280344,0.00019550059],"about_ca_topic_score_codex":0.0033765545,"about_ca_topic_score_gemma":0.000057737467,"teacher_disagreement_score":0.934326,"about_ca_system_score_codex":0.00014642083,"about_ca_system_score_gemma":0.00008717314,"threshold_uncertainty_score":0.9467803},"labels":[],"label_agreement":null},{"id":"W2065605071","doi":"10.1109/tste.2011.2166415","title":"Three-Phase Steady-State Model of Type-3 Wind Generation Unit—Part II: Model Validation and Applications","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","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":"University of Toronto","funders":"","keywords":"Solver; Computer science; Steady state (chemistry); Frame (networking); Power system simulation; Wind power; Algorithm; Sequence (biology); Flow (mathematics); Power (physics); Control theory (sociology); Simulation; Engineering; Electric power system; Mathematics; Control (management); Electrical engineering; Artificial intelligence","score_opus":0.031974015312396235,"score_gpt":0.22563063245317164,"score_spread":0.1936566171407754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065605071","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":[0.08724713,0.00010423935,0.9100452,0.000010657916,0.00011728044,0.00031385568,0.000042286523,0.00016744618,0.0019518881],"genre_scores_gemma":[0.99523747,0.00007274798,0.0008545847,0.000015338548,0.00006119956,0.00019005129,0.000022040536,0.000057136403,0.0034894499],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890906,0.000020728457,0.0003659237,0.00024222764,0.00016755263,0.00029450562],"domain_scores_gemma":[0.9991748,0.000017651184,0.000066566965,0.00036801028,0.00026836916,0.000104656225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001321167,0.00021043586,0.00022608746,0.000276438,0.00021734857,0.000024440822,0.000114114126,0.000115728835,0.000023696482],"category_scores_gemma":[0.0000020529567,0.00022866795,0.000054933535,0.0003298394,0.00004200609,0.0003578583,0.000002340193,0.00012655441,0.0000028663585],"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":[0.000038037222,0.00014288514,0.0000011862807,0.00006329286,0.00006342563,0.0000010545571,0.00038073267,0.9796436,0.00922565,0.006095983,0.000110500645,0.004233654],"study_design_scores_gemma":[0.00075549266,0.000106332,9.244634e-7,0.000009250476,0.00006261102,0.000002654769,0.00013809148,0.9376849,0.058027737,0.0023867877,0.00062356977,0.00020166139],"about_ca_topic_score_codex":0.00026809468,"about_ca_topic_score_gemma":0.00010914478,"teacher_disagreement_score":0.90919065,"about_ca_system_score_codex":0.000097634176,"about_ca_system_score_gemma":0.000087321874,"threshold_uncertainty_score":0.9324809},"labels":[],"label_agreement":null},{"id":"W2067246442","doi":"10.1109/tste.2013.2276616","title":"Interconnection of Direct-Drive Wind Turbines Using a Series-Connected DC Grid","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":144,"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 Toronto; McGill University","funders":"","keywords":"Offshore wind power; Electrical engineering; Wind power; Turbine; Engineering; Power optimizer; Forward converter; Topology (electrical circuits); Voltage; Boost converter; Inverter; Maximum power point tracking","score_opus":0.006872551231935569,"score_gpt":0.19322434437289532,"score_spread":0.18635179314095976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067246442","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":[0.44519737,0.000102857215,0.5472996,0.00002478458,0.0017823542,0.00042300374,0.00001696251,0.00054458814,0.0046084756],"genre_scores_gemma":[0.9961508,0.000041751584,0.00021553999,0.00001150526,0.00015468981,0.00012854648,0.000003858641,0.00005986775,0.00323346],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998801,0.00005427752,0.00037366114,0.00023762906,0.00015310009,0.00038036067],"domain_scores_gemma":[0.9992469,0.00004272123,0.000066982764,0.00026375713,0.00029422887,0.000085419146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008683825,0.00024185701,0.00030057895,0.0003922265,0.0001735069,0.00005506223,0.000095387375,0.00017828368,0.00022492874],"category_scores_gemma":[0.0000083256555,0.00024337991,0.00012574767,0.0006312963,0.00004130985,0.00070374407,0.0000014772907,0.00017592385,0.000011845901],"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":[0.00005275209,0.000110992856,0.0000062668205,0.0002880407,0.00019042742,0.000011286862,0.00044485426,0.87606865,0.114650175,0.0003189016,0.00024535463,0.0076123155],"study_design_scores_gemma":[0.0010853353,0.00045974366,0.00007608765,0.00019284277,0.00007609101,0.00013245996,0.005086657,0.13297868,0.83898705,0.0003546206,0.019861402,0.00070902356],"about_ca_topic_score_codex":0.006332107,"about_ca_topic_score_gemma":0.00018248221,"teacher_disagreement_score":0.74309,"about_ca_system_score_codex":0.00028796782,"about_ca_system_score_gemma":0.000034880628,"threshold_uncertainty_score":0.9924745},"labels":[],"label_agreement":null},{"id":"W2089419227","doi":"10.1109/tste.2011.2181878","title":"Computation of Dynamic Operating Balancing Reserve for Wind Power Integration for the Time-Horizon 1–48 Hours","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":116,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Unavailability; Time horizon; Wind power; Electric power system; Computer science; Reliability (semiconductor); Computation; Horizon; Reliability engineering; Power (physics); Mathematical optimization; Engineering; Mathematics","score_opus":0.006012515770543302,"score_gpt":0.22496160561211156,"score_spread":0.21894908984156827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089419227","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":[0.017719122,0.00028203634,0.97996265,0.000103699196,0.00093946524,0.0005349059,0.000028800758,0.000104256746,0.0003250621],"genre_scores_gemma":[0.9968391,0.000017657176,0.001320027,0.00002534558,0.000047784008,0.00024236063,0.000010400907,0.000040910105,0.0014563842],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989548,0.000035732824,0.00030134455,0.0001401537,0.00012299736,0.000445026],"domain_scores_gemma":[0.99907774,0.00033380583,0.000056625016,0.0001951941,0.00026850897,0.00006810263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005920127,0.00015317524,0.00019142011,0.00010779456,0.00023660032,0.000034006818,0.00011604916,0.00009893004,0.000009569795],"category_scores_gemma":[0.00005264161,0.00012435291,0.00012890203,0.00021043344,0.000031394597,0.0003500173,0.0000011504521,0.00010332844,0.0000017779298],"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":[0.00007877581,0.00007753231,0.0000024351648,0.00027542395,0.00008807987,3.12072e-7,0.0008381294,0.9759047,0.0074586878,0.0019774672,0.0009984663,0.012299973],"study_design_scores_gemma":[0.00081530906,0.00033988472,0.000036166773,0.00016095754,0.00008115795,0.00000538835,0.0059333695,0.925439,0.061530914,0.00042522684,0.0049399547,0.00029266218],"about_ca_topic_score_codex":0.00016236212,"about_ca_topic_score_gemma":0.00006268972,"teacher_disagreement_score":0.97912,"about_ca_system_score_codex":0.00031136003,"about_ca_system_score_gemma":0.000053680407,"threshold_uncertainty_score":0.50709647},"labels":[],"label_agreement":null},{"id":"W2092081531","doi":"10.1109/tste.2014.2364778","title":"Data Constrained Adequacy Assessment for Wind Resource Planning","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":19,"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 Saskatchewan","funders":"","keywords":"Wind power; Wind speed; Electric power system; Environmental science; Offshore wind power; Meteorology; Electricity generation; Computer science; Power (physics); Engineering; Electrical engineering; Geography","score_opus":0.016853006495066252,"score_gpt":0.25698152394081775,"score_spread":0.2401285174457515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092081531","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":[0.0007385003,0.000072524825,0.9837054,0.00015768918,0.00046778965,0.00022766013,0.000105258114,0.00036915363,0.014156002],"genre_scores_gemma":[0.992518,0.000010294539,0.0019344458,0.00013893789,0.00010296528,0.00009928265,0.000043641205,0.00005160865,0.0051007955],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985433,0.000052780826,0.0003016024,0.0003710046,0.00016817386,0.0005630873],"domain_scores_gemma":[0.99858195,0.00033086917,0.00003838226,0.0008398609,0.00008436475,0.0001245515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005213976,0.00021249538,0.00025742163,0.00014168386,0.00023983915,0.00006761134,0.00040220504,0.00012246789,0.000031055264],"category_scores_gemma":[0.000023401373,0.00021825047,0.0000768285,0.00019634338,0.000059176422,0.000274116,0.0000036990732,0.0001860942,0.0000032237501],"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":[0.0000478204,0.00007463112,0.0000015697835,0.00035374172,0.00009301911,0.000011002914,0.00012136641,0.968337,0.00038322696,0.011966322,0.0064822803,0.012128024],"study_design_scores_gemma":[0.00076563255,0.00012905394,0.0000068626423,0.00007045501,0.00003659498,0.000010160576,0.0012538738,0.28127387,0.0023707906,0.00070736994,0.71309495,0.0002804144],"about_ca_topic_score_codex":0.00007163652,"about_ca_topic_score_gemma":0.000020020107,"teacher_disagreement_score":0.9917795,"about_ca_system_score_codex":0.00020154426,"about_ca_system_score_gemma":0.00008056069,"threshold_uncertainty_score":0.8899996},"labels":[],"label_agreement":null},{"id":"W2096315202","doi":"10.1109/tste.2014.2298466","title":"Three-Phase Fault Direction Identification for Distribution Systems With DFIG-Based Wind DG","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":59,"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":"Crowbar; Overcurrent; Fault (geology); Wind power; Induction generator; Engineering; Phasor; Control theory (sociology); AC power; Generator (circuit theory); Voltage; Electronic engineering; Power (physics); Computer science; Electric power system; Electrical engineering","score_opus":0.005871716586165758,"score_gpt":0.21648065585503276,"score_spread":0.210608939268867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096315202","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":[0.010423977,0.000066958004,0.9857999,0.000031143558,0.0017727839,0.0006398535,0.00009740364,0.00090240175,0.00026558698],"genre_scores_gemma":[0.9970692,0.0000060484085,0.00008306567,0.000010740726,0.00017984098,0.0008900873,0.00012987839,0.000091272836,0.0015398737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982919,0.0000614711,0.000425084,0.0004018017,0.0003081334,0.00051157473],"domain_scores_gemma":[0.998813,0.00012280783,0.00010796716,0.000470154,0.00035810622,0.00012797352],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037142908,0.00030743083,0.00027965946,0.00030412446,0.00042751263,0.00017323659,0.00013164344,0.00021243318,0.000008365063],"category_scores_gemma":[0.000014163202,0.00030992008,0.00011580543,0.0006116687,0.00003958174,0.00041958733,5.0298485e-7,0.00016543454,0.00001056237],"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":[0.00023194219,0.00015853495,0.0000018423758,0.00036841177,0.0000884618,0.0000032848284,0.00003249148,0.9671849,0.0038431755,0.0008469935,0.0006607494,0.026579194],"study_design_scores_gemma":[0.0018917052,0.00046122566,0.000016791317,0.00006802242,0.000095538446,0.000015304722,0.00024215948,0.7821673,0.09121662,0.00008289149,0.12337047,0.0003719479],"about_ca_topic_score_codex":0.00079460634,"about_ca_topic_score_gemma":0.00035768028,"teacher_disagreement_score":0.9866452,"about_ca_system_score_codex":0.0008343345,"about_ca_system_score_gemma":0.000055241588,"threshold_uncertainty_score":0.99993527},"labels":[],"label_agreement":null},{"id":"W2097585376","doi":"10.1109/tste.2011.2153217","title":"Multiple Model Predictive Control for Wind Turbines With Doubly Fed Induction Generators","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":206,"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 Calgary","funders":"","keywords":"Control theory (sociology); Wind power; Turbine; Model predictive control; Controller (irrigation); Torque; Engineering; Operating point; Induction generator; Pitch control; Power (physics); Control engineering; Automotive engineering; Computer science; Control (management); Electronic engineering","score_opus":0.008488098235885921,"score_gpt":0.17164984630686095,"score_spread":0.16316174807097503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097585376","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":[0.015412585,0.00011881961,0.9828762,0.000015997572,0.00027324073,0.00042580086,0.000047942638,0.0003664236,0.00046297896],"genre_scores_gemma":[0.9947139,0.000068376394,0.0034254158,0.000058603357,0.000098523175,0.00044685512,0.0000132058485,0.00007514738,0.0010999741],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897987,0.000017633976,0.00020923646,0.00026034596,0.00012086989,0.0004120675],"domain_scores_gemma":[0.9993385,0.00003346351,0.000041159903,0.00020104852,0.00028568503,0.00010011847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000067469846,0.00024846382,0.0002159659,0.00022566221,0.00023847369,0.000038663442,0.00009614202,0.00014956821,0.000024935636],"category_scores_gemma":[0.0000029184596,0.00022401719,0.00008793925,0.0002479675,0.000037699865,0.00039565223,4.9962114e-7,0.00012684436,0.0000012938709],"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":[0.000936244,0.00007433169,0.000004518185,0.000035371515,0.0001724007,0.0000038559274,0.00031068778,0.9940546,0.0012233262,0.00030101225,0.00013194015,0.002751712],"study_design_scores_gemma":[0.002899956,0.000334488,0.000008685967,0.0000096869835,0.000115476105,0.0000049671603,0.00044610992,0.9458641,0.04912666,0.00025644142,0.00066501583,0.00026843997],"about_ca_topic_score_codex":0.00020307345,"about_ca_topic_score_gemma":0.00009916057,"teacher_disagreement_score":0.9794508,"about_ca_system_score_codex":0.00021531875,"about_ca_system_score_gemma":0.0000828781,"threshold_uncertainty_score":0.9135156},"labels":[],"label_agreement":null},{"id":"W2102600802","doi":"10.1109/tste.2012.2230653","title":"Analysis and Active Suppression of AC- and DC-Side Instabilities in Grid-Connected Current-Source Converter-Based Photovoltaic System","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":46,"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":"Control theory (sociology); Nyquist stability criterion; Photovoltaic system; Electrical impedance; Converters; Nyquist plot; LC circuit; Electronic engineering; Computer science; Engineering; Physics; Electrical engineering; Capacitor; Mathematics; Voltage","score_opus":0.0030418719830756424,"score_gpt":0.1715891210518155,"score_spread":0.16854724906873986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102600802","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":[0.5899869,0.0005180735,0.40888616,0.000010887,0.00014437722,0.00022898255,0.000023706,0.0001237289,0.000077149125],"genre_scores_gemma":[0.999382,0.00020635642,0.00007952347,0.0000086848,0.000014394229,0.00016387059,0.000013833517,0.000022736647,0.000108584085],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903744,0.000067401226,0.0002883939,0.00022563868,0.00010804691,0.00027309766],"domain_scores_gemma":[0.99940664,0.0001406508,0.00005055625,0.00017915598,0.00014439256,0.00007858622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006482784,0.00019152323,0.00034717933,0.00067511224,0.000080124555,0.000042758216,0.000060696617,0.00009727656,0.00005481748],"category_scores_gemma":[0.000005481226,0.00018530012,0.00007194611,0.0006575243,0.000059455313,0.00029000783,0.0000018467306,0.00013098236,5.4646756e-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":[0.00009385249,0.00008189529,0.00024351639,0.00061637233,0.00019392722,0.000003319501,0.00056744134,0.95368475,0.013669388,0.00003400001,0.00001593984,0.030795598],"study_design_scores_gemma":[0.0011501018,0.00005832755,0.0011051743,0.00007577631,0.00017463705,0.000001715094,0.004391656,0.8862166,0.106223606,0.00001371431,0.0003760447,0.00021264685],"about_ca_topic_score_codex":0.003913174,"about_ca_topic_score_gemma":0.00043652154,"teacher_disagreement_score":0.40939507,"about_ca_system_score_codex":0.00015259779,"about_ca_system_score_gemma":0.000033755903,"threshold_uncertainty_score":0.755632},"labels":[],"label_agreement":null},{"id":"W2106934845","doi":"10.1109/tste.2011.2149551","title":"Dynamic Modeling and Performance Analysis of a Grid-Connected Current-Source Inverter-Based Photovoltaic System","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":232,"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":"Photovoltaic system; Interfacing; Electronic engineering; Computer science; Inverter; Grid-connected photovoltaic power system; Transient (computer programming); Controllability; Maximum power point tracking; Electric power system; Grid; Engineering; Electrical engineering; Control theory (sociology); Power (physics); Voltage","score_opus":0.006877455987335539,"score_gpt":0.1720276111092409,"score_spread":0.16515015512190534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106934845","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":[0.25663114,0.0004030604,0.74246365,8.73802e-7,0.00012100401,0.000076115095,0.00001124379,0.00019781743,0.00009507054],"genre_scores_gemma":[0.9991463,0.00028348036,0.0003599988,0.000008106688,0.0000070367114,0.00006515123,0.000014159962,0.00003173023,0.00008406213],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908215,0.000026385476,0.00029001175,0.00020218742,0.00011338446,0.00028586877],"domain_scores_gemma":[0.9994867,0.000022468377,0.00004588539,0.00022602487,0.00014518331,0.00007374412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007851156,0.00018853831,0.0003071354,0.0007752209,0.00011323741,0.000018757919,0.00009377748,0.00007983167,0.000032311884],"category_scores_gemma":[0.0000012892314,0.00019439943,0.00012010822,0.0009779042,0.000025192718,0.00016607386,0.0000010104138,0.00011341489,7.7814616e-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":[0.000067031695,0.00004736792,0.000022220818,0.0003119125,0.0002960769,0.0000020831912,0.00020684605,0.98652565,0.00076072395,0.000023355718,0.0000018983322,0.0117348],"study_design_scores_gemma":[0.00047060405,0.000059284677,0.000029886232,0.0000450328,0.0005510689,0.0000015001712,0.0004935433,0.9918251,0.0062726494,0.000003073358,0.00006346333,0.00018476616],"about_ca_topic_score_codex":0.0006394032,"about_ca_topic_score_gemma":0.00012353256,"teacher_disagreement_score":0.74251515,"about_ca_system_score_codex":0.00015231792,"about_ca_system_score_gemma":0.000032793065,"threshold_uncertainty_score":0.79273784},"labels":[],"label_agreement":null},{"id":"W2112934668","doi":"10.1109/tste.2012.2191581","title":"Negative Sequence Current Control in Wind Power Plants With VSC-HVDC Connection","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":115,"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 Manitoba","funders":"","keywords":"Wind power; Connection (principal bundle); Electrical engineering; Current (fluid); Power (physics); Power control; Control (management); Engineering; Control theory (sociology); Computer science; Physics; Mechanical engineering","score_opus":0.009289263258960043,"score_gpt":0.2195277456273069,"score_spread":0.21023848236834686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112934668","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":[0.13905105,0.00032855247,0.85686916,0.00002046432,0.0011097996,0.0003850501,0.00001775389,0.00027049278,0.0019476729],"genre_scores_gemma":[0.99883187,0.000061219565,0.00003202733,0.000025759826,0.00008583159,0.00020620518,0.000002177393,0.00004211283,0.00071281695],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987306,0.000067022534,0.00023653122,0.00019508712,0.0001898888,0.0005808799],"domain_scores_gemma":[0.99950826,0.00006615598,0.000041176143,0.00018374558,0.00007325493,0.00012740602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018234526,0.00022601435,0.00022196858,0.00030175544,0.00014440552,0.000035375113,0.00006870449,0.000120320845,0.00006320141],"category_scores_gemma":[0.000003531375,0.00020704394,0.000048461854,0.00036026275,0.000033843175,0.0005798276,4.946919e-7,0.00030256822,0.000015498248],"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":[0.0003511356,0.00030049088,0.0001483032,0.00015533277,0.00012719426,0.000040560997,0.0016606625,0.9753807,0.0033168835,0.0012850537,0.00015081548,0.017082859],"study_design_scores_gemma":[0.024318537,0.003050553,0.004420034,0.0015397553,0.00029189602,0.00078607,0.040932667,0.22810201,0.3449788,0.0012220435,0.34478012,0.0055775032],"about_ca_topic_score_codex":0.0011326865,"about_ca_topic_score_gemma":0.00020795286,"teacher_disagreement_score":0.8597808,"about_ca_system_score_codex":0.0005384372,"about_ca_system_score_gemma":0.00004270692,"threshold_uncertainty_score":0.8443007},"labels":[],"label_agreement":null},{"id":"W2121586881","doi":"10.1109/tste.2011.2178045","title":"Interactive Distributed Generation Interface for Flexible Micro-Grid Operation in Smart Distribution Systems","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":98,"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":"Islanding; Interface (matter); Backup; Distributed generation; Grid; Controller (irrigation); AC power; Smart grid; Computer science; Engineering; Microgrid; Control engineering; Voltage; Control theory (sociology); Control (management); Electrical engineering; Renewable energy","score_opus":0.008200582650001073,"score_gpt":0.21670211103065384,"score_spread":0.20850152838065278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121586881","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":[0.009037323,0.00076080806,0.9873311,0.000047303813,0.0017814474,0.00045446577,0.00026053097,0.00024522908,0.00008181516],"genre_scores_gemma":[0.9968216,0.00016277067,0.00033203536,0.000020474527,0.00027984576,0.0006587758,0.0008034733,0.000041538817,0.0008794924],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987678,0.00005470564,0.00035215498,0.00020587245,0.000102953985,0.0005165371],"domain_scores_gemma":[0.99946135,0.000056917124,0.00004626083,0.0001734678,0.00017316414,0.00008886298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019850512,0.00022251795,0.00021347952,0.00018255964,0.00017608228,0.00012376603,0.00008524645,0.0001482922,0.000027260809],"category_scores_gemma":[0.000008244934,0.00023890652,0.00007704744,0.00032052593,0.000016409202,0.0008308172,0.0000013766254,0.00015052699,0.000007494644],"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":[0.00009254968,0.00012671898,0.000007141011,0.00006230607,0.00004379623,8.81097e-7,0.00015917167,0.9834815,0.011005852,0.000719235,0.0016955405,0.0026052697],"study_design_scores_gemma":[0.0009455154,0.00008210099,0.000021874645,0.000028671835,0.00003654316,0.0000069691946,0.0008067359,0.74934983,0.2098333,0.000016397284,0.038585026,0.00028702995],"about_ca_topic_score_codex":0.00033672532,"about_ca_topic_score_gemma":0.00007675176,"teacher_disagreement_score":0.98778427,"about_ca_system_score_codex":0.0008911817,"about_ca_system_score_gemma":0.00003463969,"threshold_uncertainty_score":0.9742325},"labels":[],"label_agreement":null},{"id":"W2128793456","doi":"10.1109/tste.2014.2309661","title":"Impact of Energy Storage Systems on Electricity Market Equilibrium","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":112,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada; University of Waterloo","funders":"Government of Canada","keywords":"Energy storage; Electricity market; Arbitrage; Market clearing; Mixed complementarity problem; Market price; Demand response; Economic dispatch; Electric power system; Computer science; Smart grid; Electricity; Distributed generation; Mathematical optimization; Microeconomics; Economics; Renewable energy; Power (physics); Engineering; Electrical engineering; Finance","score_opus":0.004894339326047541,"score_gpt":0.19703263883692027,"score_spread":0.19213829951087272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128793456","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":[0.043371856,0.0001142027,0.9070088,0.000013832824,0.0010230765,0.000105992054,0.00001324331,0.0005080467,0.047840945],"genre_scores_gemma":[0.9815176,0.000096122196,0.000030388468,0.0000348543,0.000167979,0.000131791,0.0000062895574,0.00011294402,0.01790204],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997862,0.00014392173,0.00041942112,0.00036701406,0.00040592655,0.00080175605],"domain_scores_gemma":[0.9986764,0.00019158355,0.000077425415,0.00072969304,0.0001413947,0.00018350726],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027452028,0.000408771,0.00044592703,0.0007449316,0.000106589636,0.0000615551,0.0003122351,0.00017241262,0.00019318942],"category_scores_gemma":[0.000009905358,0.00040326058,0.00028485619,0.0008575764,0.000042652104,0.00022261571,0.0000035536705,0.00020118468,0.000007367554],"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":[0.00011148507,0.0001686418,0.0000059448253,0.00011706994,0.0002705328,0.000019237656,0.000015721613,0.9817647,0.00092341116,0.0070026214,0.0078181205,0.0017825585],"study_design_scores_gemma":[0.00091958937,0.0010519653,0.00025232922,0.000052795996,0.00008475785,0.000009750734,0.00010039995,0.9180923,0.02740955,0.00021167511,0.051158413,0.00065647444],"about_ca_topic_score_codex":0.0022489794,"about_ca_topic_score_gemma":0.000033465723,"teacher_disagreement_score":0.93814576,"about_ca_system_score_codex":0.00089568266,"about_ca_system_score_gemma":0.00006096491,"threshold_uncertainty_score":0.9998419},"labels":[],"label_agreement":null},{"id":"W2129595206","doi":"10.1109/tste.2012.2191986","title":"Coordinated Control of Cascaded Current-Source Converter Based Offshore Wind Farm","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":124,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Rockwell Automation (Canada); Toronto Metropolitan University","funders":"","keywords":"Offshore wind power; Wind power; Turbine; Power optimizer; Permanent magnet synchronous generator; Converters; Engineering; Voltage source; Control theory (sociology); Grid; AC power; Computer science; Electrical engineering; Maximum power point tracking; Voltage; Control (management)","score_opus":0.00686954209980149,"score_gpt":0.20489630889579452,"score_spread":0.19802676679599304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129595206","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":[0.013660984,0.0005743559,0.9834339,0.000017875203,0.0009609825,0.0002586609,0.000021609558,0.0002766471,0.00079497887],"genre_scores_gemma":[0.9973988,0.000018604756,0.00002224946,0.000032894826,0.000104503866,0.000100641075,0.000005112567,0.000059658414,0.0022575625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866253,0.00007151309,0.00034376176,0.00016689725,0.00019301086,0.00056226546],"domain_scores_gemma":[0.99929047,0.00006223329,0.000059286438,0.00026647054,0.00016365874,0.00015785717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018868671,0.00023876781,0.00031312733,0.00029117736,0.00012850479,0.0000214532,0.000106327854,0.00017696858,0.00013821464],"category_scores_gemma":[0.000003588857,0.00023773425,0.00014520407,0.00042179893,0.000045380017,0.00020520733,6.257332e-7,0.00024498155,0.000011162533],"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":[0.00023913181,0.0004954786,0.00010722893,0.0007726572,0.00029961643,0.000009608562,0.00055139285,0.83671314,0.014941761,0.0009230738,0.00048090646,0.14446601],"study_design_scores_gemma":[0.004260504,0.00023661813,0.00014226812,0.00012253634,0.00018237013,0.00002477692,0.0016668524,0.4099754,0.26515752,0.0000243561,0.31745753,0.0007492247],"about_ca_topic_score_codex":0.0006324556,"about_ca_topic_score_gemma":0.000022973943,"teacher_disagreement_score":0.98373777,"about_ca_system_score_codex":0.00021936737,"about_ca_system_score_gemma":0.000042076532,"threshold_uncertainty_score":0.9694521},"labels":[],"label_agreement":null},{"id":"W2130820962","doi":"10.1109/tste.2012.2191425","title":"Impact of High PV Penetration on Voltage Profiles in Residential Neighborhoods","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":539,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Photovoltaic system; Penetration (warfare); Transformer; Voltage; Grid; Electrical impedance; Electrical engineering; Distribution transformer; Environmental science; Automotive engineering; Engineering; Geography","score_opus":0.005859413454427066,"score_gpt":0.23108739782648596,"score_spread":0.2252279843720589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130820962","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":[0.5631101,0.000060900576,0.43464315,0.000012906226,0.000391257,0.00014537873,0.0000532394,0.00012858621,0.0014544518],"genre_scores_gemma":[0.9990589,0.000045227658,0.000057217057,0.0000061876513,0.00008895875,0.00004924608,0.00003611078,0.000042317115,0.0006158559],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987233,0.000039437764,0.00030408747,0.0001640657,0.00022328342,0.0005457773],"domain_scores_gemma":[0.9994588,0.000050944174,0.00004260755,0.00025831885,0.00008503907,0.00010431576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014866581,0.00021459414,0.00020966186,0.00040028672,0.00006754497,0.00002770811,0.00010530227,0.00015628857,0.00024711297],"category_scores_gemma":[0.00000750502,0.0002214155,0.00012744474,0.00053926965,0.00002971552,0.0005562444,0.00000110375,0.00020444831,0.00001101341],"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":[0.00016239178,0.0003631814,0.00016490769,0.0000668995,0.00005837106,0.000009199872,0.00013022643,0.98470926,0.006872586,0.0048232777,0.0005930821,0.0020466056],"study_design_scores_gemma":[0.003410374,0.0022775126,0.06679442,0.00015011606,0.00013876367,0.000018456029,0.001353217,0.059079316,0.8626481,0.00140514,0.0013494678,0.0013750695],"about_ca_topic_score_codex":0.0021464385,"about_ca_topic_score_gemma":0.000087993714,"teacher_disagreement_score":0.92563,"about_ca_system_score_codex":0.00072023453,"about_ca_system_score_gemma":0.00006793944,"threshold_uncertainty_score":0.9029062},"labels":[],"label_agreement":null},{"id":"W2142461803","doi":"10.1109/tste.2015.2412694","title":"Accuracy Improvement of the Ideal PV Model","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":63,"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":"Datasheet; Irradiance; Photovoltaic system; Ideal (ethics); Solar irradiance; Simplicity; Saturation current; Monocrystalline silicon; Computer science; Electronic engineering; Engineering; Voltage; Electrical engineering; Optics; Physics","score_opus":0.017836670903878634,"score_gpt":0.2483582239684731,"score_spread":0.23052155306459446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142461803","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":[0.0038017435,0.0000665947,0.97243375,0.00017243261,0.0003138568,0.0002986971,0.000012748802,0.00028147746,0.02261868],"genre_scores_gemma":[0.97192097,0.000050862247,0.0009772101,0.00032935798,0.000030165145,0.00030870916,0.0000024490093,0.000050778297,0.026329473],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982232,0.000079710335,0.00047691146,0.00029242324,0.00051447557,0.000413316],"domain_scores_gemma":[0.9981854,0.000077846176,0.00021866638,0.00078607065,0.0005906672,0.00014138113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030243082,0.00022547171,0.00025833608,0.00021090925,0.00018334627,0.000035016856,0.00044858086,0.00014885323,0.00006587426],"category_scores_gemma":[0.00003723736,0.00017749942,0.00017493681,0.00060383003,0.000084482504,0.00027918097,0.000008067803,0.0001515473,0.0000047292233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000702399,0.0001639732,0.0000013676743,0.000028524548,0.00004546217,0.0000033782044,0.00025526644,0.96181357,0.0057567907,0.023834908,0.002137796,0.005888737],"study_design_scores_gemma":[0.00073927373,0.00016966059,0.0000010223324,0.000025092559,0.000040370767,0.0000060898365,0.001561505,0.13477989,0.82764024,0.009590607,0.025206687,0.00023954788],"about_ca_topic_score_codex":0.013141405,"about_ca_topic_score_gemma":0.00033306488,"teacher_disagreement_score":0.9714566,"about_ca_system_score_codex":0.00050255074,"about_ca_system_score_gemma":0.0004959768,"threshold_uncertainty_score":0.9934302},"labels":[],"label_agreement":null},{"id":"W2148634590","doi":"10.1109/tste.2011.2160374","title":"Design and Implementation of Neuro-Fuzzy Vector Control for Wind-Driven Doubly-Fed Induction Generator","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":87,"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":"Control theory (sociology); Induction generator; AC power; Vector control; Engineering; Rotor (electric); Wind power; Fuzzy control system; Slip ring; Wound rotor motor; Computer science; Voltage; Induction motor; Fuzzy logic; Control engineering; Electrical engineering; Control (management)","score_opus":0.014853557899503808,"score_gpt":0.21600111718245613,"score_spread":0.2011475592829523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148634590","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":[0.0639167,0.000083711304,0.93435025,0.00003270484,0.0005679257,0.0007496658,0.000022342454,0.0001630216,0.00011367775],"genre_scores_gemma":[0.99806094,0.000019766128,0.0010361337,0.0000335914,0.00011208055,0.00042844441,0.0000039974684,0.00006457609,0.0002404435],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99884796,0.00007009123,0.00035387123,0.00023358337,0.00013154079,0.00036294377],"domain_scores_gemma":[0.9993326,0.00010223374,0.00007752106,0.00020439447,0.00019026651,0.000092947994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015377655,0.00021232234,0.00027820526,0.0002676291,0.00012966071,0.000026756701,0.00009163108,0.00011534755,0.000042674827],"category_scores_gemma":[0.0000037608447,0.00022314025,0.00008241039,0.00020884888,0.000028488386,0.0002902377,7.4591276e-7,0.00009487871,0.0000010631051],"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":[0.00069005945,0.00014042848,0.000035541198,0.00034465408,0.00050351606,0.000015515423,0.0013480025,0.8433909,0.13823992,0.004763904,0.0006677606,0.0098598],"study_design_scores_gemma":[0.01177222,0.0019420232,0.00067719474,0.000035778674,0.0004460986,0.000034227975,0.0029078515,0.12801,0.8474387,0.0009011794,0.0049500875,0.0008846392],"about_ca_topic_score_codex":0.00067929237,"about_ca_topic_score_gemma":0.00004753312,"teacher_disagreement_score":0.93414426,"about_ca_system_score_codex":0.00013545055,"about_ca_system_score_gemma":0.000062187566,"threshold_uncertainty_score":0.9099395},"labels":[],"label_agreement":null},{"id":"W2161425028","doi":"10.1109/tste.2012.2235151","title":"System Stability Impact of Large-Scale and Distributed Solar Photovoltaic Generation: The Case of Ontario, Canada","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":324,"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":"Institut de Recherche pour le Développement","keywords":"Photovoltaic system; Electricity; Renewable energy; Stability (learning theory); Rooftop photovoltaic power station; Voltage; Distributed generation; Scale (ratio); Engineering; Computer science; Reliability engineering; Environmental science; Electrical engineering; Maximum power point tracking; Geography","score_opus":0.0051551780308219525,"score_gpt":0.18980686862905222,"score_spread":0.18465169059823028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161425028","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":[0.6723981,0.000051909003,0.32670343,0.000008943007,0.00011578677,0.00018089084,0.00042088088,0.00003797661,0.000082091334],"genre_scores_gemma":[0.99963605,0.000005964675,0.000049516522,0.0000040082505,0.000014646421,0.00008363545,0.000043707892,0.000018208288,0.00014423316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897224,0.000047346224,0.00033371008,0.00016706837,0.00013643774,0.00034321134],"domain_scores_gemma":[0.9991171,0.00005159534,0.000056250676,0.0003503736,0.0003200583,0.00010463266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013993494,0.00018126747,0.0002394037,0.000052250263,0.000185177,0.000028966033,0.000085050924,0.00008326773,0.00023840628],"category_scores_gemma":[0.0000034973134,0.0001471243,0.00009367013,0.00027509138,0.000051769213,0.00020639811,0.0000022476536,0.00015465367,3.7260216e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002905611,0.00011056868,0.00016610546,0.00028866326,0.00018531426,0.00008189635,0.00044158575,0.987303,0.0090450365,0.0001470074,0.0018701542,0.0003316051],"study_design_scores_gemma":[0.00085991155,0.0002783603,0.0009084332,0.00002900158,0.00013257087,0.00023366671,0.009233393,0.76094365,0.22578348,0.00002592827,0.0011883111,0.00038329893],"about_ca_topic_score_codex":0.9690713,"about_ca_topic_score_gemma":0.9310383,"teacher_disagreement_score":0.32723796,"about_ca_system_score_codex":0.0023740225,"about_ca_system_score_gemma":0.00063347555,"threshold_uncertainty_score":0.62079865},"labels":[],"label_agreement":null},{"id":"W2161888124","doi":"10.1109/tste.2011.2158457","title":"A Control Design Approach for Three-Phase Grid-Connected Renewable Energy Resources","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Decoupling (probability); Computer science; Filter (signal processing); Algorithm; Engineering; Control engineering; Computer vision","score_opus":0.01428323686663913,"score_gpt":0.18933372322048092,"score_spread":0.1750504863538418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161888124","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":[0.00011387479,0.0006004027,0.99529964,0.000013483532,0.00029409712,0.00039128598,0.00004200804,0.00064796244,0.0025972226],"genre_scores_gemma":[0.98078245,0.00013808544,0.013261986,0.00014170658,0.0001955025,0.0015144161,0.000031381336,0.00013771115,0.0037967733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982965,0.000067929584,0.00036561146,0.000385775,0.00015522924,0.0007289807],"domain_scores_gemma":[0.9990259,0.00013621186,0.000061485596,0.00038139292,0.00022814769,0.00016690945],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020365752,0.00034840265,0.0003643408,0.00036774442,0.00033521728,0.000072337294,0.00024357483,0.0002212881,0.00015337272],"category_scores_gemma":[0.000008530666,0.00035079927,0.00018864103,0.00046149627,0.00004864344,0.00027928397,0.0000011278007,0.00012003376,0.0000017827789],"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":[0.0007662306,0.00030951394,2.8832258e-7,0.00005950473,0.00021922709,0.000012733889,0.00017538117,0.9810619,0.0011474424,0.0007370178,0.0015769289,0.013933867],"study_design_scores_gemma":[0.004352667,0.0004262006,7.993466e-7,0.000009996513,0.00015265218,0.000009337516,0.00031412567,0.9273191,0.04177386,0.00089384796,0.024321478,0.0004259431],"about_ca_topic_score_codex":0.0026534759,"about_ca_topic_score_gemma":0.00027111938,"teacher_disagreement_score":0.98203766,"about_ca_system_score_codex":0.00016061173,"about_ca_system_score_gemma":0.00006237236,"threshold_uncertainty_score":0.9998944},"labels":[],"label_agreement":null},{"id":"W2170036927","doi":"10.1109/tste.2012.2230346","title":"Multiagent Stochastic Simulation of Minute-to-Minute Grid Operations and Control to Integrate Wind Generation Under AC Power Flow Constraints","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Power System Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hydro-Québec","funders":"","keywords":"Wind power; Grid; Automatic Generation Control; Computer science; Interconnection; Reliability (semiconductor); Power system simulation; Electric power system; Automatic frequency control; Electricity generation; Reliability engineering; Simulation; Computation; Real-time computing; Engineering; Power (physics); Electrical engineering; Telecommunications","score_opus":0.006983961489957405,"score_gpt":0.20225131572324448,"score_spread":0.19526735423328706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170036927","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":[0.046237413,0.000049841143,0.9518553,0.00014843457,0.0005350371,0.0008794909,0.000040477655,0.00013241351,0.000121567246],"genre_scores_gemma":[0.9956621,0.000008023336,0.002453577,0.00018334427,0.000060099446,0.00026110729,0.000018834819,0.000055885477,0.0012970235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985199,0.000070095346,0.0004594637,0.00031686114,0.00022788817,0.00040582335],"domain_scores_gemma":[0.99884707,0.00011550975,0.000038603856,0.0002737451,0.0005014514,0.00022363411],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013432837,0.00027333165,0.00028794425,0.00053815544,0.00017952302,0.000105458275,0.000101713464,0.00014080698,0.00022227126],"category_scores_gemma":[0.000024896422,0.0002858795,0.000059626967,0.00057757023,0.00004626285,0.000414752,0.0000019625888,0.00012894829,0.000026195874],"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":[0.000019486082,0.000057119767,4.9961534e-7,0.00002322533,0.0000868584,0.0000021024302,0.00055231765,0.98176,0.01412433,0.00015673431,0.00024555923,0.002971763],"study_design_scores_gemma":[0.00075925404,0.0001931561,0.000026715907,0.00003108722,0.000048777594,0.0000053519334,0.0007181467,0.98295105,0.014780567,0.000019265126,0.00019139478,0.000275212],"about_ca_topic_score_codex":0.00032867916,"about_ca_topic_score_gemma":0.00014886311,"teacher_disagreement_score":0.9494247,"about_ca_system_score_codex":0.0003530284,"about_ca_system_score_gemma":0.00008308304,"threshold_uncertainty_score":0.99995935},"labels":[],"label_agreement":null},{"id":"W2210662871","doi":"10.1109/tste.2015.2483489","title":"Long-Term Renewable Energy Planning Model for Remote Communities","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"Natural Resources Canada; University of Waterloo; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Renewable energy; Subsidy; Term (time); Energy planning; Electricity; Wind power; Environmental economics; Business; Computer science; Operations research; Environmental resource management; Engineering; Environmental science; Economics","score_opus":0.04484765815850878,"score_gpt":0.27294105026036525,"score_spread":0.22809339210185647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2210662871","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":[0.0045827893,0.0005882891,0.96447426,0.00011177062,0.0011317354,0.00021606739,0.00003465064,0.00071512914,0.02814529],"genre_scores_gemma":[0.739766,0.00008580132,0.0015684306,0.00041802693,0.00029299568,0.00034782974,0.00009558094,0.0002274645,0.25719786],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9957645,0.00030797673,0.00087138754,0.00069300656,0.00070747675,0.0016556308],"domain_scores_gemma":[0.9964307,0.00035071728,0.00027387173,0.0014564481,0.00084361405,0.0006446339],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006382793,0.0007485872,0.00081646605,0.00085629907,0.00096093,0.000255912,0.0008573175,0.00044372308,0.00008017867],"category_scores_gemma":[0.000026323249,0.0007861716,0.0004023822,0.0007594905,0.00019078619,0.00069063157,0.000015986114,0.00030375755,0.000011567697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049525604,0.00021868429,0.000007966075,0.00011204093,0.00023390933,0.00011297998,0.00096071366,0.9783194,0.00020960304,0.008721614,0.0039020698,0.006705773],"study_design_scores_gemma":[0.0029343439,0.00043737274,0.0000016032228,0.00018125561,0.00014292507,0.00009884043,0.005955071,0.8679382,0.03555021,0.008905518,0.076721855,0.0011327581],"about_ca_topic_score_codex":0.17686,"about_ca_topic_score_gemma":0.028144525,"teacher_disagreement_score":0.9629058,"about_ca_system_score_codex":0.0011289874,"about_ca_system_score_gemma":0.0008256329,"threshold_uncertainty_score":0.9994589},"labels":[],"label_agreement":null},{"id":"W2311854124","doi":"10.1109/tste.2015.2504504","title":"An Enhanced MPPT Method Combining Model-Based and Heuristic Techniques","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":55,"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":"Maximum power point tracking; Heuristic; Computer science; BitTorrent tracker; Photovoltaic system; Power (physics); Point (geometry); Computational complexity theory; Voltage; Set (abstract data type); Control theory (sociology); Algorithm; Engineering; Mathematics; Artificial intelligence","score_opus":0.01684325018571421,"score_gpt":0.2846044983056472,"score_spread":0.267761248119933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2311854124","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":[0.000999569,0.000045307672,0.9866547,0.00005480901,0.00010435697,0.00026516445,0.00000834584,0.001585136,0.010282603],"genre_scores_gemma":[0.89054394,0.000027735932,0.104185574,0.00043078396,0.0000317648,0.0006129794,0.000013801678,0.000101510166,0.004051915],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99769026,0.0003286166,0.00045594608,0.00059151795,0.00038308135,0.0005505552],"domain_scores_gemma":[0.99803835,0.00015336249,0.00014575724,0.000689776,0.0006021404,0.0003706169],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006428461,0.00036294298,0.00042331155,0.0005835241,0.0002974777,0.00012767302,0.00028269453,0.00027479298,0.000043097458],"category_scores_gemma":[0.000033383174,0.00038343272,0.00008633986,0.00058510056,0.00009511896,0.00047727703,0.0000035099613,0.00021947648,0.000002980232],"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":[0.00017602989,0.0002695044,7.375833e-7,0.00004856099,0.000033052936,0.000024827366,0.00033549455,0.9543219,0.011284094,0.014603175,0.0002537563,0.018648816],"study_design_scores_gemma":[0.00050360005,0.00034861817,2.0048036e-7,0.000028868202,0.000033974564,0.000009242435,0.0007638252,0.4149066,0.5739155,0.006125443,0.0030499583,0.00031419398],"about_ca_topic_score_codex":0.0043368465,"about_ca_topic_score_gemma":0.00016538441,"teacher_disagreement_score":0.88954437,"about_ca_system_score_codex":0.00042114072,"about_ca_system_score_gemma":0.00034916392,"threshold_uncertainty_score":0.9998618},"labels":[],"label_agreement":null},{"id":"W2314669240","doi":"10.1109/tste.2014.2356551","title":"Impact of Wind-Based Distributed Generation on Electric Energy in Distribution Systems Embedded With Electric Vehicles","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":54,"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":"Wind power; Penetration (warfare); Automotive engineering; Distributed generation; AC power; Wind speed; Electric power system; Electrical engineering; Voltage; Environmental science; Engineering; Computer science; Power (physics); Renewable energy; Physics; Meteorology","score_opus":0.0036354260868958887,"score_gpt":0.18984152749919253,"score_spread":0.18620610141229665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314669240","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":[0.39283168,0.00010900498,0.6065424,0.000009637588,0.000068486006,0.000112815476,0.00003436958,0.00013539483,0.0001561926],"genre_scores_gemma":[0.999338,0.000063831794,0.00002386892,0.000019926898,0.0000947533,0.00007798631,0.00017391374,0.000063518426,0.00014423272],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980435,0.00012539307,0.0004331205,0.00033851547,0.00033848992,0.00072099274],"domain_scores_gemma":[0.9990768,0.00011543118,0.00010515226,0.00036015772,0.00021794662,0.00012454395],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015160404,0.00037688788,0.00041304546,0.00059439725,0.00014843667,0.000063298925,0.00016335762,0.00024921363,0.000016394446],"category_scores_gemma":[0.000009569409,0.00032539607,0.00014422924,0.0022820237,0.000022429353,0.00019462874,7.0295533e-7,0.00031533616,0.0000010202486],"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":[0.00019039828,0.0001620817,0.000048937796,0.00005499234,0.00007942397,0.000010097275,0.000012782356,0.96227545,0.026153388,0.00263882,0.00035947582,0.008014145],"study_design_scores_gemma":[0.0011420571,0.0014950818,0.0008091154,0.00003589199,0.00003920582,0.000009770709,0.000028519375,0.79686785,0.19854002,0.00009438331,0.0005956312,0.0003424721],"about_ca_topic_score_codex":0.0014058817,"about_ca_topic_score_gemma":0.000077065975,"teacher_disagreement_score":0.60651857,"about_ca_system_score_codex":0.0012404444,"about_ca_system_score_gemma":0.00019558427,"threshold_uncertainty_score":0.99991983},"labels":[],"label_agreement":null},{"id":"W2314775828","doi":"10.1109/tste.2016.2530740","title":"A Unified Approach to the Power Flow Analysis of AC/DC Hybrid Microgrids","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":145,"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":"Ministry of Higher Education","keywords":"Voltage droop; Converters; Computer science; Controllability; AC power; Network topology; Power (physics); Islanding; Smart grid; Topology (electrical circuits); Control theory (sociology); Distributed generation; Control engineering; Electronic engineering; Electrical engineering; Engineering; Voltage; Voltage source; Control (management); Mathematics; Renewable energy","score_opus":0.003967239727779018,"score_gpt":0.17331345096485024,"score_spread":0.16934621123707122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314775828","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":[0.0054851854,0.0002086471,0.9914661,0.00019782342,0.00017202461,0.00013907345,0.000053969845,0.00014432345,0.0021328388],"genre_scores_gemma":[0.99436635,0.0002053046,0.0008984062,0.0001052541,0.000028281014,0.000108150125,0.000007362459,0.00003446972,0.004246412],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989247,0.0000395528,0.00026250444,0.00022565105,0.00017006346,0.0003775588],"domain_scores_gemma":[0.99918544,0.00006632013,0.00003132911,0.0004538399,0.00017411342,0.00008897287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000144569,0.00018551847,0.0002709253,0.00054206,0.00011934055,0.000033484484,0.00023148334,0.00006477416,0.0001431492],"category_scores_gemma":[0.0000046231553,0.00012005186,0.00022497101,0.0013210541,0.000034322402,0.00012321217,0.000001950114,0.00007860019,0.000007113519],"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":[0.000047679965,0.00008429668,8.906342e-7,0.000013115898,0.0006720494,0.0000028646007,0.00014534577,0.96779895,0.0029138695,0.00038568382,0.00073201826,0.027203234],"study_design_scores_gemma":[0.001601471,0.0002043966,0.00009697057,0.000028767296,0.0015344636,0.000010492309,0.0013989607,0.65031147,0.20309225,0.00012865532,0.14082174,0.0007703619],"about_ca_topic_score_codex":0.00014572305,"about_ca_topic_score_gemma":0.00004431528,"teacher_disagreement_score":0.9905677,"about_ca_system_score_codex":0.00013573255,"about_ca_system_score_gemma":0.00003405999,"threshold_uncertainty_score":0.4895573},"labels":[],"label_agreement":null},{"id":"W2320639967","doi":"10.1109/tste.2016.2543024","title":"Optimal Control of Energy Storage in a Microgrid by Minimizing Conditional Value-at-Risk","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":139,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"CVAR; Microgrid; Mathematical optimization; Expected shortfall; Stochastic optimization; Stochastic control; Computer science; Electricity; Demand response; Electricity pricing; Energy storage; Optimal control; Optimization problem; Electricity market; Control (management); Engineering; Power (physics); Economics; Mathematics; Risk management","score_opus":0.003154841162092742,"score_gpt":0.1756939718664597,"score_spread":0.17253913070436697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2320639967","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":[0.056299955,0.00045304876,0.94121736,0.00010347425,0.0003978156,0.0000923772,0.00018182381,0.00019411152,0.0010600548],"genre_scores_gemma":[0.99249387,0.0005740273,0.0003492977,0.000090217225,0.00006271864,0.00024853658,0.00001597596,0.00008118433,0.00608416],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980814,0.000098666016,0.00047686597,0.0003623863,0.00030975873,0.0006709601],"domain_scores_gemma":[0.9990744,0.00025703874,0.00008675676,0.00036326193,0.00008825791,0.00013031145],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019113418,0.0003200489,0.00036508185,0.0005265052,0.00012740091,0.000019998763,0.00022646433,0.00015207965,0.00031411264],"category_scores_gemma":[0.000007708191,0.00029904768,0.00016295673,0.0004053033,0.00010381896,0.00025797312,0.0000045530596,0.00012630654,0.000007760919],"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":[0.00013999769,0.00015755913,0.000023358043,0.000039051913,0.00019865509,0.00005587203,0.00003849361,0.9775713,0.012528148,0.002994716,0.003735529,0.002517319],"study_design_scores_gemma":[0.009455751,0.0004411275,0.0002176495,0.00013948516,0.00020796145,0.00002629029,0.00071997184,0.14186169,0.52565074,0.000623137,0.3193532,0.0013029806],"about_ca_topic_score_codex":0.0007651708,"about_ca_topic_score_gemma":0.0001272326,"teacher_disagreement_score":0.940868,"about_ca_system_score_codex":0.0008561372,"about_ca_system_score_gemma":0.00004928222,"threshold_uncertainty_score":0.9999462},"labels":[],"label_agreement":null},{"id":"W2321944543","doi":"10.1109/tste.2014.2339172","title":"Optimal Incentive Design for Targeted Penetration of Renewable Energy Sources","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Power System Optimization","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"IBM Canada; ABB","keywords":"Renewable energy; Incentive; Environmental economics; Energy conservation; Portfolio; Time horizon; Electricity; Market penetration; Wind power; Electricity generation; Distributed generation; Business; Economics; Engineering; Microeconomics; Finance","score_opus":0.005932198490464514,"score_gpt":0.18739253293411784,"score_spread":0.18146033444365334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2321944543","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":[0.0010948594,0.00017787263,0.99640197,0.00001263757,0.00030349716,0.00019774683,0.000007171242,0.00025038607,0.001553882],"genre_scores_gemma":[0.98323095,0.00007784622,0.009995444,0.000021113012,0.000055150493,0.00028715594,0.000017417762,0.00006810222,0.006246808],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986531,0.00009623807,0.0003649866,0.0002462284,0.00019524647,0.0004441966],"domain_scores_gemma":[0.9990789,0.00021656814,0.00008953492,0.00024807063,0.00028873692,0.00007813232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024579567,0.00021957573,0.00026968296,0.00037863987,0.0001740989,0.000039772705,0.00015573307,0.0001609445,0.000036251637],"category_scores_gemma":[0.000014660022,0.00024413635,0.000102781385,0.0005764431,0.0000293609,0.00028790472,8.9096807e-7,0.000067728775,9.285423e-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":[0.00008373342,0.00005893212,5.424796e-7,0.00008329252,0.00007580845,8.758991e-7,0.00011696944,0.9899493,0.005539346,0.0014016841,0.0009524589,0.0017370764],"study_design_scores_gemma":[0.00042490422,0.00025183478,0.0000010133938,0.000014830578,0.00003311225,0.0000015024664,0.00017345013,0.53680986,0.45594764,0.00026706237,0.005903903,0.00017090396],"about_ca_topic_score_codex":0.00091372733,"about_ca_topic_score_gemma":0.000097267606,"teacher_disagreement_score":0.9864065,"about_ca_system_score_codex":0.00023443962,"about_ca_system_score_gemma":0.00007732097,"threshold_uncertainty_score":0.99555916},"labels":[],"label_agreement":null},{"id":"W2325574851","doi":"10.1109/tste.2014.2334696","title":"A Control Strategy for Power Regulation in a Direct-Drive WECS With Flexible Drive-Train","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":29,"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":"Control theory (sociology); Train; Wind power; Power (physics); Engineering; Drivetrain; Power control; Permanent magnet synchronous generator; Electric power system; Control engineering; Control (management); Computer science; Torque; Voltage; Electrical engineering","score_opus":0.0048154467440442205,"score_gpt":0.1939073334612466,"score_spread":0.1890918867172024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2325574851","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":[0.009063898,0.00006281886,0.9775072,0.0000985438,0.00024701896,0.0006345877,0.000019986921,0.00042899165,0.0119369775],"genre_scores_gemma":[0.9915895,0.0000041978396,0.00018772332,0.00005883951,0.00009417518,0.0008587454,0.0000071465392,0.0000962421,0.0071034343],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983423,0.00008189217,0.00035425086,0.00034804383,0.0002106161,0.0006629151],"domain_scores_gemma":[0.9990593,0.0002226426,0.0000566454,0.00035824982,0.00018315854,0.000119958626],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026365218,0.00031085068,0.00042139474,0.00043275533,0.00013257668,0.00007550659,0.00014224103,0.0001785919,0.000045788034],"category_scores_gemma":[0.000009318351,0.00029550336,0.00011221731,0.0004754426,0.000037597776,0.00031201646,5.507283e-7,0.00017718173,0.000005279639],"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":[0.00024603828,0.000077874,0.0000090844505,0.00008605418,0.00009696196,0.000011746723,0.00015282938,0.9866536,0.0016814306,0.008232143,0.00024100773,0.0025111914],"study_design_scores_gemma":[0.013269017,0.0015627763,0.00062601425,0.0001722429,0.00014319771,0.000031366453,0.001487454,0.88507026,0.024680622,0.0023270093,0.06942613,0.0012039258],"about_ca_topic_score_codex":0.0005188215,"about_ca_topic_score_gemma":0.00052445155,"teacher_disagreement_score":0.9825256,"about_ca_system_score_codex":0.00036793065,"about_ca_system_score_gemma":0.00008063174,"threshold_uncertainty_score":0.9999497},"labels":[],"label_agreement":null},{"id":"W2326041979","doi":"10.1109/tste.2014.2345059","title":"Wind Turbine Power Curve Modeling Using Advanced Parametric and Nonparametric Methods","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":227,"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 Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Manitoba Hydro","keywords":"Polynomial regression; Wind power; Nonparametric regression; Turbine; Spline (mechanical); Curve fitting; Parametric statistics; Regression analysis; Nonparametric statistics; Wind power forecasting; Semiparametric regression; Multivariate adaptive regression splines; Local regression; Polynomial; Computer science; Regression; Statistics; Mathematics; Engineering; Power (physics); Electric power system","score_opus":0.013917923202634148,"score_gpt":0.26999652443620586,"score_spread":0.25607860123357173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2326041979","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":[0.12894852,0.0005070261,0.867726,0.00001695446,0.00027178338,0.0000868513,0.0000018510641,0.00020343141,0.0022375537],"genre_scores_gemma":[0.9632046,0.000267335,0.034937404,0.000050492676,0.000033601493,0.00003371103,0.0000021153166,0.00006973889,0.0014009678],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812204,0.00011246475,0.00030950757,0.00036519894,0.00029292845,0.00079786114],"domain_scores_gemma":[0.99893665,0.00026666367,0.000026438076,0.00031798214,0.00016198575,0.0002903011],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00048612195,0.00029633808,0.00032481176,0.0012244665,0.0002698113,0.00009890811,0.00015027492,0.0001546801,0.00006127548],"category_scores_gemma":[0.000052525207,0.0002964092,0.00008497759,0.0018923456,0.000042221178,0.00033162846,0.0000046454193,0.00030896475,0.000004076257],"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":[0.0000328281,0.00004191116,0.0000021595984,0.00004659858,0.000060466027,0.000010727605,0.000047828973,0.93466073,0.0006635822,0.00041977235,0.000017713946,0.06399569],"study_design_scores_gemma":[0.00062678836,0.00012447807,0.000011882984,0.000020080632,0.000021205029,0.000017569773,0.00033358668,0.9743332,0.017161498,0.0007969564,0.006170832,0.00038189476],"about_ca_topic_score_codex":0.00029672083,"about_ca_topic_score_gemma":0.000008545385,"teacher_disagreement_score":0.8342561,"about_ca_system_score_codex":0.00031382844,"about_ca_system_score_gemma":0.0000727034,"threshold_uncertainty_score":0.9999488},"labels":[],"label_agreement":null},{"id":"W2328102190","doi":"10.1109/tste.2014.2337053","title":"Stability Analysis of Converter-Connected Battery Energy Storage Systems in the Grid","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":63,"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 Manitoba","funders":"","keywords":"Internal resistance; Battery (electricity); Energy storage; Electrical engineering; Engineering; State of charge; Grid; Voltage; Power (physics); Electric power system; Automotive engineering; Control theory (sociology); Computer science; Physics","score_opus":0.010109795646088245,"score_gpt":0.22032252997895493,"score_spread":0.2102127343328667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328102190","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":[0.08343344,0.000099210294,0.915101,0.00007104779,0.00022414255,0.00011135331,0.000028651215,0.00026305212,0.00066811603],"genre_scores_gemma":[0.9992317,0.000083773564,0.000036237296,0.000053140637,0.000020802796,0.0002383725,0.0000120238965,0.000032444183,0.00029149523],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981205,0.00024003531,0.00042090716,0.00030835072,0.00034616122,0.00056403474],"domain_scores_gemma":[0.99823135,0.0006108708,0.00005126441,0.0009044981,0.00015145769,0.00005055387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004080721,0.00022646716,0.0004536318,0.0010502503,0.00009859414,0.000040394192,0.00049994973,0.00016512076,0.000095536314],"category_scores_gemma":[0.000026488815,0.00019054575,0.00015131432,0.0027043147,0.00012780596,0.00020665163,0.000004191629,0.0003075627,0.0000015560126],"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":[0.000029025077,0.000111958725,0.00003339675,0.00011518479,0.00027658406,0.000020282521,0.00013652311,0.9892761,0.0017030981,0.0025483444,0.00011665983,0.0056328285],"study_design_scores_gemma":[0.00054814667,0.00018716863,0.00040054735,0.00002164955,0.00017900171,0.0000048313004,0.0061436873,0.93988043,0.041633524,0.0003650371,0.010251703,0.0003842635],"about_ca_topic_score_codex":0.002104416,"about_ca_topic_score_gemma":0.0006887444,"teacher_disagreement_score":0.91579825,"about_ca_system_score_codex":0.0003742267,"about_ca_system_score_gemma":0.000031354422,"threshold_uncertainty_score":0.777023},"labels":[],"label_agreement":null},{"id":"W2328710506","doi":"10.1109/tste.2014.2336773","title":"Distance Protection of Lines Connected to Induction Generator-Based Wind Farms During Balanced Faults","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":152,"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":"Crowbar; Tripping; Relay; Protective relay; Generator (circuit theory); Computer science; Fault (geology); Reliability engineering; Grid; Wind power; Induction generator; Power-system protection; Electrical engineering; Control theory (sociology); Engineering; Circuit breaker; Voltage; Electric power system; Mathematics; Power (physics)","score_opus":0.005730243653039223,"score_gpt":0.19446882977296465,"score_spread":0.18873858611992542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328710506","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":[0.39029267,0.000015539666,0.6080367,0.00002544998,0.0008346051,0.00024554066,0.0000068688128,0.00039770638,0.00014490288],"genre_scores_gemma":[0.99810946,0.00000521501,0.00021247711,0.000020829175,0.00017885647,0.00027980946,0.0000043092737,0.00007773649,0.0011112946],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998395,0.00008753624,0.0004318841,0.0003591392,0.0002782129,0.00044818572],"domain_scores_gemma":[0.9990413,0.000035757268,0.000086679094,0.00041180264,0.0002904575,0.00013398076],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015690818,0.00028617983,0.0003113623,0.0005375388,0.0002180441,0.00003202103,0.00013019245,0.00020153054,0.000018797142],"category_scores_gemma":[0.000023752398,0.00031432425,0.000099270925,0.0010331097,0.000029588375,0.0002554047,0.0000011763294,0.00021491079,0.0000074525246],"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":[0.00015418691,0.000056005785,0.0000068035088,0.00025843005,0.000039814586,0.0000032297537,0.000102172606,0.76991624,0.22205222,0.00006701692,0.000018970963,0.0073249126],"study_design_scores_gemma":[0.0009307753,0.00022867678,0.00017343363,0.00008892285,0.00002146242,0.000008981615,0.00029008277,0.08650105,0.8965408,0.000032208878,0.014831717,0.0003518992],"about_ca_topic_score_codex":0.00046939735,"about_ca_topic_score_gemma":0.00024181948,"teacher_disagreement_score":0.6834152,"about_ca_system_score_codex":0.00048902445,"about_ca_system_score_gemma":0.000040630828,"threshold_uncertainty_score":0.99993086},"labels":[],"label_agreement":null},{"id":"W2335621649","doi":"10.1109/tste.2014.2329647","title":"Management Scheme for Increasing the Connectivity of Small-Scale Renewable DG","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":29,"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":"Capacity planning; Renewable energy; Photovoltaic system; Scalability; Nameplate capacity; Scheme (mathematics); Computer science; Capacity optimization; Distributed generation; Mathematical optimization; Reliability engineering; Power (physics); Electricity generation; Engineering; Mathematics; Electrical engineering","score_opus":0.005836750330151486,"score_gpt":0.1952889327458591,"score_spread":0.1894521824157076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2335621649","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":[0.04669429,0.00003724031,0.94600683,0.00008107026,0.00024500964,0.00023147283,0.000021082462,0.000177423,0.0065055606],"genre_scores_gemma":[0.9944807,0.000035790057,0.0030958317,0.000028212733,0.00003851546,0.00020036112,0.000008670797,0.000037937454,0.0020739299],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990193,0.00005147784,0.00021497054,0.00019199516,0.000128038,0.0003942121],"domain_scores_gemma":[0.9992217,0.00020108475,0.00003789981,0.00035549563,0.0001268836,0.00005698287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042158292,0.00016633689,0.0001839226,0.000117917065,0.00022676814,0.000034091805,0.00016630952,0.00008227067,0.000021286021],"category_scores_gemma":[0.000009539083,0.00015325399,0.00011825966,0.00031005606,0.000050286566,0.00012880091,0.00000243423,0.00009534776,0.0000017472283],"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":[0.00010871431,0.00010295583,0.0000047627777,0.0002645962,0.00010385875,0.0000017649713,0.0000457116,0.98067117,0.0026077805,0.007614755,0.0004872993,0.007986604],"study_design_scores_gemma":[0.001669906,0.00036258693,0.00012579736,0.00007989537,0.00018397733,0.000009455789,0.001833071,0.52669036,0.3517638,0.0035119555,0.11322073,0.00054841687],"about_ca_topic_score_codex":0.00077289983,"about_ca_topic_score_gemma":0.00016594572,"teacher_disagreement_score":0.94778645,"about_ca_system_score_codex":0.00021522911,"about_ca_system_score_gemma":0.000017800845,"threshold_uncertainty_score":0.62495166},"labels":[],"label_agreement":null},{"id":"W2346539864","doi":"10.1109/tste.2016.2564105","title":"Fractional-Order Sliding-Mode Control of Islanded Distributed Energy Resource Systems","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":125,"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":"Control theory (sociology); Controller (irrigation); Dispatchable generation; Grid; Sliding mode control; Distributed generation; Computer science; Control engineering; PID controller; Voltage; Engineering; Control (management); Temperature control; Renewable energy; Electrical engineering; Nonlinear system","score_opus":0.0030479778844703024,"score_gpt":0.17609182578750976,"score_spread":0.17304384790303945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2346539864","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":[0.0003432994,0.000580327,0.9968796,0.00013481938,0.000373068,0.00010173866,0.00016710901,0.00028927383,0.0011307788],"genre_scores_gemma":[0.9935785,0.00043662233,0.0000567846,0.00004791214,0.000103054255,0.00014544693,0.000023249046,0.00005607999,0.0055523803],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859804,0.00006706144,0.00039804092,0.00024542236,0.00023969477,0.00045172198],"domain_scores_gemma":[0.9989742,0.00020762491,0.000083698586,0.00031277692,0.00031484227,0.00010685695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000101806785,0.0002449175,0.00032800602,0.00027010226,0.00014902235,0.00003729723,0.00014777972,0.00018231904,0.00013080727],"category_scores_gemma":[0.000010708286,0.00019887407,0.00012428121,0.00042628462,0.000035725003,0.00023574235,0.0000010999526,0.00009742004,0.000004608316],"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":[0.00015171447,0.00007416865,0.0000020887278,0.00004593893,0.00018385328,0.00000992426,0.000023364242,0.9823581,0.005753893,0.005571348,0.0012540938,0.0045715133],"study_design_scores_gemma":[0.004326157,0.00015985014,0.000009126148,0.0001033988,0.00014355377,0.000023449282,0.0005008166,0.68113554,0.041134313,0.00037538804,0.2715201,0.00056828366],"about_ca_topic_score_codex":0.0005801407,"about_ca_topic_score_gemma":0.00004468528,"teacher_disagreement_score":0.9968228,"about_ca_system_score_codex":0.00026775236,"about_ca_system_score_gemma":0.00006234794,"threshold_uncertainty_score":0.8109849},"labels":[],"label_agreement":null},{"id":"W2392792036","doi":"10.1109/tste.2016.2569022","title":"An Analytical Method to Obtain Maximum Allowable Grid Support by Using Grid-Connected Converters","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":53,"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":"Converters; Grid; AC power; Voltage; Control theory (sociology); Range (aeronautics); Computer science; Three-phase; Maximum power principle; Set (abstract data type); Engineering; Mathematical optimization; Control (management); Mathematics; Electrical engineering","score_opus":0.007007890939874718,"score_gpt":0.23247783459530635,"score_spread":0.22546994365543163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2392792036","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":[0.003298633,0.000041969455,0.9947178,0.00025445578,0.0005362661,0.00018523334,0.000094579016,0.00048250507,0.000388592],"genre_scores_gemma":[0.9827297,0.00013173217,0.010151169,0.00077401707,0.00024585397,0.00012486221,0.000049135513,0.00017397292,0.0056195683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980809,0.00010166968,0.00035998056,0.0004353986,0.00021914094,0.0008028732],"domain_scores_gemma":[0.9989065,0.00010187817,0.000033351076,0.00040153365,0.0001869233,0.0003698434],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025046093,0.00032145757,0.0003399855,0.00037505792,0.00019551876,0.000090284084,0.000227715,0.00018132586,0.00073326245],"category_scores_gemma":[0.0000068835816,0.00028127438,0.00012587607,0.0005706799,0.00003391058,0.00050099316,0.000001995708,0.00012746418,0.000022426375],"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":[0.000115578616,0.00011011643,0.0000031784118,0.000026484904,0.00013813809,0.000042765198,0.000074211755,0.9030626,0.049346376,0.00017718627,0.0047180043,0.04218537],"study_design_scores_gemma":[0.0018576308,0.0003787777,0.000004903776,0.000028860519,0.00016217462,0.00003282011,0.00053083064,0.74305636,0.15784648,0.00017939176,0.095117755,0.0008040102],"about_ca_topic_score_codex":0.0005097688,"about_ca_topic_score_gemma":0.000052692365,"teacher_disagreement_score":0.98456657,"about_ca_system_score_codex":0.00049326586,"about_ca_system_score_gemma":0.000093894785,"threshold_uncertainty_score":0.99996394},"labels":[],"label_agreement":null},{"id":"W2396312483","doi":"10.1109/tste.2016.2569425","title":"Practical Strategies for Storage Operation in Energy Systems: Design and Evaluation","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":30,"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":"Computer science; Tariff; Energy storage; Context (archaeology); Grid; Payment; Distributed generation; Electricity generation; Demand response; Photovoltaic system; Mathematical optimization; Reliability engineering; Operations research; Renewable energy; Electricity; Power (physics); Engineering; Electrical engineering; Economics","score_opus":0.024835496476767863,"score_gpt":0.2604470144705332,"score_spread":0.23561151799376534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2396312483","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":[0.0018318328,0.00017246052,0.9961432,0.00018134476,0.0005290584,0.00034160833,0.0000034140958,0.00017136728,0.0006257003],"genre_scores_gemma":[0.99476707,0.00030115727,0.0014040516,0.000029898698,0.000075154494,0.0016593833,0.0000035042203,0.00004985266,0.001709938],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99869025,0.00014569535,0.00026693527,0.00027980702,0.00023952937,0.0003777624],"domain_scores_gemma":[0.9992553,0.0002871884,0.000028875473,0.00021879988,0.00014101723,0.00006884254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054966746,0.0001975207,0.00017539866,0.00035190434,0.0001164157,0.00012761037,0.000067789966,0.000115988005,0.000033116074],"category_scores_gemma":[0.000011881205,0.00017043234,0.00003472726,0.00020414428,0.000030661256,0.0008023728,0.0000013902962,0.00005779682,0.0000017620148],"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":[0.00005998558,0.00004501842,2.9841715e-7,0.000055788612,0.00004393901,0.000010822553,0.00004912083,0.9520663,0.0007429182,0.039932445,0.000967948,0.006025408],"study_design_scores_gemma":[0.0011983641,0.00015932327,0.000007765563,0.000039995048,0.000049863884,0.0000069495422,0.0015505903,0.9727034,0.0067725373,0.0013702702,0.015881667,0.00025924738],"about_ca_topic_score_codex":0.000308868,"about_ca_topic_score_gemma":0.00013391228,"teacher_disagreement_score":0.9947392,"about_ca_system_score_codex":0.00063299324,"about_ca_system_score_gemma":0.0001400244,"threshold_uncertainty_score":0.6950029},"labels":[],"label_agreement":null},{"id":"W2407187696","doi":"10.1109/tste.2016.2571563","title":"Optimal Secondary Distribution System Design Considering Rooftop Solar Photovoltaics","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":18,"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":"Photovoltaics; Photovoltaic system; Mathematical optimization; Computer science; Distribution (mathematics); Building-integrated photovoltaics; Subdivision; Architectural engineering; Engineering; Civil engineering; Electrical engineering; Mathematics","score_opus":0.00744988300301986,"score_gpt":0.18720508242547518,"score_spread":0.17975519942245533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2407187696","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":[0.009662242,0.00013699227,0.9869338,0.000055032415,0.0007478773,0.00023694526,0.0002633037,0.0012518255,0.0007119755],"genre_scores_gemma":[0.99710405,0.000087982866,0.0010893436,0.000019976345,0.00007370648,0.00019422155,0.000032678745,0.00008618909,0.0013118769],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979732,0.00007852652,0.00041323493,0.00038868672,0.0002972864,0.0008490514],"domain_scores_gemma":[0.99892163,0.00016979709,0.000053016865,0.00043002705,0.00021263334,0.00021288398],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002800929,0.00037687845,0.00030889758,0.00017671003,0.00034273617,0.00010386177,0.00020529695,0.00024987428,0.0001545781],"category_scores_gemma":[0.000011378638,0.0003454032,0.00015879508,0.0003943699,0.00008405466,0.000618293,0.000003499099,0.00025055293,0.000053955555],"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":[0.00014978551,0.00008887355,0.0000015296973,0.0002465779,0.00016326614,0.00020240921,0.000046195735,0.95229477,0.022426957,0.0026296533,0.0039720847,0.017777877],"study_design_scores_gemma":[0.0013799671,0.0002734649,0.00000848857,0.00015454399,0.000091501,0.00011139653,0.0011890951,0.09790369,0.8501467,0.00014067435,0.047846228,0.0007542372],"about_ca_topic_score_codex":0.000110463225,"about_ca_topic_score_gemma":0.000011359961,"teacher_disagreement_score":0.9874418,"about_ca_system_score_codex":0.0017076614,"about_ca_system_score_gemma":0.00015067587,"threshold_uncertainty_score":0.9998998},"labels":[],"label_agreement":null},{"id":"W2499015274","doi":"10.1109/tste.2016.2598265","title":"Estimating the Price Impact of Proposed Wind Farms in Competitive Electricity Markets","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Power System Optimization","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 Calgary","funders":"","keywords":"Electricity; Wind power; Electricity market; Electricity price; Electricity retailing; Electricity generation; Grid; Electricity price forecasting; Stand-alone power system; Environmental economics; Offshore wind power; Renewable energy; Business; Environmental science; Natural resource economics; Economics; Econometrics; Engineering; Distributed generation; Power (physics); Electrical engineering; Mathematics","score_opus":0.0037995282291013537,"score_gpt":0.20542203338581502,"score_spread":0.20162250515671368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2499015274","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":[0.08728269,0.00006626575,0.9081838,0.000037920923,0.00013300567,0.00026783656,0.000006236741,0.00012779822,0.0038944334],"genre_scores_gemma":[0.9984087,0.00003436983,0.0003889742,0.0000072327093,0.000020237223,0.000035920417,8.6188106e-7,0.00003922443,0.0010644828],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986992,0.0001122938,0.00032995778,0.00018526812,0.00019885921,0.0004744428],"domain_scores_gemma":[0.99915856,0.00029770783,0.00007486297,0.0002575539,0.00015879486,0.00005252403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028791552,0.00019263545,0.00022552743,0.00034204946,0.00009390198,0.00002143729,0.00017881447,0.00009166587,0.00006263415],"category_scores_gemma":[0.000026804899,0.000121963254,0.0000983793,0.001111572,0.000039100505,0.00023657441,0.0000011974901,0.00014711496,0.0000024775181],"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":[0.0000723395,0.00008224957,0.00006722879,0.000057995894,0.00008237626,0.000012075587,0.00018552964,0.9881843,0.003957266,0.00048069365,0.00003814999,0.0067798276],"study_design_scores_gemma":[0.0027502629,0.000650096,0.0030950129,0.00033590925,0.000064682776,0.000051811516,0.0005219484,0.78579915,0.20474492,0.00083783054,0.00039537752,0.0007529849],"about_ca_topic_score_codex":0.00036236964,"about_ca_topic_score_gemma":0.000045537607,"teacher_disagreement_score":0.911126,"about_ca_system_score_codex":0.0009226542,"about_ca_system_score_gemma":0.00014729062,"threshold_uncertainty_score":0.49735174},"labels":[],"label_agreement":null},{"id":"W2523134030","doi":"10.1109/tste.2016.2612121","title":"Power Ramp Limitation Capabilities of Large PV Power Plants With Active Power Reserves","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":64,"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 Manitoba","funders":"","keywords":"Power (physics); Electrical engineering; AC power; Electricity generation; Base load power plant; Engineering; Environmental science; Automotive engineering; Distributed generation; Renewable energy; Voltage; Physics","score_opus":0.0075231008415805,"score_gpt":0.22708490548859867,"score_spread":0.21956180464701816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2523134030","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":[0.22261418,0.00008129359,0.7405035,0.0003246354,0.00029531735,0.0005854006,0.00023449391,0.00071843294,0.03464276],"genre_scores_gemma":[0.9681694,0.00006570083,0.000595969,0.00010346009,0.000014664617,0.00036631193,0.0000120927725,0.00010322254,0.030569183],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9973006,0.00026519125,0.00057288137,0.00055450446,0.00059823407,0.0007085771],"domain_scores_gemma":[0.99738187,0.00054191507,0.00029457282,0.0007933146,0.0008323166,0.00015602044],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00031835298,0.000396806,0.00047806132,0.00064742926,0.00025450793,0.000043416134,0.00031713257,0.00028281801,0.001191122],"category_scores_gemma":[0.00006521537,0.00028972133,0.00016919618,0.00051033776,0.00021008204,0.0008742355,0.0000061211817,0.0001530701,0.000018447972],"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":[0.018224737,0.009096393,0.00053725246,0.0010026149,0.004058009,0.000613123,0.027834825,0.19105676,0.1520753,0.57187617,0.016078783,0.0075460193],"study_design_scores_gemma":[0.00214822,0.0011814239,0.00019343474,0.00028010743,0.00003764952,0.000022589678,0.018846842,0.00008484744,0.9441996,0.0026933055,0.029694559,0.00061739597],"about_ca_topic_score_codex":0.0020774393,"about_ca_topic_score_gemma":0.0006016421,"teacher_disagreement_score":0.79212433,"about_ca_system_score_codex":0.0005097422,"about_ca_system_score_gemma":0.00026483485,"threshold_uncertainty_score":0.9999555},"labels":[],"label_agreement":null},{"id":"W2526713913","doi":"10.1109/tste.2016.2614397","title":"Electric Vehicle Charging Facility as a Smart Energy Microhub","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":36,"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":"Majmaah University","keywords":"Electric vehicle; Renewable energy; Distributed generation; Smart grid; Energy storage; Computer science; Reliability engineering; Automotive engineering; Photovoltaic system; Electric power system; Engineering; Grid; Power (physics); Electrical engineering","score_opus":0.0033704681771042767,"score_gpt":0.1757023198990084,"score_spread":0.17233185172190413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526713913","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":[0.12909609,0.0005896374,0.86259055,0.00029366105,0.00038694046,0.000104127415,0.000025745985,0.0008052981,0.0061079576],"genre_scores_gemma":[0.9811853,0.0005630344,0.000043106567,0.00024588683,0.00007494906,0.00008373335,0.000002731107,0.00005564451,0.017745586],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998089,0.00004711485,0.00029924227,0.00038048442,0.00023897651,0.0009451753],"domain_scores_gemma":[0.999143,0.00009504169,0.000035452056,0.0004069624,0.00012536751,0.00019415337],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010294508,0.0003295433,0.00026724942,0.00036652203,0.0002815554,0.00005708326,0.00023366424,0.00021301574,0.00054858014],"category_scores_gemma":[0.000006131675,0.00026972243,0.00016436871,0.0008273642,0.00003653089,0.00033553893,0.0000020667355,0.00021929637,0.000052025145],"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":[0.00015055957,0.00014527566,0.000023904593,0.00009843799,0.00024768722,0.00013075159,0.00013542357,0.043058965,0.38246092,0.008735037,0.0044646203,0.5603484],"study_design_scores_gemma":[0.00083904085,0.00021237701,0.000049704297,0.00002319729,0.00003322984,0.00004806261,0.00012553704,0.0076820217,0.80460864,0.002764757,0.1830762,0.0005372237],"about_ca_topic_score_codex":0.0008028468,"about_ca_topic_score_gemma":0.000055296627,"teacher_disagreement_score":0.86254746,"about_ca_system_score_codex":0.00055975805,"about_ca_system_score_gemma":0.00010375565,"threshold_uncertainty_score":0.9999755},"labels":[],"label_agreement":null},{"id":"W2549753853","doi":"10.1109/tste.2016.2632116","title":"Real-Time Integration of Intermittent Generation With Voltage Rise Considerations","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":9,"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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Renewable energy; Grid; Voltage; Computer science; Leverage (statistics); Population; Distributed generation; Demand response; Electric power system; Distributed computing; Electricity; Engineering; Power (physics); Electrical engineering; Mathematics","score_opus":0.007469111847622333,"score_gpt":0.2011018938603645,"score_spread":0.19363278201274217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2549753853","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":[0.077027954,0.000012198741,0.9201178,0.00009761851,0.00017168983,0.00014761566,0.00006393014,0.0002578675,0.002103358],"genre_scores_gemma":[0.9947657,0.00010900931,0.00088185375,0.000011652182,0.000045339737,0.00010799039,0.000019643416,0.0000407847,0.004018015],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989731,0.00003459221,0.00031001974,0.00021288525,0.00018668696,0.00028272183],"domain_scores_gemma":[0.99918616,0.000076462544,0.000054177483,0.00029380416,0.00030979628,0.00007958707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009494329,0.00020162821,0.00019042728,0.00023261893,0.00012556175,0.000037003552,0.00006569896,0.00010190145,0.0003288723],"category_scores_gemma":[0.000008732144,0.00015302599,0.000072324656,0.00024579364,0.000077209006,0.00045920958,9.816994e-7,0.000082516664,0.000017549528],"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":[0.000073298,0.00014476335,0.0000024396895,0.000034153334,0.00009865697,0.000029906536,0.00012925973,0.24298409,0.73166716,0.007707396,0.002465588,0.014663278],"study_design_scores_gemma":[0.00085447653,0.00042238185,0.000034483342,0.0000739996,0.000058427227,0.000026403906,0.00027389568,0.063102625,0.9333364,0.00041708688,0.0010758763,0.00032399077],"about_ca_topic_score_codex":0.00018744679,"about_ca_topic_score_gemma":0.00009143895,"teacher_disagreement_score":0.9192359,"about_ca_system_score_codex":0.00038775644,"about_ca_system_score_gemma":0.000071715964,"threshold_uncertainty_score":0.6240219},"labels":[],"label_agreement":null},{"id":"W2586955751","doi":"10.1109/tste.2017.2664666","title":"Coordinated Optimal Dispatch of Energy Storage in a Network of Grid-Connected Microgrids","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":117,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Energy storage; Mathematical optimization; Grid; Computer science; Renewable energy; Economic dispatch; Electricity; Distributed generation; Optimization problem; Engineering; Electric power system; Power (physics); Electrical engineering; Mathematics","score_opus":0.003911908117018953,"score_gpt":0.18786752441265409,"score_spread":0.18395561629563514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586955751","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":[0.08550345,0.00088013784,0.911643,0.00005984882,0.000649926,0.00013440449,0.000038320388,0.00013970784,0.0009511614],"genre_scores_gemma":[0.99769115,0.0006352712,0.0005821768,0.000015406544,0.00007090781,0.00006220616,0.0000146697685,0.000049951803,0.0008782405],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986801,0.0000451244,0.00043555244,0.00022300109,0.00012962997,0.000486592],"domain_scores_gemma":[0.99899036,0.00006125752,0.00014185386,0.0005097855,0.00022202931,0.00007473092],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013608295,0.00023172724,0.00041858645,0.00022102759,0.00017555611,0.000041578824,0.0003110751,0.00017667074,0.00007778582],"category_scores_gemma":[0.000009617574,0.0002512434,0.00013056914,0.0003810707,0.00009081172,0.0002622348,0.000004219466,0.00015326966,5.7661066e-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":[0.00015774967,0.00013719946,0.00003768777,0.00008786261,0.00009529888,0.00003148885,0.00006999965,0.98597634,0.0031687298,0.0007366867,0.0003227637,0.009178164],"study_design_scores_gemma":[0.0036969215,0.00032420355,0.00065535086,0.00017696006,0.00011680176,0.000010391613,0.00047622414,0.8160184,0.16691473,0.00027465832,0.01065848,0.00067688443],"about_ca_topic_score_codex":0.0030346958,"about_ca_topic_score_gemma":0.00068618875,"teacher_disagreement_score":0.9121877,"about_ca_system_score_codex":0.00014715883,"about_ca_system_score_gemma":0.00006889203,"threshold_uncertainty_score":0.999994},"labels":[],"label_agreement":null},{"id":"W2604726630","doi":"10.1109/tste.2017.2691279","title":"SSR Mitigation With a New Control of PV Solar Farm as STATCOM (PV-STATCOM)","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":122,"is_retracted":false,"has_abstract":true,"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","keywords":"Photovoltaic system; Engineering; Fault (geology); Inverter; AC power; Grid-connected photovoltaic power system; Compensation (psychology); Flexible AC transmission system; Electrical engineering; Electricity generation; Electric power system; Maximum power point tracking; Electronic engineering; Control theory (sociology); Power (physics); Computer science; Voltage; Control (management); Physics","score_opus":0.003480712959966783,"score_gpt":0.18693933581872108,"score_spread":0.1834586228587543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604726630","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":[0.00621403,0.00025077283,0.9902922,0.00023103104,0.000222359,0.00022229688,0.00002469965,0.00018479594,0.0023578398],"genre_scores_gemma":[0.99259263,0.0003204612,0.00073994446,0.00009346079,0.00006344201,0.00006165041,0.000009084864,0.0000612962,0.0060580275],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878937,0.00002500247,0.00028998652,0.00023186476,0.00022380827,0.00043995763],"domain_scores_gemma":[0.9989296,0.000051109924,0.00012068433,0.00053066306,0.00021983933,0.00014808358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009694193,0.0002481517,0.00030954147,0.00018516793,0.00038506193,0.00013902689,0.00023831896,0.00012219786,0.000122349],"category_scores_gemma":[0.000008107536,0.00023770882,0.000107160195,0.00013950079,0.00007264255,0.0004099984,0.0000013571731,0.00017765345,0.000007217331],"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":[0.0002305333,0.000066764915,0.000018521425,0.00007225825,0.00018946966,0.000025267247,0.00018461797,0.9680096,0.0018346289,0.0014553452,0.00013114346,0.027781846],"study_design_scores_gemma":[0.016631331,0.001344378,0.0003695791,0.00020634526,0.00065124413,0.000054456552,0.0028352574,0.63083655,0.27090552,0.0035463339,0.07105283,0.0015661905],"about_ca_topic_score_codex":0.0028277303,"about_ca_topic_score_gemma":0.00057266245,"teacher_disagreement_score":0.98955226,"about_ca_system_score_codex":0.00014644391,"about_ca_system_score_gemma":0.00017428583,"threshold_uncertainty_score":0.9693485},"labels":[],"label_agreement":null},{"id":"W2606185087","doi":"10.1109/tste.2017.2692754","title":"A Sustainable Energy Management System for Isolated Microgrids","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":115,"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","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microgrid; Benchmark (surveying); Energy management; Generator (circuit theory); Fossil fuel; Computer science; Engineering; Automotive engineering; Energy (signal processing); Operations research; Reliability engineering; Voltage; Electrical engineering; Power (physics); Mathematics; Waste management","score_opus":0.004129817140963562,"score_gpt":0.18805705271607925,"score_spread":0.1839272355751157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606185087","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":[0.00035020395,0.00060791656,0.9901085,0.00009043162,0.00070554815,0.0003721874,0.000019874919,0.0006813385,0.0070639853],"genre_scores_gemma":[0.9304988,0.0006607428,0.00092392595,0.00006052081,0.00012966187,0.0008801485,0.000018304234,0.00011693605,0.066711],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980909,0.000021390388,0.0003532612,0.00039407203,0.00016507746,0.0009752978],"domain_scores_gemma":[0.99861544,0.00003594137,0.00009270591,0.00080347306,0.00030235463,0.00015007172],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.000162771,0.00035641296,0.00033377693,0.00036973876,0.0013121938,0.0004293615,0.00045123367,0.00019537588,0.00003887566],"category_scores_gemma":[0.0000028590398,0.0003825174,0.00021640319,0.00020834713,0.000050755203,0.0004905323,0.000006082086,0.00011911152,0.0000063247535],"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":[0.00027515047,0.00013562452,7.2138147e-7,0.0010691559,0.00047065428,0.00022355957,0.000086682296,0.9016837,0.0006534789,0.033621285,0.0027783276,0.059001654],"study_design_scores_gemma":[0.0035660923,0.0002637495,0.000006573066,0.00010045877,0.0003004737,0.000031146104,0.003942001,0.45771566,0.03858196,0.0006202507,0.49397823,0.0008933998],"about_ca_topic_score_codex":0.000981487,"about_ca_topic_score_gemma":0.000075568765,"teacher_disagreement_score":0.98918456,"about_ca_system_score_codex":0.00059299625,"about_ca_system_score_gemma":0.000045890054,"threshold_uncertainty_score":0.99998796},"labels":[],"label_agreement":null},{"id":"W2620557118","doi":"10.1109/tste.2017.2710624","title":"Modification of DFIG's Active Power Control Loop for Speed Control Enhancement and Inertial Frequency Response","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":40,"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 British Columbia","funders":"","keywords":"Control theory (sociology); Controller (irrigation); Sensitivity (control systems); Electronic speed control; Wind speed; Engineering; PID controller; Induction generator; Rotor (electric); Low-pass filter; Particle swarm optimization; Wind power; Filter (signal processing); Computer science; Control engineering; Electronic engineering","score_opus":0.008659698331641399,"score_gpt":0.22918483627183492,"score_spread":0.22052513794019352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620557118","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":[0.18422396,0.00014166912,0.8131616,0.00030321753,0.000493756,0.0007551683,0.00010453062,0.00009405189,0.0007220413],"genre_scores_gemma":[0.9975813,0.000015601401,0.00006880236,0.00003628176,0.000073442534,0.00027930993,0.0000028946288,0.000051794963,0.0018905404],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99864143,0.00008128215,0.0003943758,0.0002820849,0.00019171498,0.00040908836],"domain_scores_gemma":[0.9985602,0.00026676114,0.00017268788,0.00058778987,0.00030144508,0.00011110031],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003329424,0.00025092417,0.00041243696,0.0002215001,0.00032946616,0.00007957405,0.00021873967,0.00015539723,0.000036082867],"category_scores_gemma":[0.000060421422,0.00025436256,0.00012736412,0.00006423236,0.000088189554,0.00038196915,0.0000011353904,0.00012557615,0.0000025297916],"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":[0.008617296,0.00032694274,0.000025182168,0.0002720506,0.00086186075,0.00002506087,0.0005307398,0.24416259,0.73321474,0.0046887775,0.00022261043,0.0070521818],"study_design_scores_gemma":[0.025967496,0.0015811004,0.0020699708,0.00011914805,0.00043902142,0.0000147689525,0.0015320983,0.22195406,0.7399252,0.0012211954,0.004109276,0.0010666418],"about_ca_topic_score_codex":0.00054214464,"about_ca_topic_score_gemma":0.000032441363,"teacher_disagreement_score":0.81335735,"about_ca_system_score_codex":0.00025811934,"about_ca_system_score_gemma":0.00008952751,"threshold_uncertainty_score":0.9999909},"labels":[],"label_agreement":null},{"id":"W2621135070","doi":"10.1109/tste.2017.2710340","title":"Reactive Power Control for Single-Phase Grid-Tie Inverters Using Quasi-Sinusoidal Waveform","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":22,"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 Manitoba","funders":"Canada Research Chairs","keywords":"Waveform; AC power; Power (physics); Electronic engineering; Non-sinusoidal waveform; Control theory (sociology); Three-phase; Power control; Volt-ampere reactive; Electrical engineering; Grid; Computer science; Control (management); Engineering; Physics; Voltage; Voltage optimisation; Mathematics","score_opus":0.012090036515235573,"score_gpt":0.2315228799201192,"score_spread":0.21943284340488362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621135070","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":[0.005914911,0.00008897516,0.99062246,0.00009503542,0.0009375749,0.00034663975,0.00008462179,0.00022475654,0.0016850083],"genre_scores_gemma":[0.9977996,0.000025438123,0.000648494,0.00012754771,0.00015260816,0.00008879245,0.0000118161315,0.0000849572,0.0010607605],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986402,0.00002172074,0.0002876932,0.00028601315,0.00015281598,0.0006115687],"domain_scores_gemma":[0.9989313,0.000070530616,0.00010567134,0.00050115335,0.0002467726,0.00014456955],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012397017,0.00029703107,0.00032010445,0.00024383124,0.0008207659,0.0002398085,0.00023954314,0.00018021137,0.00004566771],"category_scores_gemma":[0.00001505265,0.00030704163,0.00020539254,0.000104532,0.00007818306,0.0007672404,0.0000016158261,0.00016442475,0.000002789522],"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":[0.00069391495,0.00047922917,9.695923e-7,0.00008759528,0.00035390077,0.000053568074,0.00048524956,0.93062514,0.02191936,0.0006041383,0.00032790608,0.04436904],"study_design_scores_gemma":[0.006245964,0.00050425396,0.0000017917041,0.000038273505,0.00015899584,0.000023693003,0.0011511364,0.92226446,0.05342937,0.00024941372,0.015425251,0.00050738413],"about_ca_topic_score_codex":0.00046714224,"about_ca_topic_score_gemma":0.0000869301,"teacher_disagreement_score":0.99188465,"about_ca_system_score_codex":0.0005411704,"about_ca_system_score_gemma":0.00007814507,"threshold_uncertainty_score":0.9999382},"labels":[],"label_agreement":null},{"id":"W2735549622","doi":"10.1109/tste.2017.2724514","title":"Stochastic Optimal Planning of Battery Energy Storage Systems for Isolated Microgrids","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":239,"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","funders":"Natural Sciences and Engineering Research Council of Canada; Taif University","keywords":"Dispatchable generation; Microgrid; Stochastic programming; Mathematical optimization; Time horizon; Energy storage; Computer science; Monte Carlo method; Reliability engineering; Distributed generation; Engineering; Renewable energy; Power (physics); Mathematics","score_opus":0.007226901608446616,"score_gpt":0.20727176669935002,"score_spread":0.2000448650909034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735549622","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":[0.0029076468,0.0014351533,0.99407244,0.000021788866,0.0009086899,0.00016041397,0.00004859536,0.00018437485,0.0002609144],"genre_scores_gemma":[0.9964295,0.00015626312,0.0003469825,0.000017972367,0.00011962977,0.00020962983,0.000015628342,0.00007342703,0.002630979],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880826,0.00002046277,0.00033596897,0.00023621146,0.00012310661,0.00047595665],"domain_scores_gemma":[0.99905306,0.00008074546,0.0001192995,0.00045322473,0.00020281893,0.00009084905],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010660895,0.00024476805,0.00033190535,0.00026317724,0.0004591651,0.00015222564,0.00027293412,0.00016591667,0.000020026984],"category_scores_gemma":[0.000006073648,0.00026392663,0.00013923932,0.00010265363,0.000053970125,0.00031505295,0.0000023927273,0.00011162936,9.576974e-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":[0.0001435545,0.000051453477,4.6828094e-7,0.00014555118,0.00015144578,0.000014136401,0.0000876495,0.9925273,0.002208966,0.0003503686,0.00044334718,0.0038757734],"study_design_scores_gemma":[0.0010262292,0.00016998254,0.000003401674,0.00007217374,0.00008212582,0.000009869046,0.0004066697,0.98322284,0.0072587933,0.000025557838,0.0074368673,0.00028551352],"about_ca_topic_score_codex":0.0004411589,"about_ca_topic_score_gemma":0.000009310325,"teacher_disagreement_score":0.9937254,"about_ca_system_score_codex":0.00013814672,"about_ca_system_score_gemma":0.000051338036,"threshold_uncertainty_score":0.9999813},"labels":[],"label_agreement":null},{"id":"W2761362953","doi":"10.1109/tste.2017.2761813","title":"Coordinated Supplementary Damping Control of DFIG and PSS to Suppress Inter-Area Oscillations With Optimally Controlled Plant Dynamics","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":47,"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 Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Control theory (sociology); Induction generator; Power (physics); Damping ratio; Electric power system; Generator (circuit theory); Engineering; Doubly fed electric machine; Controller (irrigation); Automatic frequency control; Control engineering; Function (biology); AC power; Computer science; Control (management); Vibration; Physics","score_opus":0.005721238186880437,"score_gpt":0.20193145891751924,"score_spread":0.1962102207306388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2761362953","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":[0.023711165,0.000019301146,0.97296256,0.0002645468,0.0002114765,0.00050697,0.00066186354,0.00010062623,0.0015614753],"genre_scores_gemma":[0.998202,0.000016598477,0.0005976815,0.000037797763,0.000006747286,0.00016417445,0.000035508467,0.00003503806,0.0009044234],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881226,0.000048926544,0.00037862587,0.00025231118,0.00015653062,0.00035136592],"domain_scores_gemma":[0.9988934,0.00012481195,0.000093405404,0.0004941056,0.00023921108,0.00015511374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018115858,0.00022935169,0.00046374922,0.00023529926,0.00039956413,0.0001309625,0.00020994787,0.000080279955,0.00012559122],"category_scores_gemma":[0.000015104029,0.00020874199,0.00007010798,0.00012433724,0.000080206664,0.00023580834,0.0000040168575,0.00011268814,4.6612126e-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":[0.00088467414,0.00009246678,0.00030411035,0.00012083808,0.00029365797,0.000020730868,0.0002521506,0.9959852,0.00023529089,0.0013652506,0.00011275032,0.00033286802],"study_design_scores_gemma":[0.008042144,0.00034276355,0.00025583233,0.00009145643,0.00013200741,0.000017481098,0.0021240874,0.9840949,0.0029268493,0.000027611475,0.0015692917,0.00037554352],"about_ca_topic_score_codex":0.0009210257,"about_ca_topic_score_gemma":0.0017690451,"teacher_disagreement_score":0.9744909,"about_ca_system_score_codex":0.00021952584,"about_ca_system_score_gemma":0.000056430552,"threshold_uncertainty_score":0.85122514},"labels":[],"label_agreement":null},{"id":"W2761390235","doi":"10.1109/tste.2017.2761913","title":"Application of Information Gap Decision Theory to the Design of Robust Wide-Area Power System Stabilizers Considering Uncertainties of Wind Power","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":36,"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 Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Wind power; Power (physics); Electric power system; Power optimizer; Computer science; Control theory (sociology); Decision theory; Reliability engineering; Engineering; Control engineering; Maximum power point tracking; Electrical engineering; Control (management); Mathematics; Voltage","score_opus":0.012479509561230485,"score_gpt":0.209718992973942,"score_spread":0.19723948341271152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2761390235","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":[0.008246427,0.00004708909,0.9883902,0.000029158024,0.00031153043,0.00050807674,0.000028309012,0.000074571224,0.002364652],"genre_scores_gemma":[0.99775785,0.000015117421,0.0020123085,0.00001162652,0.0000021054418,0.000069908565,0.0000018629072,0.000020593523,0.000108629305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985308,0.00010501099,0.00067285856,0.00014775599,0.00031118223,0.0002323578],"domain_scores_gemma":[0.99772173,0.00044666335,0.00026851834,0.0009148048,0.0005806374,0.00006762451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008578409,0.0001815739,0.0003333823,0.0002672191,0.00024569654,0.00004993413,0.00034286443,0.00011119452,0.000047479214],"category_scores_gemma":[0.00011226426,0.00014979146,0.000105941435,0.000251348,0.00012528876,0.00051778863,0.0000061070327,0.00009028999,0.000001963004],"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":[0.00018799718,0.00003286447,0.00002284553,0.00025867368,0.00005625022,4.2792485e-7,0.001375472,0.9893759,0.00031180633,0.0070728883,0.00007374989,0.0012311054],"study_design_scores_gemma":[0.0023698644,0.00066183135,0.0007754404,0.00070502446,0.00019495281,0.00001511778,0.09082394,0.7484261,0.14417657,0.0017438359,0.009147906,0.0009594285],"about_ca_topic_score_codex":0.0002835511,"about_ca_topic_score_gemma":0.00003049275,"teacher_disagreement_score":0.98951143,"about_ca_system_score_codex":0.00022790619,"about_ca_system_score_gemma":0.000095865675,"threshold_uncertainty_score":0.61083186},"labels":[],"label_agreement":null},{"id":"W2762453449","doi":"10.1109/tste.2017.2761179","title":"Stochastic Operation Framework for Distribution Networks Hosting High Wind Penetrations","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Power System Optimization","field":"Engineering","cited_by":37,"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 Calgary","funders":"","keywords":"Stochastic programming; Mathematical optimization; Wind power; Control reconfiguration; Computer science; Linear programming; Integer programming; Conic section; Stochastic optimization; Electric power system; Operations research; Power (physics); Reliability engineering; Engineering; Mathematics; Electrical engineering","score_opus":0.00704614382327904,"score_gpt":0.22094458083656762,"score_spread":0.2138984370132886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762453449","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":[0.0013546182,0.00008378393,0.99618196,0.00011130849,0.0012193767,0.00040977693,0.000039090017,0.00032610804,0.00027394455],"genre_scores_gemma":[0.99547374,0.00003933558,0.0024055815,0.000023143992,0.00024597425,0.00029879034,0.000103662256,0.00006662037,0.0013431481],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987043,0.000028305576,0.0003066722,0.0002778606,0.00016528057,0.0005175935],"domain_scores_gemma":[0.9988503,0.00019550356,0.00009886642,0.00052438345,0.00023244933,0.00009851265],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00017692639,0.00023124412,0.00020441043,0.00012287374,0.0015955253,0.00039958858,0.00023458671,0.00024722648,0.00003079096],"category_scores_gemma":[0.00006560166,0.0002667308,0.000086006956,0.00019641574,0.000035695826,0.0006157472,0.0000016119604,0.00022227503,0.0000036828503],"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":[0.000021938666,0.000033744927,0.0000011693425,0.000033536806,0.000046301502,0.0000025215866,0.000037774265,0.9702133,0.000058353515,0.025957836,0.00023807886,0.0033554465],"study_design_scores_gemma":[0.00048021704,0.00012212057,0.000060581275,0.000059822632,0.000069422764,0.000005890804,0.00013027007,0.9929947,0.0033118047,0.0017737997,0.00066214136,0.0003292279],"about_ca_topic_score_codex":0.00021946005,"about_ca_topic_score_gemma":0.0000727078,"teacher_disagreement_score":0.9941191,"about_ca_system_score_codex":0.00045026295,"about_ca_system_score_gemma":0.00006898384,"threshold_uncertainty_score":0.9999785},"labels":[],"label_agreement":null},{"id":"W2765830748","doi":"10.1109/tste.2017.2767064","title":"Optimal Day-Ahead Scheduling of Power-to-Gas Energy Storage and Gas Load Management in Wholesale Electricity and Gas Markets","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":140,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Power to gas; Natural gas; Electricity; Energy storage; Gas consumption; Scheduling (production processes); Grid; Environmental science; Process engineering; Waste management; Power (physics); Engineering; Operations management; Electrical engineering; Chemistry","score_opus":0.004598923741815085,"score_gpt":0.20287495135945569,"score_spread":0.1982760276176406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765830748","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":[0.260483,0.00038658388,0.73077214,0.00010447827,0.0002786667,0.00017327466,0.0000083088,0.00013609671,0.0076574637],"genre_scores_gemma":[0.9926004,0.0012229118,0.002433472,0.000026691081,0.000025798756,0.000111603986,0.0000037785303,0.00007791309,0.003497461],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99818105,0.00007936405,0.00041842976,0.00042951552,0.0002821735,0.000609489],"domain_scores_gemma":[0.9989433,0.000053630556,0.00009839704,0.00054622645,0.00019464156,0.00016379067],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037224795,0.0003411213,0.00038481274,0.0006654178,0.00032000215,0.00015282482,0.00024391088,0.00020344988,0.000024372821],"category_scores_gemma":[0.00001666393,0.00038520296,0.000060396666,0.00039206544,0.00007556195,0.00044729843,0.000010461696,0.00022036092,0.0000012347249],"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":[0.00012076316,0.000080245576,0.000008078863,0.00014997911,0.00011102925,0.00010858225,0.00023320116,0.9769747,0.0012829163,0.003153277,0.00006444793,0.017712727],"study_design_scores_gemma":[0.0025469314,0.00035258097,0.00033755557,0.00040936292,0.00011309703,0.000049563594,0.0024554937,0.8911535,0.092101805,0.00046671738,0.008969541,0.0010438648],"about_ca_topic_score_codex":0.002730699,"about_ca_topic_score_gemma":0.0006403681,"teacher_disagreement_score":0.73211735,"about_ca_system_score_codex":0.0005211583,"about_ca_system_score_gemma":0.000060689476,"threshold_uncertainty_score":0.99986},"labels":[],"label_agreement":null},{"id":"W2766996475","doi":"10.1109/tste.2017.2765681","title":"Flexible Interlinking and Coordinated Power Control of Multiple DC Microgrids Clusters","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":133,"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":"Voltage droop; Converters; Computer science; Power (physics); Power control; Control (management); AC power; Fault (geology); Voltage; Electronic engineering; Engineering; Electrical engineering; Voltage regulator","score_opus":0.00437877032785946,"score_gpt":0.192131783370244,"score_spread":0.18775301304238454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766996475","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":[0.018881615,0.0005505762,0.9787449,0.00009263783,0.00040016513,0.0001472314,0.000017466462,0.00018014791,0.0009852416],"genre_scores_gemma":[0.99790657,0.00025140363,0.00028831608,0.000053204134,0.000022864238,0.000026038018,0.0000028557017,0.000040669514,0.0014080986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991143,0.000021001217,0.00024722255,0.00019043862,0.00008793961,0.00033910864],"domain_scores_gemma":[0.9992869,0.000059885813,0.000075949356,0.00034914236,0.00014921477,0.00007889551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010734538,0.00018824426,0.00025744562,0.00019676755,0.00033535718,0.00011854096,0.00018640645,0.000120806115,0.0000460413],"category_scores_gemma":[0.000009262788,0.0001947512,0.00008584884,0.00008945023,0.000094365925,0.00030882278,0.0000027644578,0.00013903882,0.0000015701141],"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":[0.00022652638,0.00008883745,0.000052768846,0.00012019179,0.00022207556,0.000020788435,0.00029510327,0.9463053,0.012999451,0.00027257472,0.00015066612,0.039245747],"study_design_scores_gemma":[0.0065669357,0.00029686652,0.0001920568,0.00011619408,0.00014645579,0.000021086866,0.0014168898,0.74845165,0.22734301,0.0002043804,0.014627954,0.0006165534],"about_ca_topic_score_codex":0.00040636535,"about_ca_topic_score_gemma":0.0000653581,"teacher_disagreement_score":0.97902495,"about_ca_system_score_codex":0.00007975851,"about_ca_system_score_gemma":0.00002326466,"threshold_uncertainty_score":0.79417235},"labels":[],"label_agreement":null},{"id":"W2767154953","doi":"10.1109/tste.2017.2769558","title":"Priority-Based Microgrid Energy Management in a Network Environment","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microgrid; Renewable energy; Computer science; Energy storage; Mathematical optimization; Economic dispatch; Distributed generation; Grid; Energy management; Electric power system; Power (physics); Engineering; Energy (signal processing); Electrical engineering; Mathematics","score_opus":0.003738184470263683,"score_gpt":0.17684269928743826,"score_spread":0.17310451481717457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767154953","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":[0.0008706657,0.00079123507,0.99385315,0.00013545896,0.0004384455,0.00015139567,0.00000509032,0.00017558521,0.0035789886],"genre_scores_gemma":[0.99033654,0.002884088,0.0023277013,0.00017092652,0.00010862207,0.00028716907,0.000008787467,0.00006061471,0.0038155597],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870455,0.000029305014,0.00024507032,0.0002792984,0.00015247191,0.0005892748],"domain_scores_gemma":[0.9992185,0.00002087764,0.000049129725,0.00060163834,0.000021197924,0.00008863126],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011591461,0.00023590289,0.00020565234,0.00019971876,0.00039765728,0.00013587732,0.00027743354,0.0001126533,0.00011120514],"category_scores_gemma":[6.846751e-7,0.00026476572,0.00010028491,0.00011803668,0.00004470784,0.00019061625,0.0000034642794,0.00013572919,0.0000090070025],"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":[0.000045635137,0.000088306144,0.000007949161,0.00003810431,0.000056736997,0.00009835033,0.000014540702,0.90910196,0.00008021869,0.0011918447,0.00025241097,0.089023925],"study_design_scores_gemma":[0.0028417322,0.000100077574,0.00026081217,0.000058523667,0.00008502215,0.0000040644654,0.00012566216,0.5297005,0.010996642,0.0007903996,0.45435992,0.00067661214],"about_ca_topic_score_codex":0.00046771427,"about_ca_topic_score_gemma":0.0002067078,"teacher_disagreement_score":0.9915254,"about_ca_system_score_codex":0.0003381611,"about_ca_system_score_gemma":0.000022339169,"threshold_uncertainty_score":0.99998045},"labels":[],"label_agreement":null},{"id":"W2768891253","doi":"10.1109/tste.2017.2774195","title":"Direct Interval Forecast of Uncertain Wind Power Based on Recurrent Neural Networks","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":204,"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; China Scholarship Council","keywords":"Wind power; Artificial neural network; Interval (graph theory); Computer science; Power (physics); Control theory (sociology); Engineering; Artificial intelligence; Electrical engineering; Mathematics; Control (management); Physics","score_opus":0.01212446752455444,"score_gpt":0.22558462243875108,"score_spread":0.21346015491419665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768891253","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":[0.08216647,0.00020972847,0.83295774,0.000146225,0.004777697,0.00023463718,0.000050019687,0.00048552128,0.07897194],"genre_scores_gemma":[0.9974693,0.00003110141,0.0000876008,0.00005827648,0.00009806328,0.000030885585,0.0000069203065,0.000072413175,0.0021454056],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984834,0.000052404106,0.00034640898,0.0002881701,0.00023321113,0.0005963718],"domain_scores_gemma":[0.9988185,0.00015632348,0.000111223155,0.000669353,0.00010455168,0.00014001929],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019228547,0.00031824014,0.00035804423,0.00024821778,0.00042095614,0.00010375714,0.00036228873,0.00015638146,0.00014514792],"category_scores_gemma":[0.000016932201,0.00031068988,0.00024168288,0.00017331316,0.000093689785,0.0002422407,0.000003518903,0.00031283675,0.0000017848524],"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":[0.00012670657,0.00009912829,0.00001530015,0.00005571484,0.000052904248,0.000047003814,0.000073675634,0.9699926,0.000058347345,0.00042945103,0.00026775713,0.028781418],"study_design_scores_gemma":[0.00069207314,0.00045452462,0.00006194471,0.00017186784,0.000035308654,0.000004776926,0.00017639673,0.9730222,0.016461289,0.000040351602,0.00850818,0.00037106534],"about_ca_topic_score_codex":0.000379137,"about_ca_topic_score_gemma":0.00013116882,"teacher_disagreement_score":0.9153029,"about_ca_system_score_codex":0.00017951365,"about_ca_system_score_gemma":0.000036514204,"threshold_uncertainty_score":0.9999345},"labels":[],"label_agreement":null},{"id":"W2781736504","doi":"10.1109/tste.2018.2789465","title":"Hierarchical Control of Multiterminal DC Grids for Large-Scale Renewable Energy Integration","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":82,"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":"National Key Research and Development Program of China","keywords":"Voltage droop; Converters; MATLAB; Grid; Computer science; Renewable energy; Voltage source; AC power; Voltage; Engineering; Power control; Control theory (sociology); Electronic engineering; Control engineering; Power (physics); Electrical engineering; Control (management)","score_opus":0.005829052077092169,"score_gpt":0.2189351672088544,"score_spread":0.21310611513176222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781736504","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":[0.0027062125,0.00006386846,0.99420786,0.000025139361,0.00073904084,0.00021144513,0.00005806616,0.00020504686,0.0017833085],"genre_scores_gemma":[0.98727816,0.000025195874,0.0011025948,0.00004580999,0.00034066467,0.0004542337,0.000010385364,0.000052241347,0.010690704],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866986,0.000048576767,0.00038650213,0.0002504934,0.0001735325,0.0004710202],"domain_scores_gemma":[0.9991676,0.00007853403,0.000056253142,0.00027022255,0.00032618755,0.000101199614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021752511,0.0002099474,0.00028709276,0.00029553,0.0002567643,0.00003516175,0.00011964252,0.00021222589,0.00007535391],"category_scores_gemma":[0.0000082954975,0.0002050162,0.00015984772,0.00032938027,0.000057713984,0.00022912628,9.699619e-7,0.00012068305,0.0000025626687],"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":[0.0012387983,0.00064286625,0.000006770368,0.0005512579,0.0003244249,0.000016110978,0.0012395213,0.78127515,0.1201598,0.011184232,0.002969495,0.08039159],"study_design_scores_gemma":[0.0015938352,0.0006228796,0.0000063457996,0.00005167761,0.000044246914,0.000011681199,0.00075825775,0.48725444,0.38743472,0.0006564418,0.1213134,0.0002520841],"about_ca_topic_score_codex":0.0023104209,"about_ca_topic_score_gemma":0.0017013575,"teacher_disagreement_score":0.9931053,"about_ca_system_score_codex":0.00017983504,"about_ca_system_score_gemma":0.000053279513,"threshold_uncertainty_score":0.8360318},"labels":[],"label_agreement":null},{"id":"W2793814978","doi":"10.1109/tste.2018.2808601","title":"PV-STATCOM: A New Smart Inverter for Voltage Control in Distribution Systems","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":173,"is_retracted":false,"has_abstract":true,"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; Ontario Centres of Excellence","keywords":"Photovoltaic system; Inverter; Maximum power point tracking; Low voltage ride through; AC power; Engineering; Grid-connected photovoltaic power system; Voltage; Control theory (sociology); Computer science; Electrical engineering; Control (management)","score_opus":0.004796386370232385,"score_gpt":0.18551345673372174,"score_spread":0.18071707036348936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793814978","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":[0.0007033831,0.00028398843,0.9972905,0.000077591714,0.00072734925,0.0003672952,0.00006926284,0.00021655916,0.00026408533],"genre_scores_gemma":[0.99311495,0.00008620918,0.000098548,0.00013240412,0.00018817102,0.00028330408,0.000037681217,0.000042128693,0.0060166316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890107,0.000023318253,0.000282893,0.00020942869,0.00010304452,0.00048022615],"domain_scores_gemma":[0.99945045,0.00006169328,0.000029624156,0.00019969682,0.0001530755,0.00010547393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001197884,0.0001903264,0.00022865021,0.00017338882,0.00013275057,0.00007735779,0.00010173848,0.00013398065,0.0000493971],"category_scores_gemma":[0.0000053234467,0.00019821698,0.00008563976,0.00032373893,0.000029336747,0.00024274428,5.597543e-7,0.00010328401,0.0000104157825],"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":[0.00018427207,0.00006415425,0.0000092650835,0.000096621414,0.00007085137,0.000008695823,0.00012470898,0.97676885,0.00096774986,0.0021467493,0.0077441228,0.011813962],"study_design_scores_gemma":[0.0025052677,0.00015792128,0.000013646098,0.000025896074,0.00003824909,0.0000039527863,0.00025127755,0.85584676,0.0030789103,0.00025999817,0.13757995,0.00023817597],"about_ca_topic_score_codex":0.0013446371,"about_ca_topic_score_gemma":0.0004082218,"teacher_disagreement_score":0.99719197,"about_ca_system_score_codex":0.0003478275,"about_ca_system_score_gemma":0.00007162378,"threshold_uncertainty_score":0.8083054},"labels":[],"label_agreement":null},{"id":"W2794971681","doi":"10.1109/tste.2018.2820696","title":"Assessment and Enhancement Frameworks for System Reliability Performance Using Different PEV Charging Models","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Advanced Battery Technologies Research","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":false,"ca_institutions":"University of Waterloo","funders":"Majmaah University","keywords":"Reliability (semiconductor); Reliability engineering; Computer science; Monte Carlo method; Electric vehicle; Engineering; Power (physics); Mathematics","score_opus":0.016581389151803846,"score_gpt":0.2750390337356367,"score_spread":0.25845764458383286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794971681","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":[0.29118618,0.00004314629,0.7076029,0.000025482339,0.00021966068,0.00027051967,0.0000046929845,0.00034995025,0.0002974413],"genre_scores_gemma":[0.9890262,0.00017597101,0.009702806,0.000016652692,0.000054517983,0.0004935227,0.0000017193958,0.000053985263,0.00047465737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843806,0.000022064232,0.00026984583,0.00036276085,0.00022936234,0.00067790167],"domain_scores_gemma":[0.99912333,0.00010107582,0.00003408991,0.00045025747,0.0002096012,0.00008163247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017341232,0.00024219476,0.00025629989,0.00024018485,0.00045735328,0.00006103266,0.00017535505,0.00022856232,0.000019938974],"category_scores_gemma":[0.0000034934642,0.00023237374,0.000055351346,0.00024155396,0.000118470336,0.0003513494,0.0000074001478,0.0004026028,7.9838554e-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":[0.000044506854,0.00006906858,0.000009565559,0.00078826555,0.00005156509,0.000003241065,0.00009070803,0.96768796,0.0034748819,0.003139864,0.000013948271,0.024626397],"study_design_scores_gemma":[0.00029072553,0.0002219892,0.000016181173,0.00010129124,0.000017007946,0.000004002276,0.0011234944,0.8811301,0.11562368,0.00089505926,0.0003589625,0.00021747625],"about_ca_topic_score_codex":0.000036443842,"about_ca_topic_score_gemma":0.0000053687877,"teacher_disagreement_score":0.6979001,"about_ca_system_score_codex":0.0014684943,"about_ca_system_score_gemma":0.000040762417,"threshold_uncertainty_score":0.9475927},"labels":[],"label_agreement":null},{"id":"W2807030657","doi":"10.1109/tste.2018.2841938","title":"Analytical Iterative Multistep Interval Forecasts of Wind Generation Based on TLGP","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Queen's University; National Natural Science Foundation of China; Queen's University Belfast; European Commission","keywords":"Probabilistic logic; Probabilistic forecasting; Wind power; Wind power forecasting; Interval (graph theory); Benchmark (surveying); Computer science; Mathematical optimization; Monte Carlo method; Power system simulation; Grid; Electric power system; Key (lock); Iterative method; Consensus forecast; Econometrics; Power (physics); Engineering; Algorithm; Mathematics; Artificial intelligence; Statistics","score_opus":0.015124768453612715,"score_gpt":0.23375542188111406,"score_spread":0.21863065342750135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807030657","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":[0.10482317,0.000019306586,0.8791361,0.000032836735,0.00072462595,0.00008327474,0.000021099451,0.00015505488,0.015004514],"genre_scores_gemma":[0.99587005,0.000005861717,0.0007027521,0.00010200586,0.0002526406,0.000021128215,0.0000137444995,0.000049791048,0.0029820292],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987632,0.000049518643,0.00032255374,0.00025193972,0.00022002772,0.00039275005],"domain_scores_gemma":[0.99926895,0.00009769868,0.000043369728,0.00026955933,0.00021378929,0.00010662998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011898991,0.00023912135,0.00023818403,0.00036353982,0.00017263608,0.000043454816,0.0001187613,0.00013606304,0.000253935],"category_scores_gemma":[0.000010011007,0.0002361382,0.0001343958,0.0004183633,0.00010027944,0.00019096043,0.0000012837619,0.00017284855,0.00000853681],"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":[0.00012125606,0.00012360736,0.0000051057186,0.000047210706,0.00006711773,0.000022044327,0.00028888503,0.9764651,0.0014146661,0.0026043518,0.00036454503,0.018476123],"study_design_scores_gemma":[0.00048251334,0.0006390226,0.000008589166,0.000054820364,0.000026418225,0.0000036701756,0.00014817424,0.8110234,0.1824413,0.000042742773,0.0049317805,0.00019756577],"about_ca_topic_score_codex":0.00013886743,"about_ca_topic_score_gemma":0.00015816466,"teacher_disagreement_score":0.8910469,"about_ca_system_score_codex":0.00019103287,"about_ca_system_score_gemma":0.000048418136,"threshold_uncertainty_score":0.9629437},"labels":[],"label_agreement":null},{"id":"W2808230357","doi":"10.1109/tste.2018.2846661","title":"Tidal Current and Level Uncertainty Prediction via Adaptive Linear Programming","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":14,"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":"Robust optimization; Computer science; Extreme learning machine; Mathematical optimization; Quantile; Quantile regression; Linear programming; Weighting; Simplex algorithm; Tidal power; Mathematics; Algorithm; Artificial intelligence; Statistics; Engineering; Machine learning; Artificial neural network","score_opus":0.01812674541682845,"score_gpt":0.25463908118795475,"score_spread":0.2365123357711263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808230357","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":[0.003662567,0.0000748268,0.9944663,0.00024211963,0.0006007101,0.000110037545,0.0000044382145,0.00031951632,0.0005194746],"genre_scores_gemma":[0.9880774,0.000030373154,0.0070083733,0.00007981173,0.00019476537,0.0000671545,0.0000023136922,0.000016950697,0.0045228545],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985047,0.00009348314,0.00019467818,0.00047048097,0.00025681374,0.00047985182],"domain_scores_gemma":[0.9991184,0.000058640067,0.00006342382,0.00033754163,0.00027006955,0.00015192901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024055413,0.00019192425,0.0001485477,0.00022779609,0.0006581605,0.00011309309,0.0002559439,0.000082179526,0.000018719504],"category_scores_gemma":[0.000007825657,0.00018010402,0.00006262479,0.00051385054,0.00011876261,0.00040306515,0.000008784257,0.00022471593,0.0000119422075],"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":[0.00006383463,0.00021212688,0.000009538912,0.000026946846,0.000033520264,0.000012308787,0.0008372323,0.033498257,0.00004367848,0.010365941,0.0002117069,0.9546849],"study_design_scores_gemma":[0.0007390026,0.0012495345,0.00012173597,0.000039189723,0.000026930094,0.000039077986,0.00045596214,0.8362064,0.002896147,0.0019667835,0.15591866,0.00034058426],"about_ca_topic_score_codex":0.0015527977,"about_ca_topic_score_gemma":0.00012366223,"teacher_disagreement_score":0.98745793,"about_ca_system_score_codex":0.00013360151,"about_ca_system_score_gemma":0.00011619527,"threshold_uncertainty_score":0.7344429},"labels":[],"label_agreement":null},{"id":"W2884269146","doi":"10.1109/tste.2018.2857764","title":"Flexibility Provisions From a Fast Charging Facility Equipped With DERs for Wind Integrated Grids","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":19,"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":"Majmaah University","keywords":"Wind power; Flexibility (engineering); Distributed generation; Photovoltaic system; Energy storage; Automotive engineering; Reliability engineering; Computer science; Engineering; Renewable energy; Power (physics); Electrical engineering; Economics","score_opus":0.007338052891832092,"score_gpt":0.20966276624896887,"score_spread":0.20232471335713678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884269146","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":[0.24004492,0.00003407441,0.7582804,0.000051248087,0.00018176268,0.00027658787,0.00018517561,0.00035734678,0.000588509],"genre_scores_gemma":[0.9967916,0.000009349848,0.0012089111,0.00007882645,0.00009623376,0.00010348097,0.000043695512,0.000044708304,0.0016231777],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984582,0.000030348023,0.00025988705,0.00041325015,0.00017857442,0.0006597329],"domain_scores_gemma":[0.9990085,0.00010681799,0.00003441156,0.00040130332,0.0002986303,0.00015036078],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010926193,0.00029989413,0.00026513997,0.00017586267,0.00042089983,0.00007827611,0.0001798457,0.00014896532,0.00022007455],"category_scores_gemma":[0.0000099301005,0.00025171167,0.00010562216,0.00061212573,0.00012017857,0.00029376874,0.0000016090871,0.00028635093,0.0000055420605],"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":[0.0017580054,0.0003956051,0.00015461497,0.00040139837,0.00071622146,0.0000416276,0.002408944,0.76412374,0.01868413,0.0014507105,0.0024093867,0.20745559],"study_design_scores_gemma":[0.0046134493,0.002638229,0.00061631174,0.00013647656,0.00027284597,0.000025621372,0.010898194,0.39117116,0.50366247,0.0057478454,0.07844515,0.0017722304],"about_ca_topic_score_codex":0.0013953821,"about_ca_topic_score_gemma":0.0004926709,"teacher_disagreement_score":0.75707144,"about_ca_system_score_codex":0.00038956606,"about_ca_system_score_gemma":0.00015655007,"threshold_uncertainty_score":0.9999935},"labels":[],"label_agreement":null},{"id":"W2885339850","doi":"10.1109/tste.2018.2863941","title":"Investigation of Horizontal and Vertical Wind Shear Effects Using a Wind Turbine Emulator","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Wind shear; Aerodynamics; Wind power; Turbine; Wind speed; Wind profile power law; Marine engineering; Engineering; Environmental science; Meteorology; Mechanical engineering; Aerospace engineering; Physics; Electrical engineering","score_opus":0.00948840736049418,"score_gpt":0.2152482037730397,"score_spread":0.2057597964125455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885339850","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":[0.8771247,0.000085215834,0.12202751,0.00001955369,0.00019364686,0.00008414155,0.0000017322504,0.00007896308,0.0003844969],"genre_scores_gemma":[0.99890244,0.00002324409,0.0006387734,0.000025979629,0.0000919282,0.000008135189,0.0000018729728,0.000033278826,0.0002743735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989399,0.000033612698,0.00019091261,0.00018824288,0.00023074528,0.00041658705],"domain_scores_gemma":[0.9994363,0.00006383432,0.000011249259,0.00015647529,0.0001164099,0.00021569338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009794413,0.00016305476,0.00018528402,0.00025126408,0.00015614413,0.000031002466,0.00006744961,0.0001115054,0.00003621601],"category_scores_gemma":[0.000008809544,0.0001623586,0.000041546507,0.00036491288,0.00016011191,0.00020893353,0.0000027885114,0.00012901648,0.0000030550602],"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":[0.0007383451,0.00022928885,0.00033437612,0.0014316082,0.0007446976,0.00024879785,0.0023493876,0.49257633,0.47335303,0.004997065,0.0007288536,0.022268206],"study_design_scores_gemma":[0.0008661286,0.0005057431,0.00075252535,0.00007210955,0.00003308489,0.000020434574,0.00027193,0.06128782,0.9344581,0.00048213077,0.0009852407,0.0002648006],"about_ca_topic_score_codex":0.00035416972,"about_ca_topic_score_gemma":0.000024886001,"teacher_disagreement_score":0.46110502,"about_ca_system_score_codex":0.00018656225,"about_ca_system_score_gemma":0.000105437124,"threshold_uncertainty_score":0.66207916},"labels":[],"label_agreement":null},{"id":"W2886770490","doi":"10.1109/tste.2018.2864938","title":"A Sequence-Component-Based Power-Flow Analysis for Unbalanced Droop-Controlled Hybrid AC/DC Microgrids","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; University of Waterloo","funders":"","keywords":"Voltage droop; Microgrid; Converters; Slack bus; Control theory (sociology); AC power; Computer science; Voltage; Power (physics); Component (thermodynamics); MATLAB; Algorithm; Power-flow study; Engineering; Voltage source; Electrical engineering","score_opus":0.006132979182080902,"score_gpt":0.20617050794254274,"score_spread":0.20003752876046185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886770490","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":[0.01032868,0.0002932174,0.98702693,0.00014532795,0.000538281,0.0005028096,0.00011347842,0.0005512443,0.00050002424],"genre_scores_gemma":[0.99235415,0.00009352598,0.004291065,0.00025486306,0.0001448375,0.00066122296,0.000078855446,0.000081290425,0.0020401864],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979753,0.000053644813,0.0004844412,0.00044981172,0.0002254384,0.0008113469],"domain_scores_gemma":[0.9986346,0.00014597367,0.00008332303,0.0004851345,0.0004830334,0.00016795639],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021634335,0.00039394374,0.000664205,0.0008091208,0.00039696242,0.00013759815,0.00025696043,0.00014615766,0.00031733],"category_scores_gemma":[0.000009791936,0.0003954744,0.00060543075,0.0011245222,0.000099511686,0.00022783029,0.0000013323719,0.00015224141,0.000013391679],"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":[0.0008018185,0.00013952989,0.0000032667317,0.0000424361,0.0010571504,0.000016276319,0.000055724588,0.9794399,0.009653078,0.0001152005,0.00037969768,0.008295885],"study_design_scores_gemma":[0.005752425,0.00026453502,0.000007052901,0.000012832798,0.00064538466,0.000003615134,0.00012517585,0.8680737,0.11099791,0.00011042864,0.013578078,0.0004288481],"about_ca_topic_score_codex":0.00018986753,"about_ca_topic_score_gemma":0.00011502871,"teacher_disagreement_score":0.9827359,"about_ca_system_score_codex":0.00036801575,"about_ca_system_score_gemma":0.000117850876,"threshold_uncertainty_score":0.99984974},"labels":[],"label_agreement":null},{"id":"W2890813689","doi":"10.1109/tste.2018.2869229","title":"A Reactive Power Control Scheme for DER-Caused Voltage Rise Mitigation in Secondary Systems","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"ATCO (Canada); University of Alberta","funders":"","keywords":"AC power; Overvoltage; Voltage optimisation; Voltage regulation; Reliability engineering; Distributed generation; Electric power system; Voltage; Engineering; Electrical engineering; Computer science; Renewable energy; Power (physics)","score_opus":0.0045838277779806,"score_gpt":0.20688277878155578,"score_spread":0.20229895100357517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890813689","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":[0.045178838,0.00014659189,0.950185,0.000044128752,0.00078036246,0.0005509791,0.0001843072,0.00031237013,0.002617427],"genre_scores_gemma":[0.99776673,0.000008970918,0.00015426367,0.00004450796,0.00009233201,0.00044414974,0.00002795093,0.000067447654,0.0013936262],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985481,0.000038915026,0.00034602865,0.0003079022,0.00016856777,0.00059049897],"domain_scores_gemma":[0.99909496,0.00012020586,0.000050918356,0.00028151326,0.00034124812,0.000111168636],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021372011,0.00025450918,0.00027139604,0.00033501486,0.0001730097,0.00007618542,0.00011894058,0.00021556225,0.000078619196],"category_scores_gemma":[0.000014464631,0.00029533906,0.00010672127,0.00043105744,0.00007257738,0.0005147916,8.6913127e-7,0.00022791403,0.00001634951],"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":[0.0016558962,0.00088944077,0.000038423663,0.0008858748,0.0008928045,0.00014752761,0.0016528683,0.87149215,0.09111331,0.014284346,0.010613423,0.006333955],"study_design_scores_gemma":[0.009690387,0.0014258467,0.00028842437,0.00018866727,0.00017115979,0.000022847898,0.0068188747,0.67151344,0.20726992,0.0010584719,0.10016042,0.0013915094],"about_ca_topic_score_codex":0.00030210978,"about_ca_topic_score_gemma":0.00011243649,"teacher_disagreement_score":0.9525879,"about_ca_system_score_codex":0.0008276453,"about_ca_system_score_gemma":0.00010819757,"threshold_uncertainty_score":0.9999499},"labels":[],"label_agreement":null},{"id":"W2891022339","doi":"10.1109/tste.2018.2871074","title":"PV Solar System Control as STATCOM (PV-STATCOM) for Power Oscillation Damping","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":118,"is_retracted":false,"has_abstract":true,"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; Ontario Centres of Excellence","keywords":"Photovoltaic system; Control theory (sociology); Electric power system; Engineering; Inverter; Oscillation (cell signaling); Power (physics); Electronic engineering; Computer science; Electrical engineering; Control (management); Voltage; Physics","score_opus":0.005725827858861667,"score_gpt":0.21072402707318863,"score_spread":0.20499819921432696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891022339","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":[0.0028809917,0.00006601662,0.9839261,0.00007699943,0.0015933765,0.0005466115,0.00007843087,0.00080125214,0.010030191],"genre_scores_gemma":[0.9947313,0.000012181678,0.0006689714,0.00012246463,0.0000705918,0.00025368689,0.000011294714,0.000083588595,0.0040459386],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99809396,0.000094695395,0.0005095463,0.00037737,0.00027015177,0.00065426243],"domain_scores_gemma":[0.99855363,0.00017711466,0.00007406026,0.0004783675,0.00053640746,0.00018044567],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00039605936,0.00030275155,0.00036677637,0.00027638086,0.0005273466,0.00013260028,0.00017133178,0.00018675427,0.00019589369],"category_scores_gemma":[0.000018603543,0.00031897312,0.00017612886,0.00040408608,0.000065469765,0.00039694255,0.0000013911435,0.0001356131,0.00003325231],"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":[0.00021750251,0.00007831481,0.000011912749,0.0003835322,0.0001729587,0.000010247166,0.0006765681,0.9864329,0.0003791434,0.009929511,0.0008647858,0.0008425993],"study_design_scores_gemma":[0.0031115094,0.0005363827,0.000028165821,0.00009272695,0.000096396616,0.000023296008,0.0072317715,0.80309653,0.013799366,0.00034862102,0.17084369,0.000791534],"about_ca_topic_score_codex":0.00023816737,"about_ca_topic_score_gemma":0.000086906795,"teacher_disagreement_score":0.9918503,"about_ca_system_score_codex":0.0007403489,"about_ca_system_score_gemma":0.00012318179,"threshold_uncertainty_score":0.9999262},"labels":[],"label_agreement":null},{"id":"W2891043964","doi":"10.1109/tste.2018.2869882","title":"Joint Arbitrage and Operating Reserve Scheduling of Energy Storage Through Optimal Adaptive Allocation of the State of Charge","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Arbitrage; Energy storage; Computer science; Scheduling (production processes); Mathematical optimization; Economics; Power (physics); Finance","score_opus":0.008593630645897606,"score_gpt":0.19620208781578674,"score_spread":0.18760845716988914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891043964","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":[0.15290199,0.00040903164,0.84587175,0.00003447411,0.000110471476,0.00010070568,0.000020944572,0.000033853918,0.0005167888],"genre_scores_gemma":[0.99617445,0.0003085239,0.002823027,0.00002522393,0.00002502647,0.000025821228,0.0000022879128,0.000029382281,0.00058626157],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990153,0.00005599475,0.0003815171,0.00015961222,0.00015959496,0.00022802597],"domain_scores_gemma":[0.9992205,0.00003682588,0.00012041154,0.0002378734,0.00035213964,0.000032233118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014520441,0.00015030133,0.00024997292,0.00011675119,0.00012433044,0.000013193877,0.00011392965,0.00006844553,0.000031905915],"category_scores_gemma":[0.000007793011,0.00012971465,0.00007587448,0.0003538286,0.0001273519,0.0002565296,0.000004352109,0.000117332806,1.652806e-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":[0.000052667587,0.000049813796,7.3518186e-7,0.000088196066,0.000090362075,9.91197e-7,0.0008533609,0.95192575,0.042671166,0.0024442608,0.000009215058,0.0018134663],"study_design_scores_gemma":[0.0003243901,0.00013652649,0.00000871274,0.00003607109,0.000036150414,0.0000014588989,0.0005327779,0.4396427,0.5589454,0.0001323764,0.00011623278,0.00008717745],"about_ca_topic_score_codex":0.001360332,"about_ca_topic_score_gemma":0.00013817778,"teacher_disagreement_score":0.84327245,"about_ca_system_score_codex":0.00006702836,"about_ca_system_score_gemma":0.00007060936,"threshold_uncertainty_score":0.528961},"labels":[],"label_agreement":null},{"id":"W2910963647","doi":"10.1109/tste.2019.2892943","title":"Simultaneous Fast Frequency Control and Power Oscillation Damping by Utilizing PV Solar System as PV-STATCOM","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":118,"is_retracted":false,"has_abstract":true,"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","keywords":"Control theory (sociology); Frequency deviation; Controller (irrigation); Automatic frequency control; Electric power system; Voltage droop; Engineering; Grid-connected photovoltaic power system; Photovoltaic system; Power control; AC power; Maximum power point tracking; Power (physics); Inverter; Computer science; Voltage regulator; Voltage; Electrical engineering; Control (management); Physics","score_opus":0.0028509981930842144,"score_gpt":0.1835382975948347,"score_spread":0.1806872994017505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910963647","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":[0.033950325,0.00034226378,0.9488446,0.000038527305,0.0007419622,0.0003909555,0.000052679177,0.0006146856,0.015024011],"genre_scores_gemma":[0.99646646,0.000041503983,0.00014724511,0.00006581649,0.000011962563,0.000047380574,0.000009142948,0.00006532152,0.0031451727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982886,0.00010275724,0.00042739784,0.0003919304,0.0002661319,0.0005232005],"domain_scores_gemma":[0.998971,0.00021920203,0.00006376179,0.00038395,0.00019236338,0.00016971743],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022592496,0.0002990885,0.0003613207,0.00019924209,0.0002669774,0.00013686321,0.0001203991,0.00019117647,0.00016560509],"category_scores_gemma":[0.00001384375,0.00031983605,0.000090446614,0.00031705204,0.000034765937,0.0003899995,0.0000016659445,0.00020356753,0.000029733073],"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":[0.00004334573,0.00003975142,0.000055850836,0.00037413358,0.00008445,0.00002737895,0.00044267636,0.99413764,0.0022073607,0.001834996,0.00006324332,0.00068917684],"study_design_scores_gemma":[0.0016135552,0.00017647528,0.000017330198,0.00009660194,0.000050347808,0.00004617105,0.008655658,0.9734323,0.0023705317,0.0000652112,0.012879321,0.00059651386],"about_ca_topic_score_codex":0.00047383472,"about_ca_topic_score_gemma":0.0000273547,"teacher_disagreement_score":0.9625161,"about_ca_system_score_codex":0.0005450663,"about_ca_system_score_gemma":0.000063048916,"threshold_uncertainty_score":0.9999254},"labels":[],"label_agreement":null},{"id":"W2911905556","doi":"10.1109/tste.2019.2897288","title":"Demand Response Strategy Applied to Residential Electric Water Heaters Using Dynamic Programming and K-Means Clustering","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Cluster analysis; Demand response; Peak demand; Peaking power plant; Computer science; Silhouette; Consumption (sociology); Process (computing); Dynamic demand; Dynamic programming; Energy consumption; Cluster (spacecraft); Load management; Demand management; Hierarchical clustering; Control (management); Electricity; Power (physics); Engineering; Electric power system; Artificial intelligence; Electrical engineering; Algorithm","score_opus":0.004593137353370297,"score_gpt":0.1996663807054152,"score_spread":0.1950732433520449,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911905556","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":[0.4296008,0.000025253621,0.569321,0.000029565877,0.00025897435,0.0002453819,8.12148e-7,0.00023776981,0.00028045144],"genre_scores_gemma":[0.9954539,0.000026751368,0.00092713913,0.00005820637,0.00003532987,0.00013257343,0.000002817847,0.00010775074,0.0032555375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980805,0.000058236306,0.00029376967,0.00043751672,0.00023442708,0.000895567],"domain_scores_gemma":[0.9993657,0.00004376774,0.00001874379,0.00036004838,0.0000472318,0.00016449505],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029782427,0.00031913165,0.0002612244,0.0007524604,0.00022255449,0.00018743402,0.00015212363,0.00011548323,0.000051814448],"category_scores_gemma":[0.0000011878262,0.000317179,0.00006381312,0.00048755,0.00001973564,0.00023883495,0.000008351108,0.00017856073,0.000017878374],"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":[0.00043839027,0.000025080622,0.000002442524,0.00012315609,0.00009248633,0.00004323464,0.00023204104,0.9388795,0.05645088,0.000073200164,0.000017330602,0.0036222816],"study_design_scores_gemma":[0.0011279362,0.00032132503,0.00009885071,0.000046251032,0.00009576562,0.000033009044,0.0019433497,0.86352295,0.12478362,0.000059780927,0.0072112787,0.0007559137],"about_ca_topic_score_codex":0.00033508876,"about_ca_topic_score_gemma":0.00012306838,"teacher_disagreement_score":0.5683939,"about_ca_system_score_codex":0.0005833813,"about_ca_system_score_gemma":0.00003258555,"threshold_uncertainty_score":0.99992806},"labels":[],"label_agreement":null},{"id":"W2920352247","doi":"10.1109/tste.2019.2902033","title":"An Improved Damping Method for Virtual Synchronous Machines","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":146,"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":"Control theory (sociology); Damper; Inverter; Electromagnetic coil; Control engineering; Controller (irrigation); Synchronous motor; Computer science; Electric power system; Engineering; Energy (signal processing); Power (physics); Damping torque; Inertial frame of reference; Control (management); Induction motor; Voltage; Electrical engineering","score_opus":0.0028255540399286924,"score_gpt":0.21208125199009448,"score_spread":0.2092556979501658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2920352247","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":[0.0030184502,0.00014767583,0.9950426,0.000026917758,0.00063411635,0.000283126,0.000018298442,0.0004056501,0.0004231388],"genre_scores_gemma":[0.98081493,0.00008628219,0.014355446,0.00012199368,0.000117342584,0.00022779545,0.000021755639,0.0000868625,0.004167572],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990261,0.000030020814,0.00019814952,0.00025533367,0.000076908356,0.00041344302],"domain_scores_gemma":[0.99940634,0.000085434236,0.00002632919,0.0002897294,0.00010732977,0.000084857005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013450181,0.0002002572,0.00021145391,0.00019261858,0.00014962186,0.000074452146,0.00014026927,0.000117475334,0.00013165272],"category_scores_gemma":[0.0000022346896,0.00020620876,0.000107538566,0.00019415212,0.000009648325,0.00033464367,6.430737e-7,0.00011114809,0.0000060932875],"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":[0.00006404683,0.000045505778,4.440062e-7,0.00005840697,0.000054389613,0.0000015810917,0.000080047015,0.8709354,0.016031967,0.0007072363,0.000039393795,0.111981615],"study_design_scores_gemma":[0.0008708554,0.00029400646,0.0000019720578,0.000007406364,0.000035981706,0.000004491124,0.00037922867,0.96422344,0.02501093,0.00015071828,0.008771038,0.0002499105],"about_ca_topic_score_codex":0.0002851311,"about_ca_topic_score_gemma":0.000060260805,"teacher_disagreement_score":0.9806872,"about_ca_system_score_codex":0.00015593773,"about_ca_system_score_gemma":0.00004341611,"threshold_uncertainty_score":0.84089494},"labels":[],"label_agreement":null},{"id":"W2946286752","doi":"10.1109/tste.2019.2917374","title":"Probabilistic Modeling of Energy Storage to Quantify Market Constrained Reliability Value to Active Distribution Systems","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":33,"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":"Probabilistic logic; Reliability engineering; Reliability (semiconductor); Computer science; Energy storage; Energy market; Grid; Markov chain; Mathematical optimization; Engineering; Renewable energy; Power (physics)","score_opus":0.005939595676407735,"score_gpt":0.19980995695956105,"score_spread":0.19387036128315333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946286752","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":[0.08746815,0.00004667393,0.90655136,0.00007433277,0.0012780244,0.00069982815,0.00026102224,0.00028114003,0.0033394448],"genre_scores_gemma":[0.9955813,0.000018133063,0.00014768317,0.00003607245,0.000032626092,0.00038662265,0.000016146016,0.000055124467,0.0037262538],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975232,0.00016440505,0.0006566149,0.0005707579,0.00037149512,0.0007135171],"domain_scores_gemma":[0.9980858,0.00022794782,0.00006671561,0.00080611237,0.0005290115,0.00028440577],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005456556,0.00035426152,0.0005829498,0.00024291013,0.00011829629,0.000047885376,0.00028100717,0.00021755071,0.00005753121],"category_scores_gemma":[0.000071831615,0.00036589932,0.00017650651,0.000800089,0.000050318507,0.00025224255,0.000006137088,0.00020583053,0.000013733165],"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":[0.00027540306,0.00013291478,0.0000016207096,0.0007467914,0.00006117905,0.0000071848535,0.00017402244,0.98001814,0.00078875385,0.017011855,0.00029412255,0.00048799577],"study_design_scores_gemma":[0.00050475827,0.00036633934,0.000016719934,0.000284603,0.000046147168,0.0000102337335,0.0021036803,0.97532666,0.0076731807,0.00051745324,0.012639043,0.0005112062],"about_ca_topic_score_codex":0.002672471,"about_ca_topic_score_gemma":0.000080369304,"teacher_disagreement_score":0.9081132,"about_ca_system_score_codex":0.0012250629,"about_ca_system_score_gemma":0.00017559658,"threshold_uncertainty_score":0.9998793},"labels":[],"label_agreement":null},{"id":"W2954118707","doi":"10.1109/tste.2018.2862405","title":"Enhancement of Solar Farm Connectivity With Smart PV Inverter PV-STATCOM","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Western University","funders":"Ontario Centres of Excellence","keywords":"Photovoltaic system; Grid-connected photovoltaic power system; Inverter; Voltage; Grid; Engineering; Transient (computer programming); Grid code; Electrical engineering; Maximum power point tracking; Computer science; Automotive engineering; AC power","score_opus":0.003940948522792451,"score_gpt":0.17638136784719635,"score_spread":0.1724404193244039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954118707","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":[0.020427685,0.00008795609,0.9760154,0.000041873976,0.00024393195,0.00012998994,0.0000080489335,0.00013997067,0.002905181],"genre_scores_gemma":[0.99669075,0.00014007807,0.00057918625,0.00010558889,0.00004796111,0.00007298888,0.0000041662197,0.000038045237,0.002321219],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99905324,0.000028433236,0.00020365063,0.00020015209,0.00015365193,0.00036087906],"domain_scores_gemma":[0.9993615,0.000034622313,0.000038307608,0.00026286457,0.00023187367,0.00007083198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008815226,0.00018829621,0.0002155968,0.00016814537,0.0001434667,0.00002732572,0.00009886605,0.00008017216,0.00025742766],"category_scores_gemma":[0.0000016851121,0.00017309476,0.000062242514,0.00030746977,0.000079930855,0.0001678844,0.0000011990059,0.0001092688,0.000007947462],"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":[0.00041543384,0.000364078,0.000022120073,0.00019903135,0.0004009899,0.000022800601,0.00069172354,0.9250432,0.01685629,0.0011170786,0.00050814904,0.05435911],"study_design_scores_gemma":[0.0015563287,0.00071905385,0.000023429327,0.00003732545,0.00008820324,0.0000073626375,0.00073820644,0.2505113,0.7175663,0.0001966151,0.028167479,0.00038838564],"about_ca_topic_score_codex":0.0005305416,"about_ca_topic_score_gemma":0.0005355187,"teacher_disagreement_score":0.9762631,"about_ca_system_score_codex":0.00015000641,"about_ca_system_score_gemma":0.000055418543,"threshold_uncertainty_score":0.7058599},"labels":[],"label_agreement":null},{"id":"W2955445790","doi":"10.1109/tste.2019.2926456","title":"Optimal Sizing and Scheduling of LOHC-Based Generation and Storage Plants for Concurrent Services to Transportation Sector and Ancillary Services Market","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sizing; Scheduling (production processes); Hydrogen storage; Computer science; Environmental economics; Business; Hydrogen; Engineering; Operations management; Economics; Chemistry","score_opus":0.004270743856431274,"score_gpt":0.18776120806570437,"score_spread":0.1834904642092731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955445790","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":[0.77159375,0.0008565575,0.2271418,0.000016319906,0.00010180545,0.00018265616,0.000055823308,0.000037266374,0.000014006963],"genre_scores_gemma":[0.9977192,0.00017778316,0.0018321229,0.00006180968,0.000034571283,0.000031610914,0.00002256324,0.000025233272,0.00009508691],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99932307,0.000010271759,0.00017051435,0.00019570484,0.0000921016,0.00020833337],"domain_scores_gemma":[0.99969697,0.000045074445,0.00003426709,0.00007768116,0.00007035163,0.00007566505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007137016,0.00014760112,0.00017335096,0.00014369578,0.00009130602,0.000040657786,0.00003798143,0.00008929291,0.000014859622],"category_scores_gemma":[3.6255784e-7,0.00015302657,0.000023646551,0.00011213933,0.000010250009,0.00020882882,5.3370786e-7,0.00007065855,7.8251254e-8],"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":[0.000088834684,0.00001417874,0.0001266453,0.0016245684,0.000041654443,0.0000021397252,0.00046182208,0.95262533,0.03398718,0.00011280923,0.000008952283,0.010905852],"study_design_scores_gemma":[0.00092492264,0.00026625322,0.000865147,0.00008606814,0.000038455513,0.0000032621995,0.0013112106,0.9279018,0.06692296,0.000018516777,0.0014430551,0.00021834984],"about_ca_topic_score_codex":0.00012801027,"about_ca_topic_score_gemma":0.00016761036,"teacher_disagreement_score":0.22612545,"about_ca_system_score_codex":0.000039623254,"about_ca_system_score_gemma":0.000021569389,"threshold_uncertainty_score":0.6240243},"labels":[],"label_agreement":null},{"id":"W2965955284","doi":"10.1109/tste.2018.2862351","title":"Integrated Disturbance Response Modeling of Wind-Integrated Power Systems to Quantify the Operational Reliability Benefits of Flywheel Energy Storage","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":18,"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":"Reliability engineering; Electric power system; Wind power; Energy storage; Engineering; Renewable energy; Flywheel; Probabilistic logic; Automotive engineering; Computer science; Power (physics); Electrical engineering","score_opus":0.009474493280562333,"score_gpt":0.20950962949402518,"score_spread":0.20003513621346286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965955284","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":[0.16701706,0.00032493897,0.8302733,0.00013159032,0.001059468,0.00025870802,0.00014694486,0.00015483065,0.00063321285],"genre_scores_gemma":[0.99592423,0.000039289684,0.00029403056,0.000059783553,0.00003106142,0.00012614601,0.000007915231,0.000055681823,0.003461875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974588,0.00031470772,0.00083701336,0.00043768573,0.00042281018,0.00052896567],"domain_scores_gemma":[0.99702734,0.00030452452,0.00009680751,0.00090084586,0.0015327284,0.00013775671],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010090887,0.0003476957,0.0005090445,0.0002884771,0.00025055427,0.000051594674,0.00045088172,0.00021336389,0.000057726185],"category_scores_gemma":[0.00011852358,0.0002665793,0.00017011285,0.001142579,0.00019590883,0.00026779075,0.0000061683013,0.00025074076,0.000004520947],"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":[0.0009002009,0.00013797132,0.000003262449,0.000117323,0.0000768265,0.000003283428,0.00063564634,0.9854915,0.0024459895,0.009466892,0.00040895393,0.0003121473],"study_design_scores_gemma":[0.00050490425,0.00056508125,0.00007255836,0.00029446316,0.00004074596,0.000011771325,0.003894584,0.9265795,0.04064882,0.0001295757,0.02683658,0.00042142585],"about_ca_topic_score_codex":0.0053254445,"about_ca_topic_score_gemma":0.0003086199,"teacher_disagreement_score":0.82997924,"about_ca_system_score_codex":0.0005179527,"about_ca_system_score_gemma":0.00028800612,"threshold_uncertainty_score":0.99997866},"labels":[],"label_agreement":null},{"id":"W2973118174","doi":"10.1109/tste.2019.2940488","title":"Toward Flexible Risk-Limiting Operation of Multi-Terminal HVDC Grids With Vast Wind Generation","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","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":false,"ca_institutions":"University of Saskatchewan","funders":"National Natural Science Foundation of China; Canada School of Energy and Environment","keywords":"Grid; High-voltage direct current; Wind power; Asynchronous communication; Computer science; Converters; AC power; Engineering; Reliability engineering; Voltage; Control theory (sociology); Electrical engineering; Direct current; Telecommunications; Control (management); Mathematics","score_opus":0.014042643036568301,"score_gpt":0.21201662262112014,"score_spread":0.19797397958455185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973118174","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":[0.25431684,0.000057521123,0.7440137,0.000006669302,0.00037626832,0.00026720823,0.000009920762,0.00016661182,0.00078523107],"genre_scores_gemma":[0.9936718,0.000058323763,0.0011699903,0.000010402772,0.000135382,0.000093912386,0.000010673523,0.000056396708,0.0047931564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877775,0.000057160218,0.00033683408,0.0002672191,0.00022751627,0.00033351156],"domain_scores_gemma":[0.9993841,0.000022218108,0.000083766274,0.0002600712,0.0001810627,0.00006875918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019755436,0.00021989473,0.00024202694,0.00026580383,0.00018876378,0.00006639307,0.00008590426,0.00014820954,0.00009983551],"category_scores_gemma":[0.0000021178291,0.00020664047,0.00007828534,0.00033638603,0.000023341705,0.00046518602,0.000001067535,0.00021294094,0.000016045464],"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":[0.00004463438,0.000065509186,0.000042790038,0.00017883204,0.00006472686,0.000008736891,0.0003008238,0.9612037,0.022296011,0.00022858202,0.00001788492,0.015547767],"study_design_scores_gemma":[0.0013436753,0.0005033931,0.00013295468,0.00007408562,0.000057014957,0.00004537541,0.0015959346,0.6013982,0.3903019,0.000008556903,0.004161777,0.00037705302],"about_ca_topic_score_codex":0.001229336,"about_ca_topic_score_gemma":0.00013567597,"teacher_disagreement_score":0.74284375,"about_ca_system_score_codex":0.00022095865,"about_ca_system_score_gemma":0.00006334068,"threshold_uncertainty_score":0.84265536},"labels":[],"label_agreement":null},{"id":"W2973125106","doi":"10.1109/tste.2019.2941418","title":"Coordinated Planning Strategy for Integrated Energy Systems in a District Energy Sector","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":100,"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; National Natural Science Foundation of China; National Key Research and Development Program of China; U.S. Department of Energy","keywords":"Mathematical optimization; Energy carrier; Distributed generation; Energy (signal processing); Energy planning; Computer science; Energy flow; Integrated business planning; Operational planning; Linear programming; Electric power system; Integer programming; Convergence (economics); Electricity generation; Engineering; Power (physics); Electricity; Renewable energy; Mathematics; Electrical engineering","score_opus":0.008455253863199244,"score_gpt":0.20565232206514325,"score_spread":0.197197068201944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973125106","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":[0.005893779,0.0006490351,0.98210937,0.000014233146,0.0019325733,0.00029967184,0.00007721204,0.00080427545,0.008219844],"genre_scores_gemma":[0.95314354,0.00010145032,0.00008865356,0.000041115138,0.00009000882,0.0009121398,0.00015162968,0.0001998548,0.045271587],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970723,0.00013969152,0.0007772934,0.0005815124,0.00030154,0.0011277075],"domain_scores_gemma":[0.99847823,0.0002583372,0.0001328939,0.00048349358,0.00047262324,0.00017441894],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023171722,0.00059290737,0.00066109863,0.0011385824,0.00015318838,0.00020012526,0.00032044537,0.000569723,0.00012043101],"category_scores_gemma":[0.000011505402,0.00060822105,0.0001815487,0.0017928932,0.000024926652,0.0004691513,0.0000023091477,0.00033101958,0.00000800405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017212844,0.00009737517,0.000010028443,0.00020013198,0.000187908,0.00005425321,0.00006943131,0.98269343,0.0012172335,0.011836775,0.0016014883,0.001859824],"study_design_scores_gemma":[0.0016365061,0.0002969909,0.000003837704,0.00021672045,0.000039714363,0.000022003383,0.0026367141,0.90330803,0.021320792,0.00010746135,0.069687895,0.0007233484],"about_ca_topic_score_codex":0.016203284,"about_ca_topic_score_gemma":0.0006883384,"teacher_disagreement_score":0.98202074,"about_ca_system_score_codex":0.0020665096,"about_ca_system_score_gemma":0.00021095885,"threshold_uncertainty_score":0.9996369},"labels":[],"label_agreement":null},{"id":"W2987441294","doi":"10.1109/tste.2019.2950168","title":"Coordinated Planning of Converter-Based DG Units and Soft Open Points Incorporating Active Management in Unbalanced Distribution Networks","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":112,"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 Saskatchewan","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; China Scholarship Council; Chongqing Research Program of Basic Research and Frontier Technology; National Natural Science Foundation of China","keywords":"AC power; Converters; Distributed generation; Power (physics); Engineering; Compensation (psychology); Maximum power transfer theorem; Integer programming; Control theory (sociology); Computer science; Three-phase; Linear programming; Node (physics); Voltage; Electronic engineering; Control engineering; Control (management); Electrical engineering","score_opus":0.007060818769819061,"score_gpt":0.2145919051234211,"score_spread":0.20753108635360204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2987441294","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":[0.12803301,0.000026876718,0.870357,0.000029119432,0.00017527954,0.00038522077,0.00006695218,0.000095641786,0.00083092815],"genre_scores_gemma":[0.9992849,0.000011157693,0.00013396448,0.000023333665,0.0000057081456,0.000081103775,0.00019540473,0.000029303417,0.00023508372],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888533,0.00005836669,0.00031208192,0.00025411445,0.00012483435,0.00036525537],"domain_scores_gemma":[0.9994309,0.00007365463,0.00008165048,0.00020319506,0.00014397697,0.00006661787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018486322,0.0002040227,0.0002932445,0.00017695491,0.00008026132,0.00005638376,0.00016768646,0.00012366899,0.000024568315],"category_scores_gemma":[0.000004411084,0.00023752292,0.000029321931,0.00088229275,0.00003941015,0.00039643052,0.0000074140025,0.00020990922,0.0000014720894],"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":[0.00024944288,0.00007298364,0.00013285584,0.00014407608,0.000064591666,0.000028642115,0.00004963221,0.99087596,0.00026747424,0.0016688159,0.00006645565,0.006379099],"study_design_scores_gemma":[0.002522325,0.00021107848,0.00078781287,0.0002089459,0.000033776127,0.0000022705738,0.0021699823,0.97714907,0.01598653,0.00021448659,0.00039589094,0.00031783467],"about_ca_topic_score_codex":0.00030935768,"about_ca_topic_score_gemma":0.000025412475,"teacher_disagreement_score":0.87125194,"about_ca_system_score_codex":0.00044080074,"about_ca_system_score_gemma":0.000045403787,"threshold_uncertainty_score":0.9685904},"labels":[],"label_agreement":null},{"id":"W3000723039","doi":"10.1109/tste.2020.2967428","title":"Spatio-Temporal Flexibility Management in Low-Carbon Power Systems","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Microgrid; Renewable energy; Scheduling (production processes); Wind power; Electric power system; Flexibility (engineering); Electricity generation; Reliability engineering; Mathematical optimization; Distributed computing; Power (physics); Engineering; Electrical engineering","score_opus":0.009397364776037984,"score_gpt":0.19943015675183715,"score_spread":0.19003279197579917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000723039","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":[0.08301375,0.00020695197,0.8611388,0.00032068446,0.0016287805,0.00055235595,0.0000071694253,0.0011282744,0.05200322],"genre_scores_gemma":[0.9960094,0.00007709381,0.00011018483,0.00016814047,0.000051334828,0.00031470717,0.000007853997,0.00007641641,0.003184866],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981269,0.000059846418,0.0004302407,0.00044474,0.00032944334,0.0006087875],"domain_scores_gemma":[0.9992608,0.00002785126,0.000032786804,0.00045342662,0.000050923558,0.00017420514],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016562022,0.00031036083,0.00028966228,0.00033915916,0.00007323074,0.00007174016,0.00024430582,0.00010965974,0.00010219483],"category_scores_gemma":[0.0000024030348,0.00035415217,0.00009533766,0.0008826793,0.000030848998,0.00019695339,0.000005638681,0.00021923169,0.000019317],"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":[0.00006740174,0.0001000841,0.000025894791,0.00036716263,0.000108919114,0.00022723617,0.00015073715,0.99423665,0.000015727395,0.0036225172,0.0005034993,0.0005741549],"study_design_scores_gemma":[0.0014058258,0.00016648998,0.00020330668,0.00007340133,0.000054213444,0.0000025153486,0.0032768839,0.905297,0.0040218183,0.00019406584,0.08456199,0.00074250693],"about_ca_topic_score_codex":0.0008228532,"about_ca_topic_score_gemma":0.00012634836,"teacher_disagreement_score":0.91299564,"about_ca_system_score_codex":0.0006241861,"about_ca_system_score_gemma":0.00002308583,"threshold_uncertainty_score":0.99989104},"labels":[],"label_agreement":null},{"id":"W3006255536","doi":"10.1109/tste.2020.2973086","title":"Optimal Planning of Distributed Generators and Shunt Capacitors in Isolated Microgrids With Nonlinear Loads","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":39,"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":"Microgrid; Dispatchable generation; Capacitor; Nonlinear system; Total harmonic distortion; Engineering; Sizing; Voltage; Reliability engineering; AC power; Harmonics; Distributed generation; Power flow; Control theory (sociology); Computer science; Electric power system; Electronic engineering; Power (physics); Electrical engineering; Renewable energy","score_opus":0.00415790789333493,"score_gpt":0.17153057256316828,"score_spread":0.16737266466983336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006255536","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":[0.2758799,0.00044065833,0.72331613,0.000055590845,0.0000532517,0.000081740756,0.000035926143,0.00010743902,0.000029383635],"genre_scores_gemma":[0.99790233,0.00016278012,0.001741712,0.000043683467,0.000040080886,0.000023356708,0.000022253997,0.00003574456,0.00002803695],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916154,0.000019854027,0.00023913902,0.00019079653,0.00009335939,0.00029528813],"domain_scores_gemma":[0.9996658,0.000022197826,0.000031294167,0.0000971875,0.00007723211,0.000106317944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000039274782,0.00018399343,0.00023177815,0.00015666905,0.00006280736,0.00003003361,0.00006922983,0.000101051,0.000017636396],"category_scores_gemma":[0.0000020000873,0.00017794484,0.000035865443,0.0005548732,0.000042595333,0.00014805135,0.0000011860652,0.00017023653,4.2022887e-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":[0.00018472696,0.00003823396,0.00004761995,0.00007379589,0.00005868558,0.00004540252,0.00041248382,0.9932168,0.004670306,0.000016766557,0.000036619094,0.001198535],"study_design_scores_gemma":[0.0012291006,0.00029563575,0.00003592431,0.000033531996,0.000037499613,0.000008422868,0.0012408557,0.93457747,0.06007325,0.000002293094,0.002215856,0.00025019163],"about_ca_topic_score_codex":0.00016698775,"about_ca_topic_score_gemma":0.000023933067,"teacher_disagreement_score":0.7220225,"about_ca_system_score_codex":0.00006208036,"about_ca_system_score_gemma":0.00003972581,"threshold_uncertainty_score":0.725638},"labels":[],"label_agreement":null},{"id":"W3018718829","doi":"10.1109/tste.2020.2986586","title":"Operations &amp; Maintenance Optimization of Wind Turbines Integrating Wind and Aging Information","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":147,"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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Wind power; Offshore wind power; Turbine; Reliability engineering; Revenue; Optimal maintenance; Production (economics); Maintenance engineering; Reliability (semiconductor); Renewable energy; Engineering; Computer science; Marine engineering; Power (physics); Business","score_opus":0.005592530214258211,"score_gpt":0.18853014103600388,"score_spread":0.18293761082174567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3018718829","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":[0.008777704,0.000052047297,0.9890825,0.0004843883,0.00012197544,0.0001606626,0.000012929041,0.0001733529,0.0011344134],"genre_scores_gemma":[0.98478,0.00031084887,0.014118716,0.00021372242,0.000030484218,0.00001935736,0.000025291836,0.00002417719,0.0004773625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999095,0.000025566214,0.00036401677,0.00014830001,0.00013042128,0.00023667928],"domain_scores_gemma":[0.9993914,0.000041153773,0.00004437134,0.0001451934,0.00029097305,0.00008693751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009816306,0.00016769306,0.00018366543,0.00016037496,0.00017020281,0.00007966496,0.000082201215,0.00009239605,0.000051380266],"category_scores_gemma":[0.000047765276,0.00016742793,0.000048716858,0.00048946874,0.000057602734,0.00089578144,0.0000022155489,0.00015265761,0.000002166669],"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":[0.000018873327,0.000015251848,0.000002917768,0.00015890053,0.000020585008,7.1348177e-7,0.0011332227,0.99283886,0.00032836283,0.001526686,0.00010902741,0.0038466256],"study_design_scores_gemma":[0.00036622863,0.000057670208,0.0000055416817,0.000050659095,0.000021924803,0.0000037581258,0.002222154,0.98668337,0.005170361,0.000072764175,0.005168828,0.00017676248],"about_ca_topic_score_codex":0.0002255935,"about_ca_topic_score_gemma":0.000038724134,"teacher_disagreement_score":0.97600234,"about_ca_system_score_codex":0.000093125695,"about_ca_system_score_gemma":0.000044772434,"threshold_uncertainty_score":0.6827513},"labels":[],"label_agreement":null},{"id":"W3024952177","doi":"10.1109/tste.2020.2994174","title":"Resilience Assessment of Distribution Systems Integrated With Distributed Energy Resources","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":137,"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":"Resilience (materials science); Probabilistic logic; Reliability engineering; Context (archaeology); Computer science; Grid; Vulnerability (computing); Electric power system; Distributed generation; Renewable energy; Event (particle physics); Engineering; Power (physics); Computer security","score_opus":0.005025481678804128,"score_gpt":0.19789892488280017,"score_spread":0.19287344320399605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3024952177","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":[0.017168311,0.00012143337,0.980343,0.00011927379,0.00016443328,0.00012802928,0.000800944,0.00045298657,0.0007016062],"genre_scores_gemma":[0.9988814,0.00008234117,0.00014337602,0.000023051061,0.000035659195,0.00011087723,0.0003981667,0.000044025965,0.0002811284],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982504,0.00007786943,0.00042421944,0.0003449758,0.00040387426,0.0004986542],"domain_scores_gemma":[0.9989662,0.00006840523,0.00008996403,0.00030471073,0.0003563493,0.00021434338],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001012206,0.00030750164,0.00035636182,0.0001054219,0.00016138292,0.000076763834,0.0002346913,0.00014871715,0.000035992995],"category_scores_gemma":[0.000008461593,0.00028476925,0.000088629175,0.0012893487,0.000111434485,0.0002953435,0.0000027112562,0.00024378474,0.0000014943573],"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":[0.00013185471,0.00009716145,0.000014789614,0.00015313615,0.00009468631,0.00003775551,0.000046184472,0.9899127,0.0015894407,0.0058807647,0.0012690426,0.00077251875],"study_design_scores_gemma":[0.0010439036,0.0011250287,0.00014710044,0.00012710376,0.0001211556,0.00001640228,0.003395033,0.8484676,0.060800675,0.00003369326,0.084113315,0.0006090004],"about_ca_topic_score_codex":0.00087402685,"about_ca_topic_score_gemma":0.000033684883,"teacher_disagreement_score":0.98171306,"about_ca_system_score_codex":0.00058095204,"about_ca_system_score_gemma":0.00012332753,"threshold_uncertainty_score":0.9999604},"labels":[],"label_agreement":null},{"id":"W3030829271","doi":"10.1109/tste.2020.2998408","title":"A Fast Flexibility-Driven Generation Portfolio Planning Method for Sustainable Power Systems","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Power System Optimization","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Group for Research in Decision Analysis","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dispatchable generation; Variable renewable energy; Flexibility (engineering); Renewable energy; Portfolio; Computer science; Reliability engineering; Electric power system; Exploit; Electricity generation; Variable (mathematics); Mathematical optimization; Industrial engineering; Engineering; Power (physics); Distributed generation; Economics; Electrical engineering","score_opus":0.017486060836571962,"score_gpt":0.24935303497224895,"score_spread":0.23186697413567697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3030829271","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":[0.0006473424,0.0004445858,0.9919967,0.00010877265,0.00048911263,0.0008432061,0.00001648077,0.00086603896,0.004587766],"genre_scores_gemma":[0.98173004,0.000027170385,0.0054780534,0.00017836526,0.00017247125,0.0008175342,0.000038162645,0.00015174622,0.0114064645],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99755967,0.00011832689,0.00056734245,0.00054168515,0.00030420936,0.00090874464],"domain_scores_gemma":[0.9986215,0.00013126108,0.000095993,0.00037262432,0.00052139966,0.00025717798],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003462306,0.00037764886,0.00044198055,0.00039207394,0.00039725917,0.00023426051,0.00022705446,0.00024913944,0.000054649976],"category_scores_gemma":[0.000031361946,0.00042519273,0.00017161039,0.0010418509,0.000018983264,0.00062967994,0.0000027914873,0.00023602591,0.0000060893976],"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":[0.00006739722,0.000046401165,0.0000012593338,0.0004027818,0.0001297321,0.00006100195,0.0005842331,0.9843124,0.0015104173,0.006669428,0.005692908,0.000522049],"study_design_scores_gemma":[0.0007012772,0.00031549396,7.3574273e-7,0.000022486996,0.00006900526,0.000018230123,0.00378165,0.94047016,0.016957209,0.00006559911,0.03716839,0.00042978997],"about_ca_topic_score_codex":0.00027297612,"about_ca_topic_score_gemma":0.000006033661,"teacher_disagreement_score":0.9865186,"about_ca_system_score_codex":0.00073215086,"about_ca_system_score_gemma":0.00017961998,"threshold_uncertainty_score":0.99982},"labels":[],"label_agreement":null},{"id":"W3046998254","doi":"10.1109/tste.2020.3013697","title":"Impedance-Based Stability Analysis and Design of a Fractional-Order Active Damper for Grid-Connected Current-Source Inverters","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":40,"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":"Damper; Control theory (sociology); Photovoltaic system; Engineering; Harmonics; Robustness (evolution); Grid; Electrical impedance; Active filter; Voltage source; Output impedance; Computer science; Electronic engineering; Voltage; Control engineering; Electrical engineering","score_opus":0.01141054727764865,"score_gpt":0.2028268366338836,"score_spread":0.19141628935623495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046998254","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":[0.0038142966,0.00024090943,0.99516565,0.00013355816,0.00010673518,0.00029941942,0.00007888895,0.00014643466,0.00001410819],"genre_scores_gemma":[0.9969142,0.00017607302,0.002445715,0.00011318558,0.000040623996,0.00021349125,0.000033597884,0.000032636446,0.000030475521],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901164,0.00005977817,0.00025482487,0.00027893987,0.00012872409,0.0002661187],"domain_scores_gemma":[0.9990707,0.0002820335,0.000059717077,0.00015405967,0.00031889108,0.00011460535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008523366,0.0001947687,0.00031340276,0.00024702615,0.00012234016,0.00002700732,0.000077512654,0.00008568771,0.00010961694],"category_scores_gemma":[0.000025851945,0.00020366721,0.00015068556,0.0010371277,0.000045904224,0.00020674888,9.341525e-7,0.0001291034,4.227475e-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":[0.00042011656,0.00007043697,0.000009891955,0.00014501589,0.00043333267,5.5883066e-7,0.00027050564,0.9668636,0.0021358866,0.000024189803,0.00007110488,0.029555408],"study_design_scores_gemma":[0.0010561992,0.0001093249,0.000027959213,0.000006184803,0.0004324602,2.4502415e-7,0.00055307866,0.95041645,0.045092255,0.00003877371,0.0020769087,0.00019016521],"about_ca_topic_score_codex":0.00014672843,"about_ca_topic_score_gemma":0.00003341802,"teacher_disagreement_score":0.9930999,"about_ca_system_score_codex":0.00012379402,"about_ca_system_score_gemma":0.000094036615,"threshold_uncertainty_score":0.83053076},"labels":[],"label_agreement":null},{"id":"W3088725794","doi":"10.1109/tste.2020.3026370","title":"Addressing the Conditional and Correlated Wind Power Forecast Errors in Unit Commitment by Distributionally Robust Optimization","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Power System Optimization","field":"Engineering","cited_by":73,"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 Manitoba","funders":"National Science Foundation","keywords":"Mathematical optimization; Semidefinite programming; Robust optimization; Covariance matrix; Robustness (evolution); Power system simulation; Wind power; Stochastic programming; Estimator; Ambiguity; Covariance; Mathematics; Integer programming; Optimization problem; Computer science; Electric power system; Algorithm; Power (physics); Statistics; Engineering","score_opus":0.021030977848580493,"score_gpt":0.2130901661902146,"score_spread":0.1920591883416341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088725794","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":[0.0035137264,0.00026461462,0.9940854,0.00068026315,0.00013109563,0.0002378459,0.00008890731,0.00015663814,0.00084152474],"genre_scores_gemma":[0.99866486,0.000072997806,0.00027204104,0.00019322087,0.000014948834,0.000061094346,0.00022375985,0.000038890892,0.00045816068],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988668,0.000076743934,0.00029343012,0.00021626953,0.00021955966,0.00032721853],"domain_scores_gemma":[0.9995033,0.00010282092,0.00005045636,0.0001223551,0.00011615013,0.00010489807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011080935,0.00019735706,0.00016465408,0.00012478506,0.00026310218,0.000078945995,0.0001112712,0.00012621941,0.00014951457],"category_scores_gemma":[0.000010560869,0.00018698027,0.00003814142,0.0007621476,0.00005570698,0.00028583,0.0000021421688,0.00025239517,0.0000021562828],"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":[0.00003663236,0.000045219702,0.000017559501,0.000024708677,0.0000459966,0.000012088382,0.00018798538,0.9968686,0.00004937134,0.0007440296,0.0017693485,0.00019846886],"study_design_scores_gemma":[0.0008374776,0.00009168755,0.000046050143,0.0000300839,0.00002826706,0.000015240645,0.0008259065,0.99302185,0.0013656778,0.00004955485,0.0034603262,0.00022787589],"about_ca_topic_score_codex":0.000076377684,"about_ca_topic_score_gemma":0.000018650544,"teacher_disagreement_score":0.99515116,"about_ca_system_score_codex":0.00029960822,"about_ca_system_score_gemma":0.00006309776,"threshold_uncertainty_score":0.7624834},"labels":[],"label_agreement":null},{"id":"W3089255756","doi":"10.1109/tste.2020.3008836","title":"Erratum to “Mitigation of Subsynchronous Resonance Induced by a Type III Wind System” [Jul 20 1717-1727]","year":2020,"lang":"en","type":"erratum","venue":"IEEE Transactions on Sustainable Energy","topic":"Power Transformer Diagnostics and Insulation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Division of Electrical, Communications and Cyber Systems; Washington State University; Manitoba Hydro; Virginia Polytechnic Institute and State University; National Science Foundation","keywords":"Type (biology); Wind power; Electrical engineering; Resonance (particle physics); Engineering; Physics; Geology; Atomic physics","score_opus":0.006447119690000793,"score_gpt":0.20089447368726585,"score_spread":0.19444735399726507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3089255756","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":[0.0024244701,0.005770392,0.8479994,0.0005166516,0.04618952,0.001716404,0.0008868652,0.0013042589,0.093192056],"genre_scores_gemma":[0.9420593,0.0011037397,0.000092021925,0.00012345651,0.0004333373,0.00015112123,0.00047506084,0.00023631055,0.055325657],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973574,0.000052915446,0.00076028245,0.00056941266,0.00053978624,0.0007201555],"domain_scores_gemma":[0.99852073,0.00007341161,0.00013370956,0.0005211132,0.00044808091,0.00030295906],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000119624936,0.0006035002,0.00074745127,0.00051627646,0.00020504798,0.00008123157,0.00035413436,0.0008215889,0.000065093285],"category_scores_gemma":[0.0000140013,0.0007101426,0.00019681295,0.0013484432,0.00004107024,0.00028161766,0.0000029284636,0.00090149,0.000026693791],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002029677,0.00019230359,5.5837717e-7,0.0024536576,0.00036766214,0.000067938585,0.0008173983,0.1598874,0.005007944,0.0012955879,0.8233421,0.0063644927],"study_design_scores_gemma":[0.0010747564,0.0008748114,0.000024668838,0.0010746397,0.00029087684,0.00000873251,0.0010151276,0.024747105,0.030975845,0.00012167433,0.9385346,0.0012571579],"about_ca_topic_score_codex":0.00089289446,"about_ca_topic_score_gemma":0.00016851629,"teacher_disagreement_score":0.9396348,"about_ca_system_score_codex":0.00091238494,"about_ca_system_score_gemma":0.00045744822,"threshold_uncertainty_score":0.99953496},"labels":[],"label_agreement":null},{"id":"W3108888750","doi":"10.1109/tste.2020.3039758","title":"Stochastic Energy Management of Electric Bus Charging Stations With Renewable Energy Integration and B2G Capabilities","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":60,"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","keywords":"Stochastic programming; Mathematical optimization; Computer science; Photovoltaic system; Markov decision process; Regret; Dynamic programming; Renewable energy; Heuristic; Energy management; Wind power; Energy storage; Markov process; Robust optimization; Grid; Automotive engineering; Engineering; Energy (signal processing); Power (physics); Electrical engineering; Mathematics","score_opus":0.003841288515131854,"score_gpt":0.1699156145650683,"score_spread":0.16607432604993644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108888750","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":[0.00701938,0.0004506212,0.9905501,0.000090658286,0.000053843713,0.00007552839,0.00000994258,0.00018422763,0.0015657126],"genre_scores_gemma":[0.9966532,0.00045930312,0.00079269503,0.00010729014,0.00003538693,0.000108315355,0.0000107989035,0.000053425065,0.0017795629],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880207,0.000023403652,0.00027318634,0.00027333136,0.00021300958,0.00041501707],"domain_scores_gemma":[0.9994523,0.000053528966,0.000052507658,0.0001779841,0.0001357867,0.00012788881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004077625,0.00024964075,0.0002481601,0.00027099377,0.00017657802,0.000045594013,0.000108497945,0.00008603007,0.000054368717],"category_scores_gemma":[0.0000018315624,0.00023493372,0.000050685983,0.0009336841,0.000041479776,0.00025281345,0.0000019974445,0.00013198635,2.8586618e-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":[0.00006487149,0.000029150457,5.791506e-7,0.00016584937,0.00014691203,0.000014078592,0.00037981014,0.95502377,0.0024135278,0.022631874,0.00023729174,0.018892296],"study_design_scores_gemma":[0.0013954754,0.0010638838,0.000029463476,0.00012464334,0.00025264578,0.000031383635,0.007351927,0.7328113,0.2449138,0.0051725633,0.0060867174,0.0007662058],"about_ca_topic_score_codex":0.0022444546,"about_ca_topic_score_gemma":0.00022813641,"teacher_disagreement_score":0.9897574,"about_ca_system_score_codex":0.00017068125,"about_ca_system_score_gemma":0.00005389528,"threshold_uncertainty_score":0.9580319},"labels":[],"label_agreement":null},{"id":"W3118240248","doi":"10.1109/tste.2021.3050783","title":"Robust Hamiltonian Energy Control Based on Lyapunov Function for Four-Phase Parallel Fuel Cell Boost Converter for DC Microgrid Applications","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"King Mongkut's University of Technology North Bangkok; Université de Lorraine","keywords":"Microgrid; Converters; Boost converter; Control theory (sociology); Engineering; Computer science; Voltage; Electrical engineering","score_opus":0.007944515596127542,"score_gpt":0.1880217189233847,"score_spread":0.18007720332725716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118240248","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":[0.000025929172,0.001031892,0.99574804,0.00035968202,0.0005345444,0.0007986935,0.00033423226,0.00036584074,0.00080115104],"genre_scores_gemma":[0.96987146,0.0006587943,0.008154447,0.0022395516,0.00040286692,0.007870921,0.0005498676,0.0002289801,0.010023115],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980252,0.00004884137,0.0004540407,0.0005592355,0.00017680516,0.00073587766],"domain_scores_gemma":[0.9983735,0.0002851959,0.000084610685,0.0005154559,0.000551971,0.00018924812],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012632666,0.00041935826,0.00039997336,0.00031657604,0.00045263208,0.00013521886,0.00016511435,0.0002653471,0.00014200345],"category_scores_gemma":[0.000005170267,0.00046765097,0.00038064778,0.0004049492,0.000049120048,0.00020880083,0.0000012620748,0.00015858788,0.000006533563],"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":[0.00077131385,0.0005275247,3.4205533e-7,0.00029506366,0.00014146444,0.000009419754,0.000022323276,0.9660374,0.00402965,0.0011927615,0.0022929946,0.024679776],"study_design_scores_gemma":[0.0075806878,0.00032469525,8.888404e-7,0.000013594633,0.00019833165,0.0000038714784,0.00017538572,0.6418018,0.016469806,0.00025827487,0.3328039,0.00036877897],"about_ca_topic_score_codex":0.00007639921,"about_ca_topic_score_gemma":0.00014702744,"teacher_disagreement_score":0.9875936,"about_ca_system_score_codex":0.00030994113,"about_ca_system_score_gemma":0.00020344788,"threshold_uncertainty_score":0.9997775},"labels":[],"label_agreement":null},{"id":"W3119772170","doi":"10.1109/tste.2021.3049762","title":"Adjustable Wind Farm Frequency Support Through Multi-Terminal HVDC Grids","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":65,"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":"Power Systems Engineering Research Center","keywords":"Wind power; Turbine; Offshore wind power; Automatic frequency control; Computer science; Grid; Frequency grid; Electrical engineering; Marine engineering; Engineering; Telecommunications; Voltage; Aerospace engineering; Mathematics","score_opus":0.012384652488050084,"score_gpt":0.2283118294708969,"score_spread":0.2159271769828468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119772170","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":[0.009650686,0.00047234926,0.9709534,0.00003932399,0.0015975714,0.00020827139,0.000033743334,0.00059097836,0.0164537],"genre_scores_gemma":[0.936846,0.00026146177,0.0014845838,0.00009507504,0.00019628268,0.00017831638,0.000017896486,0.000098566656,0.06082178],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980539,0.000060783143,0.00042370407,0.00042419674,0.00027628234,0.00076110003],"domain_scores_gemma":[0.99903315,0.000032730706,0.00004339002,0.00048091213,0.00026503435,0.0001448078],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013413922,0.00033520258,0.0003310057,0.00017229583,0.0003664802,0.00011105597,0.0001517683,0.0002698223,0.00071187224],"category_scores_gemma":[0.000006094649,0.00036824317,0.00018715886,0.00069441594,0.00004262622,0.00048842793,0.0000023345863,0.00037513595,0.000054613098],"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":[0.0000690311,0.0008005025,0.000021905229,0.0011224215,0.0004670061,0.003267697,0.0015372196,0.88811916,0.03618147,0.0065943426,0.0015224947,0.06029673],"study_design_scores_gemma":[0.0028818832,0.00044691865,0.000092088776,0.00013800093,0.00018063189,0.00091122993,0.008845578,0.021844802,0.47189534,0.00095625635,0.49025008,0.0015571803],"about_ca_topic_score_codex":0.0020923496,"about_ca_topic_score_gemma":0.0005047544,"teacher_disagreement_score":0.9694688,"about_ca_system_score_codex":0.00046653443,"about_ca_system_score_gemma":0.00020200772,"threshold_uncertainty_score":0.999877},"labels":[],"label_agreement":null},{"id":"W3127460143","doi":"10.1109/tste.2021.3057854","title":"Weighted Dynamic Aggregation Modeling of Induction Machine-Based Wind Farms","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":57,"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":"Wind speed; Wind power; Induction generator; Control theory (sociology); Turbine; Transient (computer programming); Computer science; Scale (ratio); Environmental science; Engineering; Meteorology; Physics","score_opus":0.005593204040732793,"score_gpt":0.1911531114658698,"score_spread":0.185559907425137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127460143","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":[0.09811286,0.0005038151,0.89920443,0.00007858876,0.0006520312,0.00011827224,0.000015200169,0.00027363418,0.0010411863],"genre_scores_gemma":[0.9973429,0.00004307434,0.0003180769,0.000023779252,0.000050519393,0.000045761815,0.000029412633,0.0000677843,0.0020787236],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866164,0.00006650704,0.00040045913,0.0002594712,0.0002586739,0.00035324076],"domain_scores_gemma":[0.99913645,0.000046520465,0.000055363274,0.0003620525,0.000319953,0.00007963865],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000110991736,0.0002266833,0.00028337247,0.00037628578,0.00012591862,0.00003639428,0.00010285807,0.00017660126,0.00007174362],"category_scores_gemma":[0.0000057678103,0.0002487784,0.00014687762,0.0007113109,0.000020096339,0.0002429685,9.02155e-7,0.00022436566,0.000004134502],"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":[0.000032094173,0.00007802589,0.0000032337548,0.00015117064,0.00008454074,0.000030041287,0.00006401331,0.9838437,0.008242858,0.00026139023,0.000010652603,0.00719829],"study_design_scores_gemma":[0.00084718515,0.000041178024,0.0000065636987,0.000054052438,0.000049545808,0.000012869312,0.00041140927,0.91156936,0.085813135,0.00030845043,0.0006727862,0.00021348677],"about_ca_topic_score_codex":0.0004238371,"about_ca_topic_score_gemma":0.00016308961,"teacher_disagreement_score":0.89923,"about_ca_system_score_codex":0.00039298568,"about_ca_system_score_gemma":0.00013811108,"threshold_uncertainty_score":0.9999964},"labels":[],"label_agreement":null},{"id":"W3132599260","doi":"10.1109/tste.2020.3039910","title":"A Stochastic Program for Siting and Sizing Fast Charging Stations and Small Wind Turbines in Urban Areas","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; Energy Research and Development Administration","keywords":"Wind power; Engineering; Turbine; Sizing; Downtown; Transport engineering; Geography; Electrical engineering","score_opus":0.009651232812068755,"score_gpt":0.22348370425993766,"score_spread":0.2138324714478689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132599260","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":[0.2831526,0.0007969247,0.7147687,0.00015325706,0.000104383435,0.0002741615,0.000014214323,0.00021152572,0.0005242076],"genre_scores_gemma":[0.99453604,0.00010079709,0.0028650914,0.000026666377,0.000041835796,0.00034345323,0.000014497301,0.00003893809,0.0020326856],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890685,0.00002004549,0.00018698558,0.0002491892,0.00010398624,0.00053296087],"domain_scores_gemma":[0.99947006,0.00015166677,0.00001480512,0.000101100806,0.000119223754,0.00014316714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010978663,0.00016479431,0.00016963897,0.00027425788,0.00023507392,0.00012767117,0.000042736592,0.00006412279,0.000009698557],"category_scores_gemma":[0.000020156094,0.00018253349,0.00003245652,0.0003738282,0.00003117422,0.00016070149,0.000003032525,0.00014015855,2.9103583e-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":[0.000042811054,0.00011791665,0.000033033757,0.00037091674,0.00008417243,0.00011455782,0.00135996,0.893396,0.0010236576,0.0014057974,0.00003499338,0.102016166],"study_design_scores_gemma":[0.005757712,0.0005179415,0.0017041559,0.0006355478,0.000105492894,0.00018841018,0.037293114,0.8850719,0.04332339,0.0027519169,0.020895358,0.0017551045],"about_ca_topic_score_codex":0.00016010243,"about_ca_topic_score_gemma":0.00041842798,"teacher_disagreement_score":0.71190363,"about_ca_system_score_codex":0.0001363524,"about_ca_system_score_gemma":0.00011232184,"threshold_uncertainty_score":0.74434996},"labels":[],"label_agreement":null},{"id":"W3138812026","doi":"10.1109/tste.2020.3024202","title":"A New Bi-Objective Approach for Optimal Sizing of Electrical and Thermal Devices in Zero Energy Buildings Considering Environmental Impacts","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":27,"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 British Columbia","funders":"","keywords":"Sizing; Thermal; Zero-energy building; Energy (signal processing); Zero (linguistics); Electric potential energy; Environmental science; Computer science; Automotive engineering; Electrical engineering; Engineering; Energy conservation; Physics; Meteorology","score_opus":0.006550955530450619,"score_gpt":0.18435309613178777,"score_spread":0.17780214060133714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138812026","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":[0.08720443,0.00047935016,0.9118912,0.000026033855,0.00003308114,0.000090262656,0.000004835813,0.000097111915,0.00017366625],"genre_scores_gemma":[0.98304546,0.0001736072,0.016442642,0.000091705784,0.000034276636,0.0000616679,0.00000599649,0.000050092673,0.000094529045],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99897856,0.000020868747,0.00024507736,0.00026121686,0.0001160553,0.0003782229],"domain_scores_gemma":[0.99961936,0.00008975584,0.00004413615,0.00009246355,0.000016570186,0.00013772913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056855955,0.00020864127,0.0002528086,0.0002060012,0.00009443272,0.00003133216,0.0000906482,0.00013359557,0.000011824532],"category_scores_gemma":[0.0000047532003,0.00022827432,0.00007208928,0.00033704514,0.000031475636,0.0002679061,0.0000033416331,0.00013766286,4.6557865e-8],"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":[0.00014121686,0.000045584453,0.00001628551,0.000062430874,0.00006779555,0.000005244697,0.000361697,0.9757053,0.01059284,0.0018878484,0.000021483314,0.011092223],"study_design_scores_gemma":[0.00097577047,0.00023806989,0.00002265245,0.000017172526,0.000039000068,0.000009140132,0.0006526136,0.8108465,0.18599294,0.0001023729,0.00082042016,0.00028332093],"about_ca_topic_score_codex":0.00038767452,"about_ca_topic_score_gemma":0.000014400233,"teacher_disagreement_score":0.89584106,"about_ca_system_score_codex":0.00014094335,"about_ca_system_score_gemma":0.000055353867,"threshold_uncertainty_score":0.93087566},"labels":[],"label_agreement":null},{"id":"W3170635306","doi":"10.1109/tste.2021.3087018","title":"A Multilevel Modeling Approach Towards Wind Farm Aggregated Power Curve","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Manitoba Hydro; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Manitoba Hydro; University of Manitoba","keywords":"Wind power; Cluster analysis; Wind power forecasting; Turbine; Power (physics); Hierarchical clustering; Set (abstract data type); Computer science; Mathematics; Algorithm; Mathematical optimization; Electric power system; Statistics; Engineering; Electrical engineering; Aerospace engineering","score_opus":0.014421495084025886,"score_gpt":0.21038555539247125,"score_spread":0.19596406030844538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170635306","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":[0.027938299,0.00056361296,0.9329383,0.00002304345,0.00065596914,0.000068489615,0.00002052047,0.0005875671,0.037204217],"genre_scores_gemma":[0.9842544,0.00016293032,0.001996246,0.00009030737,0.000073316965,0.00005061512,0.00002613116,0.000116656454,0.013229365],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99809843,0.00005079893,0.00035799382,0.0004285754,0.00028439416,0.0007798037],"domain_scores_gemma":[0.9990534,0.000042434214,0.000031226893,0.0004133087,0.0002710812,0.00018851717],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012704662,0.00036838948,0.00031850406,0.00026289816,0.0002910943,0.00011031494,0.00018105176,0.00023474342,0.00018682284],"category_scores_gemma":[0.00001053751,0.00039821808,0.00020250714,0.00066980364,0.000032468255,0.0002388921,0.000003832005,0.0003992297,0.0000075636917],"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":[0.00002000602,0.00013450696,5.35077e-7,0.00007871616,0.00012809252,0.0001483638,0.00045594637,0.9772034,0.0009178161,0.0014516565,0.00005175733,0.019409196],"study_design_scores_gemma":[0.00065001263,0.000039164268,0.0000015228741,0.00005461745,0.0000394801,0.00006574073,0.001934081,0.9375409,0.04901683,0.00024861484,0.009911721,0.0004973458],"about_ca_topic_score_codex":0.0005127944,"about_ca_topic_score_gemma":0.000062253705,"teacher_disagreement_score":0.9563161,"about_ca_system_score_codex":0.00026343993,"about_ca_system_score_gemma":0.00016296598,"threshold_uncertainty_score":0.999847},"labels":[],"label_agreement":null},{"id":"W3190975923","doi":"10.1109/tste.2021.3102515","title":"Maximum Asymmetrical Support in Parallel-Operated Grid-Interactive Smart Inverters","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":18,"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":"Grid; Interconnection; Computer science; Voltage; Smart grid; Boosting (machine learning); Grid code; AC power; Sequence (biology); Electronic engineering; Distributed computing; Electrical engineering; Engineering; Telecommunications; Mathematics; Artificial intelligence","score_opus":0.004624548814032196,"score_gpt":0.18855110774456643,"score_spread":0.18392655893053422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190975923","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":[0.0022604284,0.00027112218,0.98882896,0.00023809422,0.00088188535,0.00012750045,0.000015469323,0.00028759596,0.0070889336],"genre_scores_gemma":[0.9931636,0.0006296953,0.0004727902,0.00037625065,0.000049018687,0.000112684866,0.00004298745,0.00005225599,0.0051007024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986632,0.000064421496,0.00030694783,0.00029697502,0.0001586971,0.0005097938],"domain_scores_gemma":[0.99939865,0.00006925302,0.000021792277,0.00022825142,0.00016222283,0.000119849465],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008068272,0.00022489275,0.00026421112,0.00044956143,0.000094053794,0.00008168856,0.000107837695,0.00014664244,0.0005474042],"category_scores_gemma":[0.000009039515,0.00024756577,0.00010894261,0.0011771033,0.000022019605,0.00029182044,0.0000019183396,0.0002902482,0.000029654453],"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":[0.00008443428,0.00016180762,0.000013247193,0.000030408613,0.000085558975,0.00046025583,0.00014190757,0.9746457,0.0003808721,0.00017563801,0.0015604008,0.022259818],"study_design_scores_gemma":[0.0038757746,0.00021961813,0.00015255928,0.00004236227,0.000080397345,0.00009852947,0.0027040641,0.81854606,0.0625096,0.00037880294,0.11049184,0.0009004088],"about_ca_topic_score_codex":0.000420601,"about_ca_topic_score_gemma":0.00034272452,"teacher_disagreement_score":0.9909032,"about_ca_system_score_codex":0.0004278445,"about_ca_system_score_gemma":0.00012960062,"threshold_uncertainty_score":0.9999977},"labels":[],"label_agreement":null},{"id":"W3198115497","doi":"10.1109/tste.2021.3109482","title":"Blockchain-Based Privacy Preserving and Energy Saving Mechanism for Electricity Prosumers","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Prosumer; Computer science; Validator; Renewable energy; Blockchain; Electricity; Scalability; Distributed computing; Computer security; Engineering; Database; Electrical engineering","score_opus":0.00820685194843426,"score_gpt":0.2186429071821869,"score_spread":0.21043605523375264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3198115497","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":[0.010008536,0.00019473731,0.98643416,0.0024391597,0.00010747823,0.00015535261,0.000005525207,0.00041148372,0.00024356783],"genre_scores_gemma":[0.9726434,0.000044533426,0.02123449,0.0008367993,0.000023805245,0.0007909073,0.0000024140666,0.000027696586,0.0043959944],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99803317,0.00007408574,0.0002756797,0.00075278524,0.00020723992,0.00065703667],"domain_scores_gemma":[0.99813235,0.0002572764,0.00009488541,0.00086417067,0.00052190013,0.00012943787],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022019,0.00024268925,0.00024938586,0.00033366552,0.0008545188,0.0001416619,0.00059425127,0.00023981913,0.000012017765],"category_scores_gemma":[0.000031584557,0.0002687457,0.00012005817,0.001106028,0.000062776344,0.00010582647,0.000020366344,0.0002097878,4.4942593e-7],"study_design_candidate":"theoretical_or_conceptual","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":[0.000022125576,0.0003261182,0.0000019778902,0.000072764036,0.000054030672,0.000033170854,0.00012824801,0.008758073,0.0044385013,0.9444889,0.00011032239,0.041565802],"study_design_scores_gemma":[0.0007318881,0.00016606394,0.0000039882852,0.00001652492,0.00003095514,0.000022571903,0.00021648544,0.42747983,0.45123628,0.105599634,0.014139852,0.00035591412],"about_ca_topic_score_codex":0.0003719954,"about_ca_topic_score_gemma":0.00015176891,"teacher_disagreement_score":0.96519965,"about_ca_system_score_codex":0.0001644012,"about_ca_system_score_gemma":0.00036541186,"threshold_uncertainty_score":0.99997646},"labels":[],"label_agreement":null},{"id":"W3200781978","doi":"10.1109/tste.2021.3094093","title":"Maximum Power Tracking for a Wind Energy Conversion System Using Cascade-Forward Neural Networks","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Control theory (sociology); Cascade; Wind power; Controller (irrigation); Artificial neural network; Power (physics); Computer science; Power optimizer; Maximum power point tracking; Engineering; Electricity generation; Control engineering; Power control; Voltage; Control (management); Artificial intelligence; Electrical engineering","score_opus":0.008091913006225174,"score_gpt":0.1994808234553309,"score_spread":0.19138891044910575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200781978","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":[0.018764207,0.0009811119,0.97580105,0.000049191192,0.0027915072,0.00021635188,0.000021789705,0.0005324007,0.000842403],"genre_scores_gemma":[0.9962652,0.000022968155,0.00016714937,0.00009246023,0.00033935928,0.00009251014,0.000013673405,0.00016254517,0.0028441811],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99759007,0.00010905704,0.00054207555,0.00048028128,0.00028896172,0.0009895712],"domain_scores_gemma":[0.99864817,0.00019435372,0.00008705593,0.00046473878,0.00038345775,0.00022225006],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019409673,0.00042501622,0.0005696356,0.00030391605,0.00042030562,0.00017496939,0.00019324754,0.00034338093,0.00004788795],"category_scores_gemma":[0.0000072954763,0.00047065018,0.00038367222,0.00061083684,0.00003165856,0.00042107212,0.0000035105893,0.00026626795,0.0000018298139],"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":[0.000077979865,0.000042519274,0.0000023205325,0.0002992331,0.00020395112,0.00032424694,0.00008600436,0.9931991,0.0020599288,0.001221512,0.0002766854,0.0022064792],"study_design_scores_gemma":[0.0015119908,0.00008638963,0.000004133084,0.00010674718,0.00014211755,0.0002550288,0.0027551232,0.946199,0.030033004,0.000037718484,0.018360123,0.0005086453],"about_ca_topic_score_codex":0.0006309095,"about_ca_topic_score_gemma":0.000064080334,"teacher_disagreement_score":0.977501,"about_ca_system_score_codex":0.000950855,"about_ca_system_score_gemma":0.00011056397,"threshold_uncertainty_score":0.9997745},"labels":[],"label_agreement":null},{"id":"W4200432262","doi":"10.1109/tste.2021.3131897","title":"IEEE industry applications society","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":13,"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 New Brunswick","funders":"","keywords":"Computer science; Engineering; Electrical engineering","score_opus":0.009481953432038993,"score_gpt":0.22641946734151028,"score_spread":0.21693751390947127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200432262","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":[0.00030893538,0.00009386192,0.99427056,0.0015884412,0.0004131303,0.00004637924,0.0000020554273,0.00015212338,0.0031244939],"genre_scores_gemma":[0.93226576,0.00011078497,0.025839861,0.00088378583,0.00015534909,0.00024803964,0.0000033448575,0.000022328051,0.04047074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99895936,0.000016551176,0.00015392619,0.00032481467,0.00020156385,0.00034376222],"domain_scores_gemma":[0.9989945,0.000077630095,0.000027766659,0.0005000476,0.00026907772,0.00013094276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008126208,0.00012637669,0.00010309278,0.00007639302,0.00032913458,0.0001366775,0.0003192127,0.00015405797,0.00005305399],"category_scores_gemma":[0.0000022319064,0.0001442775,0.00012222571,0.00087448466,0.000022299493,0.00028712876,0.0000037269895,0.00030976706,0.0000145937975],"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":[8.45503e-7,0.00022914149,0.0000013969346,0.000030497435,0.00004781922,0.00001788791,0.00016205657,0.7016164,0.00075947936,0.28515112,0.0020059226,0.009977445],"study_design_scores_gemma":[0.00064912386,0.00007798329,0.00007057477,0.00003811178,0.000049560695,0.000116144955,0.0032701013,0.18725945,0.17112458,0.017050477,0.6193244,0.00096950476],"about_ca_topic_score_codex":0.00006377299,"about_ca_topic_score_gemma":0.0000063184984,"teacher_disagreement_score":0.9684307,"about_ca_system_score_codex":0.00018066369,"about_ca_system_score_gemma":0.0004378276,"threshold_uncertainty_score":0.58834654},"labels":[],"label_agreement":null},{"id":"W4205425523","doi":"10.1109/tste.2021.3070264","title":"IEEE industry applications society","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Engineering; Systems engineering","score_opus":0.009481953432038993,"score_gpt":0.22641946734151028,"score_spread":0.21693751390947127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205425523","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":[0.00030893538,0.00009386192,0.99427056,0.0015884412,0.0004131303,0.00004637924,0.0000020554273,0.00015212338,0.0031244939],"genre_scores_gemma":[0.93226576,0.00011078497,0.025839861,0.00088378583,0.00015534909,0.00024803964,0.0000033448575,0.000022328051,0.04047074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99895936,0.000016551176,0.00015392619,0.00032481467,0.00020156385,0.00034376222],"domain_scores_gemma":[0.9989945,0.000077630095,0.000027766659,0.0005000476,0.00026907772,0.00013094276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008126208,0.00012637669,0.00010309278,0.00007639302,0.00032913458,0.0001366775,0.0003192127,0.00015405797,0.00005305399],"category_scores_gemma":[0.0000022319064,0.0001442775,0.00012222571,0.00087448466,0.000022299493,0.00028712876,0.0000037269895,0.00030976706,0.0000145937975],"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":[8.45503e-7,0.00022914149,0.0000013969346,0.000030497435,0.00004781922,0.00001788791,0.00016205657,0.7016164,0.00075947936,0.28515112,0.0020059226,0.009977445],"study_design_scores_gemma":[0.00064912386,0.00007798329,0.00007057477,0.00003811178,0.000049560695,0.000116144955,0.0032701013,0.18725945,0.17112458,0.017050477,0.6193244,0.00096950476],"about_ca_topic_score_codex":0.00006377299,"about_ca_topic_score_gemma":0.0000063184984,"teacher_disagreement_score":0.9684307,"about_ca_system_score_codex":0.00018066369,"about_ca_system_score_gemma":0.0004378276,"threshold_uncertainty_score":0.58834654},"labels":[],"label_agreement":null},{"id":"W4205774840","doi":"10.1109/tste.2021.3107965","title":"IEEE Industry Applications Society","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science","score_opus":0.009481953432038993,"score_gpt":0.22641946734151028,"score_spread":0.21693751390947127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205774840","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":[0.00030893538,0.00009386192,0.99427056,0.0015884412,0.0004131303,0.00004637924,0.0000020554273,0.00015212338,0.0031244939],"genre_scores_gemma":[0.93226576,0.00011078497,0.025839861,0.00088378583,0.00015534909,0.00024803964,0.0000033448575,0.000022328051,0.04047074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99895936,0.000016551176,0.00015392619,0.00032481467,0.00020156385,0.00034376222],"domain_scores_gemma":[0.9989945,0.000077630095,0.000027766659,0.0005000476,0.00026907772,0.00013094276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008126208,0.00012637669,0.00010309278,0.00007639302,0.00032913458,0.0001366775,0.0003192127,0.00015405797,0.00005305399],"category_scores_gemma":[0.0000022319064,0.0001442775,0.00012222571,0.00087448466,0.000022299493,0.00028712876,0.0000037269895,0.00030976706,0.0000145937975],"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":[8.45503e-7,0.00022914149,0.0000013969346,0.000030497435,0.00004781922,0.00001788791,0.00016205657,0.7016164,0.00075947936,0.28515112,0.0020059226,0.009977445],"study_design_scores_gemma":[0.00064912386,0.00007798329,0.00007057477,0.00003811178,0.000049560695,0.000116144955,0.0032701013,0.18725945,0.17112458,0.017050477,0.6193244,0.00096950476],"about_ca_topic_score_codex":0.00006377299,"about_ca_topic_score_gemma":0.0000063184984,"teacher_disagreement_score":0.9684307,"about_ca_system_score_codex":0.00018066369,"about_ca_system_score_gemma":0.0004378276,"threshold_uncertainty_score":0.58834654},"labels":[],"label_agreement":null},{"id":"W4214548959","doi":"10.1109/tste.2019.2925442","title":"IEEE Transactions on Sustainable Energy","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Energy Efficiency and Management","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Energy (signal processing); Computer science","score_opus":0.006517135357169525,"score_gpt":0.21128135264221115,"score_spread":0.20476421728504163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214548959","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":[0.005820587,0.00014011902,0.8276546,0.00048448786,0.0019589076,0.00036801078,0.000015378062,0.00079352973,0.16276439],"genre_scores_gemma":[0.5938657,0.00024326301,0.00009079609,0.0012277849,0.00009520075,0.00040966138,0.000010012467,0.00013996332,0.4039176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941,0.00025458614,0.00083161856,0.0014347903,0.0010018718,0.002377149],"domain_scores_gemma":[0.99686235,0.00032779746,0.0002163436,0.0016545847,0.0004828434,0.00045610522],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00046124717,0.0009276158,0.0007569114,0.0014098014,0.0012497654,0.00024741358,0.00083550246,0.0005195176,0.003921443],"category_scores_gemma":[0.000008009914,0.0009503231,0.0006426812,0.0019966858,0.00018242263,0.00084840297,0.000004427699,0.0006454624,0.00035876385],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037431385,0.0010877325,3.6062846e-7,0.00013161609,0.00022830773,0.00024508222,0.00018373314,0.7140919,0.0005686691,0.2603495,0.0013963006,0.021342447],"study_design_scores_gemma":[0.0027065398,0.0014612013,0.0000044149083,0.00008157747,0.00022143377,0.000029909323,0.00810233,0.012761732,0.1790454,0.005502572,0.7885532,0.0015296947],"about_ca_topic_score_codex":0.019836225,"about_ca_topic_score_gemma":0.0013445849,"teacher_disagreement_score":0.8275638,"about_ca_system_score_codex":0.0012230246,"about_ca_system_score_gemma":0.00037422124,"threshold_uncertainty_score":0.99929476},"labels":[],"label_agreement":null},{"id":"W4220903767","doi":"10.1109/tste.2022.3161891","title":"Optimal Energy Management of Hydrogen Energy Facility Using Integrated Battery Energy Storage and Solar Photovoltaic Systems","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":431,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Photovoltaic system; Energy storage; Energy management; Hydrogen storage; Solar energy; Battery (electricity); Environmental science; Energy (signal processing); Automotive engineering; Battery storage; Electrical engineering; Computer science; Hydrogen; Engineering; Power (physics); Physics","score_opus":0.011527890033369032,"score_gpt":0.20863590060918483,"score_spread":0.19710801057581578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220903767","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":[0.1322088,0.0025756264,0.8588428,0.000028761242,0.0018653767,0.00025240352,0.0003914086,0.0005189661,0.0033158776],"genre_scores_gemma":[0.94915336,0.00051662966,0.0002692126,0.00017023356,0.00011588756,0.0010365068,0.00018073372,0.0002158877,0.04834152],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99228287,0.0013141353,0.0016234376,0.0016410942,0.0014051285,0.0017333402],"domain_scores_gemma":[0.99664754,0.0002075599,0.0006286598,0.0015702845,0.00042427832,0.0005217],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00076849747,0.0010992092,0.00137548,0.001495185,0.0014693241,0.00017685561,0.00090054044,0.00035262018,0.0006321857],"category_scores_gemma":[0.0000061439605,0.0012081977,0.00049922697,0.0021868942,0.00031810155,0.0005636361,0.00009832042,0.00045235257,0.0000023521866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047754485,0.000656816,0.000005813013,0.0003044775,0.0011592483,0.0009450663,0.00015987417,0.95793164,0.012253816,0.019507803,0.00039115312,0.006206737],"study_design_scores_gemma":[0.002574591,0.00067743444,0.0000029449716,0.00014819119,0.00045573906,0.00049423584,0.013288873,0.36753732,0.17390223,0.00030040328,0.43889746,0.0017205712],"about_ca_topic_score_codex":0.24708389,"about_ca_topic_score_gemma":0.0018488973,"teacher_disagreement_score":0.85857356,"about_ca_system_score_codex":0.0021725278,"about_ca_system_score_gemma":0.00047852413,"threshold_uncertainty_score":0.9998306},"labels":[],"label_agreement":null},{"id":"W4221062476","doi":"10.1109/tste.2022.3161897","title":"Fairness and Utilitarianism in Allocating Energy to EVs During Power Contingencies Using Modified Division Rules","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":29,"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","keywords":"Utilitarianism; Ranking (information retrieval); Division (mathematics); Energy (signal processing); Computer science; Task (project management); Mathematical optimization; Operations research; Index (typography); Power (physics); Engineering; Artificial intelligence; Mathematics; Statistics; Arithmetic","score_opus":0.005414175679749349,"score_gpt":0.18992860915985701,"score_spread":0.18451443348010765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221062476","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":[0.69461143,0.0002886989,0.3042931,0.000028558941,0.00015829821,0.000070069415,0.000007124524,0.00011762676,0.00042505833],"genre_scores_gemma":[0.99872756,0.00003664945,0.0003515066,0.00006952675,0.00001890786,0.00008428776,0.0000022319869,0.0000527393,0.00065661065],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985837,0.00005173885,0.00028173663,0.000300554,0.00022479623,0.0005574961],"domain_scores_gemma":[0.9995708,0.000048519738,0.000028805316,0.00019956923,0.000052916803,0.0000994275],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013840434,0.0002207006,0.00022530282,0.0004599293,0.00056105544,0.000059361522,0.00014947969,0.00007799173,0.00009414367],"category_scores_gemma":[0.0000048988463,0.00025288662,0.00005302744,0.0006145882,0.000020268242,0.00021500472,0.000011856918,0.00026785024,2.7923562e-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":[0.00004127874,0.00002898139,0.000014764231,0.000040035266,0.000024351657,0.000041572384,0.0007600092,0.9731201,0.016274469,0.003560558,0.00001461257,0.0060792817],"study_design_scores_gemma":[0.0019724206,0.00041850278,0.0019816498,0.000092142815,0.0000476577,0.000104844636,0.023365213,0.8371584,0.12356579,0.0041746115,0.005737108,0.0013816784],"about_ca_topic_score_codex":0.002096396,"about_ca_topic_score_gemma":0.00013592825,"teacher_disagreement_score":0.30411607,"about_ca_system_score_codex":0.00041473637,"about_ca_system_score_gemma":0.000045885598,"threshold_uncertainty_score":0.9999923},"labels":[],"label_agreement":null},{"id":"W4221074820","doi":"10.1109/tste.2022.3156412","title":"IEEE Industry Applications Society","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Engineering; Electrical engineering","score_opus":0.00890662127832284,"score_gpt":0.218807547898724,"score_spread":0.20990092662040116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221074820","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":[0.0003972776,0.00004850513,0.99550056,0.0013159733,0.0004957033,0.00008549584,0.000004663912,0.00018016867,0.001971664],"genre_scores_gemma":[0.9672672,0.000021111657,0.0068063447,0.00074080157,0.00008486325,0.00090984843,0.0000026667467,0.000019594669,0.024147559],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988899,0.000023992576,0.00014971808,0.00029848516,0.00028969935,0.00034819124],"domain_scores_gemma":[0.9992568,0.000067941444,0.000036069396,0.00044058546,0.00009192212,0.00010670334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014532018,0.000119819604,0.00009102166,0.00013321062,0.00090287044,0.000080426566,0.0005523785,0.00007050322,0.00011536548],"category_scores_gemma":[8.43484e-7,0.00014303095,0.00011232371,0.00092927826,0.000020320644,0.0002266685,0.000008186472,0.00046531358,0.000006502019],"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":[0.0000011590771,0.00015051637,7.03021e-7,0.000009101932,0.000021021639,0.0000036912404,0.00016118605,0.8473621,0.00012550275,0.14584564,0.0021096622,0.0042097257],"study_design_scores_gemma":[0.00039679618,0.00014063259,0.000022686218,0.000004790834,0.000022223112,0.000051672563,0.0036886488,0.23998414,0.0073383367,0.008941575,0.7388434,0.00056511274],"about_ca_topic_score_codex":0.00014163765,"about_ca_topic_score_gemma":0.000002186035,"teacher_disagreement_score":0.9886942,"about_ca_system_score_codex":0.00037384802,"about_ca_system_score_gemma":0.00027738378,"threshold_uncertainty_score":0.6944241},"labels":[],"label_agreement":null},{"id":"W4230110808","doi":"10.1109/tste.2017.2751243","title":"IEEE Transactions on Sustainable Energy","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Energy Efficiency and Management","field":"Energy","cited_by":11,"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 New Brunswick","funders":"","keywords":"Sustainable energy; Energy (signal processing); Computer science; Environmental economics; Business; Electrical engineering; Renewable energy; Engineering; Economics","score_opus":0.011121727560811215,"score_gpt":0.23691115494080106,"score_spread":0.22578942737998986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230110808","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":[0.0019310201,0.000105024126,0.82440394,0.0009343492,0.0018128194,0.0002437427,0.000017654811,0.0006100285,0.16994143],"genre_scores_gemma":[0.62881124,0.00036717602,0.0001129676,0.00085123844,0.00016109347,0.0005130408,0.000006707775,0.0001371832,0.36903936],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99432135,0.00020462774,0.0007834685,0.001382968,0.0009420834,0.0023655272],"domain_scores_gemma":[0.99557894,0.00023346246,0.0003708436,0.0027660152,0.000529996,0.0005207307],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00051883,0.00092766195,0.0007300604,0.0010690322,0.0053235786,0.0006864104,0.0014945237,0.0005202662,0.0015250924],"category_scores_gemma":[0.000024296325,0.0009519639,0.00064810883,0.00072767213,0.00042936738,0.001251708,0.000007362079,0.00063546334,0.00011266354],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038379445,0.0012044042,3.4171495e-7,0.00010387007,0.00027232946,0.0006261596,0.00018107428,0.6428585,0.00031464215,0.30041584,0.002039238,0.051599804],"study_design_scores_gemma":[0.002735533,0.0010590901,0.000013231155,0.00009031452,0.00029997516,0.000032164433,0.0050064973,0.008968228,0.19373877,0.009803145,0.7766626,0.0015904512],"about_ca_topic_score_codex":0.041612953,"about_ca_topic_score_gemma":0.0039893566,"teacher_disagreement_score":0.824291,"about_ca_system_score_codex":0.0010404424,"about_ca_system_score_gemma":0.0003671559,"threshold_uncertainty_score":0.9993876},"labels":[],"label_agreement":null},{"id":"W4235203459","doi":"10.1109/tste.2021.3065155","title":"IEEE industry applications society","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Engineering; Electrical engineering","score_opus":0.009481953432038993,"score_gpt":0.22641946734151028,"score_spread":0.21693751390947127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235203459","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":[0.00030893538,0.00009386192,0.99427056,0.0015884412,0.0004131303,0.00004637924,0.0000020554273,0.00015212338,0.0031244939],"genre_scores_gemma":[0.93226576,0.00011078497,0.025839861,0.00088378583,0.00015534909,0.00024803964,0.0000033448575,0.000022328051,0.04047074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99895936,0.000016551176,0.00015392619,0.00032481467,0.00020156385,0.00034376222],"domain_scores_gemma":[0.9989945,0.000077630095,0.000027766659,0.0005000476,0.00026907772,0.00013094276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008126208,0.00012637669,0.00010309278,0.00007639302,0.00032913458,0.0001366775,0.0003192127,0.00015405797,0.00005305399],"category_scores_gemma":[0.0000022319064,0.0001442775,0.00012222571,0.00087448466,0.000022299493,0.00028712876,0.0000037269895,0.00030976706,0.0000145937975],"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":[8.45503e-7,0.00022914149,0.0000013969346,0.000030497435,0.00004781922,0.00001788791,0.00016205657,0.7016164,0.00075947936,0.28515112,0.0020059226,0.009977445],"study_design_scores_gemma":[0.00064912386,0.00007798329,0.00007057477,0.00003811178,0.000049560695,0.000116144955,0.0032701013,0.18725945,0.17112458,0.017050477,0.6193244,0.00096950476],"about_ca_topic_score_codex":0.00006377299,"about_ca_topic_score_gemma":0.0000063184984,"teacher_disagreement_score":0.9684307,"about_ca_system_score_codex":0.00018066369,"about_ca_system_score_gemma":0.0004378276,"threshold_uncertainty_score":0.58834654},"labels":[],"label_agreement":null},{"id":"W4237366877","doi":"10.1109/tste.2019.2921049","title":"IEEE Transactions on Sustainable Energy","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Energy Efficiency and Management","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Energy (signal processing); Sustainable energy; Computer science; Environmental economics; Electrical engineering; Engineering; Renewable energy; Economics","score_opus":0.006517135357169525,"score_gpt":0.21128135264221115,"score_spread":0.20476421728504163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237366877","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":[0.005820587,0.00014011902,0.8276546,0.00048448786,0.0019589076,0.00036801078,0.000015378062,0.00079352973,0.16276439],"genre_scores_gemma":[0.5938657,0.00024326301,0.00009079609,0.0012277849,0.00009520075,0.00040966138,0.000010012467,0.00013996332,0.4039176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941,0.00025458614,0.00083161856,0.0014347903,0.0010018718,0.002377149],"domain_scores_gemma":[0.99686235,0.00032779746,0.0002163436,0.0016545847,0.0004828434,0.00045610522],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00046124717,0.0009276158,0.0007569114,0.0014098014,0.0012497654,0.00024741358,0.00083550246,0.0005195176,0.003921443],"category_scores_gemma":[0.000008009914,0.0009503231,0.0006426812,0.0019966858,0.00018242263,0.00084840297,0.000004427699,0.0006454624,0.00035876385],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037431385,0.0010877325,3.6062846e-7,0.00013161609,0.00022830773,0.00024508222,0.00018373314,0.7140919,0.0005686691,0.2603495,0.0013963006,0.021342447],"study_design_scores_gemma":[0.0027065398,0.0014612013,0.0000044149083,0.00008157747,0.00022143377,0.000029909323,0.00810233,0.012761732,0.1790454,0.005502572,0.7885532,0.0015296947],"about_ca_topic_score_codex":0.019836225,"about_ca_topic_score_gemma":0.0013445849,"teacher_disagreement_score":0.8275638,"about_ca_system_score_codex":0.0012230246,"about_ca_system_score_gemma":0.00037422124,"threshold_uncertainty_score":0.99929476},"labels":[],"label_agreement":null},{"id":"W4239000591","doi":"10.1109/tste.2020.3042037","title":"IEEE industry applications society","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Engineering; Computer science","score_opus":0.01353768407292295,"score_gpt":0.22228035316699402,"score_spread":0.20874266909407108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239000591","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":[0.00020138886,0.000039310115,0.9921208,0.005405208,0.00020469843,0.00007647277,0.0000021338335,0.00023043348,0.0017195626],"genre_scores_gemma":[0.9786387,0.000041796207,0.014093729,0.0022535508,0.00018731169,0.0001927115,0.0000014235745,0.00001963973,0.004571115],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990076,0.000011626157,0.00015349191,0.00031261484,0.00019465339,0.00032005965],"domain_scores_gemma":[0.999264,0.000057192727,0.00003102839,0.00030729192,0.00012692122,0.00021358686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059737293,0.00013253694,0.00010455736,0.00005836887,0.00027373526,0.00010680808,0.00044763196,0.00013611355,0.000033835222],"category_scores_gemma":[0.0000020976825,0.00014527814,0.00010935035,0.0007874849,0.000023324648,0.0003034513,0.0000033728206,0.00032976182,0.000022847842],"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":[0.0000019050893,0.000097471166,0.0000010987487,0.00003363225,0.000034595676,0.0000046542873,0.0003761029,0.84021765,0.00042555275,0.14873089,0.0030560093,0.0070204153],"study_design_scores_gemma":[0.00048766553,0.00015022908,0.000025362635,0.000014704514,0.00003094712,0.000014642451,0.0019156055,0.5177949,0.033448927,0.004078522,0.44135237,0.0006861351],"about_ca_topic_score_codex":0.000058536432,"about_ca_topic_score_gemma":0.0000013287708,"teacher_disagreement_score":0.9784373,"about_ca_system_score_codex":0.000114794566,"about_ca_system_score_gemma":0.0002037091,"threshold_uncertainty_score":0.5924271},"labels":[],"label_agreement":null},{"id":"W4239180994","doi":"10.1109/tste.2019.2956619","title":"IEEE industry applications society","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Engineering; Systems engineering","score_opus":0.006682364941737042,"score_gpt":0.2148043793506126,"score_spread":0.20812201440887557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239180994","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":[0.0015981448,0.000033542736,0.99233294,0.0007373553,0.0005188337,0.000111857225,0.0000014987909,0.00016888176,0.004496961],"genre_scores_gemma":[0.95268846,0.000032210348,0.008440667,0.00046874158,0.00008416224,0.00018063013,0.0000013470649,0.000018458672,0.03808533],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99896204,0.0000112135085,0.00014915165,0.00031256524,0.00020725267,0.0003577434],"domain_scores_gemma":[0.9991152,0.00007353509,0.000033485907,0.00052314746,0.00013995184,0.00011465442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009847956,0.00013417394,0.00010803535,0.00011096344,0.00020404316,0.00010472947,0.0004366586,0.00015918328,0.000071362076],"category_scores_gemma":[8.093881e-7,0.00014390134,0.00011211784,0.0006406673,0.000017940063,0.00035406052,0.0000030685558,0.00030985227,0.000067562076],"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":[0.000001325995,0.00012843366,0.0000049003684,0.000031028027,0.00003176172,0.0000017204061,0.00013180362,0.77460474,0.0004577282,0.21842317,0.0010038874,0.005179525],"study_design_scores_gemma":[0.00089923583,0.00020180184,0.00014276236,0.000043460437,0.00003646028,0.000038235827,0.0024798934,0.41193062,0.041955244,0.011896483,0.5292284,0.0011474302],"about_ca_topic_score_codex":0.00010196166,"about_ca_topic_score_gemma":0.0000023203315,"teacher_disagreement_score":0.98389226,"about_ca_system_score_codex":0.00018565835,"about_ca_system_score_gemma":0.00020916143,"threshold_uncertainty_score":0.5868127},"labels":[],"label_agreement":null},{"id":"W4245003367","doi":"10.1109/tste.2020.3000940","title":"IEEE industry applications society","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Engineering","score_opus":0.01353768407292295,"score_gpt":0.22228035316699402,"score_spread":0.20874266909407108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245003367","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":[0.00020138886,0.000039310115,0.9921208,0.005405208,0.00020469843,0.00007647277,0.0000021338335,0.00023043348,0.0017195626],"genre_scores_gemma":[0.9786387,0.000041796207,0.014093729,0.0022535508,0.00018731169,0.0001927115,0.0000014235745,0.00001963973,0.004571115],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990076,0.000011626157,0.00015349191,0.00031261484,0.00019465339,0.00032005965],"domain_scores_gemma":[0.999264,0.000057192727,0.00003102839,0.00030729192,0.00012692122,0.00021358686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059737293,0.00013253694,0.00010455736,0.00005836887,0.00027373526,0.00010680808,0.00044763196,0.00013611355,0.000033835222],"category_scores_gemma":[0.0000020976825,0.00014527814,0.00010935035,0.0007874849,0.000023324648,0.0003034513,0.0000033728206,0.00032976182,0.000022847842],"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":[0.0000019050893,0.000097471166,0.0000010987487,0.00003363225,0.000034595676,0.0000046542873,0.0003761029,0.84021765,0.00042555275,0.14873089,0.0030560093,0.0070204153],"study_design_scores_gemma":[0.00048766553,0.00015022908,0.000025362635,0.000014704514,0.00003094712,0.000014642451,0.0019156055,0.5177949,0.033448927,0.004078522,0.44135237,0.0006861351],"about_ca_topic_score_codex":0.000058536432,"about_ca_topic_score_gemma":0.0000013287708,"teacher_disagreement_score":0.9784373,"about_ca_system_score_codex":0.000114794566,"about_ca_system_score_gemma":0.0002037091,"threshold_uncertainty_score":0.5924271},"labels":[],"label_agreement":null},{"id":"W4245793701","doi":"10.1109/tste.2019.2898308","title":"IEEE Transactions on Sustainable Energy","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Energy Efficiency and Management","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Energy (signal processing); Sustainable energy; Computer science; Environmental economics; Electrical engineering; Renewable energy; Engineering; Economics","score_opus":0.006517135357169525,"score_gpt":0.21128135264221115,"score_spread":0.20476421728504163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245793701","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":[0.005820587,0.00014011902,0.8276546,0.00048448786,0.0019589076,0.00036801078,0.000015378062,0.00079352973,0.16276439],"genre_scores_gemma":[0.5938657,0.00024326301,0.00009079609,0.0012277849,0.00009520075,0.00040966138,0.000010012467,0.00013996332,0.4039176],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941,0.00025458614,0.00083161856,0.0014347903,0.0010018718,0.002377149],"domain_scores_gemma":[0.99686235,0.00032779746,0.0002163436,0.0016545847,0.0004828434,0.00045610522],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00046124717,0.0009276158,0.0007569114,0.0014098014,0.0012497654,0.00024741358,0.00083550246,0.0005195176,0.003921443],"category_scores_gemma":[0.000008009914,0.0009503231,0.0006426812,0.0019966858,0.00018242263,0.00084840297,0.000004427699,0.0006454624,0.00035876385],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037431385,0.0010877325,3.6062846e-7,0.00013161609,0.00022830773,0.00024508222,0.00018373314,0.7140919,0.0005686691,0.2603495,0.0013963006,0.021342447],"study_design_scores_gemma":[0.0027065398,0.0014612013,0.0000044149083,0.00008157747,0.00022143377,0.000029909323,0.00810233,0.012761732,0.1790454,0.005502572,0.7885532,0.0015296947],"about_ca_topic_score_codex":0.019836225,"about_ca_topic_score_gemma":0.0013445849,"teacher_disagreement_score":0.8275638,"about_ca_system_score_codex":0.0012230246,"about_ca_system_score_gemma":0.00037422124,"threshold_uncertainty_score":0.99929476},"labels":[],"label_agreement":null},{"id":"W4283217967","doi":"10.1109/tste.2022.3179086","title":"IEEE Industry Applications Society","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Business; Engineering","score_opus":0.00890662127832284,"score_gpt":0.218807547898724,"score_spread":0.20990092662040116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283217967","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":[0.0003972776,0.00004850513,0.99550056,0.0013159733,0.0004957033,0.00008549584,0.000004663912,0.00018016867,0.001971664],"genre_scores_gemma":[0.9672672,0.000021111657,0.0068063447,0.00074080157,0.00008486325,0.00090984843,0.0000026667467,0.000019594669,0.024147559],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988899,0.000023992576,0.00014971808,0.00029848516,0.00028969935,0.00034819124],"domain_scores_gemma":[0.9992568,0.000067941444,0.000036069396,0.00044058546,0.00009192212,0.00010670334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014532018,0.000119819604,0.00009102166,0.00013321062,0.00090287044,0.000080426566,0.0005523785,0.00007050322,0.00011536548],"category_scores_gemma":[8.43484e-7,0.00014303095,0.00011232371,0.00092927826,0.000020320644,0.0002266685,0.000008186472,0.00046531358,0.000006502019],"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":[0.0000011590771,0.00015051637,7.03021e-7,0.000009101932,0.000021021639,0.0000036912404,0.00016118605,0.8473621,0.00012550275,0.14584564,0.0021096622,0.0042097257],"study_design_scores_gemma":[0.00039679618,0.00014063259,0.000022686218,0.000004790834,0.000022223112,0.000051672563,0.0036886488,0.23998414,0.0073383367,0.008941575,0.7388434,0.00056511274],"about_ca_topic_score_codex":0.00014163765,"about_ca_topic_score_gemma":0.000002186035,"teacher_disagreement_score":0.9886942,"about_ca_system_score_codex":0.00037384802,"about_ca_system_score_gemma":0.00027738378,"threshold_uncertainty_score":0.6944241},"labels":[],"label_agreement":null},{"id":"W4285820315","doi":"10.1109/tste.2022.3191631","title":"Fault Ride Through of Inverter-Interfaced Renewable Energy Sources for Enhanced Resiliency and Grid Code Compliance","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":35,"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":"King Abdulaziz University","keywords":"Grid code; Inverter; Fault (geology); Grid; Engineering; Controller (irrigation); Electronic engineering; Control theory (sociology); Computer science; Selection (genetic algorithm); Renewable energy; Reliability engineering; Voltage; Electrical engineering; AC power; Control (management)","score_opus":0.00999046421153897,"score_gpt":0.21134944913233095,"score_spread":0.201358984920792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285820315","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":[0.00826497,0.0012744984,0.98858434,0.000053521013,0.00037475146,0.00015459883,0.00010664048,0.00016307339,0.0010236311],"genre_scores_gemma":[0.98979735,0.0007502255,0.00087407953,0.000103970306,0.00004166841,0.00042433175,0.00001873436,0.000049069604,0.007940548],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99881876,0.000041599327,0.0003145017,0.00028213486,0.00015470327,0.00038829437],"domain_scores_gemma":[0.99942327,0.00008823468,0.00006934461,0.00024300125,0.000120536184,0.00005564508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008308142,0.00020047942,0.0002816596,0.00014592335,0.00037437968,0.000029488509,0.00017653815,0.000061415914,0.00010726561],"category_scores_gemma":[0.000003918782,0.00022578465,0.000090461996,0.00032054086,0.000051206785,0.00021045962,0.0000049336672,0.000105638246,3.0038456e-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":[0.00018577969,0.00006560675,6.7092134e-7,0.00012661888,0.00006362082,0.0000023971622,0.000369,0.97591645,0.018343717,0.00032448908,0.001779808,0.0028218692],"study_design_scores_gemma":[0.001290489,0.0003018981,0.0000019232855,0.00002463248,0.000045889712,0.000006769288,0.0021165067,0.38803732,0.53995305,0.0010976272,0.066832446,0.000291465],"about_ca_topic_score_codex":0.002691858,"about_ca_topic_score_gemma":0.0008316947,"teacher_disagreement_score":0.98771024,"about_ca_system_score_codex":0.0001522105,"about_ca_system_score_gemma":0.00004343975,"threshold_uncertainty_score":0.9207231},"labels":[],"label_agreement":null},{"id":"W4296708720","doi":"10.1109/tste.2022.3202333","title":"IEEE Industry Applications Society Information","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Human auditory perception and evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Engineering; Systems engineering","score_opus":0.009635895685735299,"score_gpt":0.21946400247890166,"score_spread":0.20982810679316635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296708720","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":[0.007547492,0.000016578984,0.9811384,0.00010373602,0.00075356837,0.00022642943,0.000033825432,0.00065467693,0.009525308],"genre_scores_gemma":[0.9795946,0.00004070858,0.00013581294,0.0005372305,0.00015733653,0.0016762615,0.00004213916,0.000032105338,0.01778384],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99896604,0.000038993763,0.00024158566,0.00012884683,0.00033279383,0.00029173854],"domain_scores_gemma":[0.9995154,0.000022965054,0.000037057504,0.00024788646,0.000093080045,0.000083570565],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00018358388,0.00014364133,0.00010219987,0.00020669389,0.00082647894,0.00005842616,0.00014565665,0.00013270012,0.011497336],"category_scores_gemma":[7.862016e-7,0.0001796234,0.000115026465,0.0005203433,0.000028710447,0.0005169849,0.0000016907417,0.00054626586,0.00032965108],"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":[0.000006484898,0.000048344893,5.161991e-7,0.0000314005,0.000027798063,6.3201276e-7,0.0005324665,0.9399935,0.00036564088,0.00026981914,0.04443303,0.014290388],"study_design_scores_gemma":[0.0004238286,0.000055944904,0.000021731115,0.0000023233551,0.00002646474,0.000007664208,0.008105375,0.093756616,0.0026911309,0.00033096733,0.89430994,0.00026799183],"about_ca_topic_score_codex":0.000016595994,"about_ca_topic_score_gemma":0.000005978452,"teacher_disagreement_score":0.98100257,"about_ca_system_score_codex":0.00075890287,"about_ca_system_score_gemma":0.00008249405,"threshold_uncertainty_score":0.9894063},"labels":[],"label_agreement":null},{"id":"W4312039228","doi":"10.1109/tste.2022.3227789","title":"IEEE Industry Applications Society Information","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Human auditory perception and evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Systems engineering; Engineering","score_opus":0.009635895685735299,"score_gpt":0.21946400247890166,"score_spread":0.20982810679316635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312039228","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":[0.007547492,0.000016578984,0.9811384,0.00010373602,0.00075356837,0.00022642943,0.000033825432,0.00065467693,0.009525308],"genre_scores_gemma":[0.9795946,0.00004070858,0.00013581294,0.0005372305,0.00015733653,0.0016762615,0.00004213916,0.000032105338,0.01778384],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99896604,0.000038993763,0.00024158566,0.00012884683,0.00033279383,0.00029173854],"domain_scores_gemma":[0.9995154,0.000022965054,0.000037057504,0.00024788646,0.000093080045,0.000083570565],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00018358388,0.00014364133,0.00010219987,0.00020669389,0.00082647894,0.00005842616,0.00014565665,0.00013270012,0.011497336],"category_scores_gemma":[7.862016e-7,0.0001796234,0.000115026465,0.0005203433,0.000028710447,0.0005169849,0.0000016907417,0.00054626586,0.00032965108],"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":[0.000006484898,0.000048344893,5.161991e-7,0.0000314005,0.000027798063,6.3201276e-7,0.0005324665,0.9399935,0.00036564088,0.00026981914,0.04443303,0.014290388],"study_design_scores_gemma":[0.0004238286,0.000055944904,0.000021731115,0.0000023233551,0.00002646474,0.000007664208,0.008105375,0.093756616,0.0026911309,0.00033096733,0.89430994,0.00026799183],"about_ca_topic_score_codex":0.000016595994,"about_ca_topic_score_gemma":0.000005978452,"teacher_disagreement_score":0.98100257,"about_ca_system_score_codex":0.00075890287,"about_ca_system_score_gemma":0.00008249405,"threshold_uncertainty_score":0.9894063},"labels":[],"label_agreement":null},{"id":"W4313465417","doi":"10.1109/tste.2022.3215686","title":"Hierarchical Distributed Energy Management Framework for Multiple Greenhouses Considering Demand Response","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Greenhouse; Computer science; Grid; Distributed generation; Limiting; Time limit; Limit (mathematics); News aggregator; Demand response; Energy consumption; Electricity; Distributed computing; Engineering; Mathematics; Electrical engineering; Systems engineering; Renewable energy; Operating system","score_opus":0.01271063347198744,"score_gpt":0.21549677375398887,"score_spread":0.20278614028200143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313465417","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":[0.32049015,0.000145498,0.6747089,0.003047714,0.00024792182,0.00033494644,0.00034085682,0.0006030281,0.00008100844],"genre_scores_gemma":[0.9950611,0.000063614825,0.00043730275,0.0007033568,0.000040276114,0.0013729176,0.000039619976,0.0000065654144,0.0022752297],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99814725,0.0002185774,0.00026951992,0.00046705932,0.00023063821,0.0006669854],"domain_scores_gemma":[0.9982711,0.0013104563,0.0000784907,0.00016061052,0.00006969144,0.00010962932],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00033025487,0.0002244006,0.00024734423,0.00008443309,0.0017849267,0.000047580168,0.00034855673,0.00015628528,0.00047956264],"category_scores_gemma":[0.000031771415,0.00012826476,0.00019361431,0.0005662022,0.00010344262,0.000083647996,0.000019176188,0.00027798073,0.0000020380705],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.02750778,0.0036513042,0.00037919584,0.00013764742,0.0010181216,0.0013293247,0.0002983916,0.15169857,0.031240003,0.46585116,0.0041644685,0.31272402],"study_design_scores_gemma":[0.0034825983,0.0038326634,0.002349761,0.00004583144,0.0002547449,0.00011202472,0.013131836,0.007791066,0.046452336,0.10511468,0.8159738,0.0014586534],"about_ca_topic_score_codex":0.00029052258,"about_ca_topic_score_gemma":0.00047146188,"teacher_disagreement_score":0.8118093,"about_ca_system_score_codex":0.0001769811,"about_ca_system_score_gemma":0.000020102163,"threshold_uncertainty_score":0.99951464},"labels":[],"label_agreement":null},{"id":"W4319338726","doi":"10.1109/tste.2023.3243030","title":"Adaptive Fault-Tolerant Control for a 2-Body Point Absorber Wave Energy Converter Against Actuator Faults: An Iterative Learning Control Approach","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wave and Wind Energy Systems","field":"Engineering","cited_by":18,"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":"Japan Society for the Promotion of Science; National Natural Science Foundation of China","keywords":"Iterative learning control; Control theory (sociology); Actuator; Lyapunov function; Adaptive control; Iterative method; Fault (geology); Computer science; Tracking error; Control engineering; Engineering; Algorithm; Artificial intelligence; Control (management)","score_opus":0.01030962868129473,"score_gpt":0.203112899762216,"score_spread":0.19280327108092127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319338726","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":[0.008071858,0.00008915219,0.9864498,0.00007567513,0.0006586055,0.0005002909,0.00016244141,0.0011317497,0.0028604195],"genre_scores_gemma":[0.98278916,0.00007501393,0.0001739423,0.00046173602,0.0003574914,0.0019115978,0.00014373971,0.00022687801,0.013860426],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967484,0.00022694682,0.00064460794,0.00071394746,0.00038459655,0.0012814978],"domain_scores_gemma":[0.998301,0.0003532243,0.00011064422,0.00047192883,0.00040896086,0.0003542151],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034841642,0.0006647994,0.0007940445,0.0006346447,0.00058289035,0.00014438806,0.00024159835,0.00038695897,0.00004258095],"category_scores_gemma":[0.000012323664,0.00063383154,0.00039495822,0.00066381367,0.00008562667,0.0006891431,0.000002706436,0.00040471376,0.000018972802],"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":[0.0005048692,0.0001724492,9.837563e-7,0.00010019017,0.00074638077,0.00011111374,0.0012957341,0.9813548,0.002978977,0.0041194656,0.0007732207,0.007841819],"study_design_scores_gemma":[0.004878737,0.0005583124,0.000005817812,0.000056732646,0.000119360986,0.00001831399,0.010416308,0.9502649,0.0074123223,0.00021464196,0.025291063,0.0007635007],"about_ca_topic_score_codex":0.0006457815,"about_ca_topic_score_gemma":0.00006770338,"teacher_disagreement_score":0.98627585,"about_ca_system_score_codex":0.0004460843,"about_ca_system_score_gemma":0.00011760634,"threshold_uncertainty_score":0.9996113},"labels":[],"label_agreement":null},{"id":"W4319338799","doi":"10.1109/tste.2023.3243163","title":"A Multi-Port DC Power Flow Controller Integrated With MMC Stations for Offshore Meshed Multi-Terminal HVDC Grids","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Opal-Rt Technologies (Canada); Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Engineering; Converters; Transformer; Electrical engineering; Voltage","score_opus":0.011273878585773263,"score_gpt":0.23348343920082018,"score_spread":0.22220956061504693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319338799","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":[0.011499294,0.000051160197,0.9854167,0.00004566774,0.0006395005,0.0009230185,0.0001552059,0.0010839755,0.00018547194],"genre_scores_gemma":[0.9614646,0.000027775857,0.0040113647,0.000029363442,0.00004982324,0.0025796313,0.00007836199,0.00013243918,0.031626683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982293,0.000046534096,0.0004244657,0.00039255296,0.00020723921,0.0006998802],"domain_scores_gemma":[0.99900055,0.00008799834,0.000057058613,0.00029239434,0.0004219939,0.0001399795],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023552368,0.000367997,0.00039011697,0.0005727986,0.00041298868,0.00009752124,0.00013581065,0.00021666297,0.00008202459],"category_scores_gemma":[0.000012731503,0.00032178,0.00017510563,0.0010296548,0.000050428887,0.0003130923,0.0000012840961,0.00026984233,0.000026477974],"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":[0.00031574394,0.00020933658,0.000006248877,0.0001799411,0.0003521808,0.000090618014,0.0006720265,0.9819396,0.004700615,0.00013113905,0.0011573434,0.010245175],"study_design_scores_gemma":[0.005780898,0.0004897949,0.0001572678,0.00008795264,0.000114499715,0.000045425157,0.0067977402,0.9053826,0.014817174,0.000024543662,0.06567145,0.0006306737],"about_ca_topic_score_codex":0.00068113254,"about_ca_topic_score_gemma":0.0006525821,"teacher_disagreement_score":0.9814053,"about_ca_system_score_codex":0.00034144416,"about_ca_system_score_gemma":0.0001352818,"threshold_uncertainty_score":0.9999234},"labels":[],"label_agreement":null},{"id":"W4376456770","doi":"10.1109/tste.2023.3274939","title":"An Improved PSO-Based MPPT Technique Using Stability and Steady State Analyses Under Partial Shading Conditions","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Maximum power point tracking; Control theory (sociology); Maximum power principle; Photovoltaic system; Steady state (chemistry); Convergence (economics); Stability (learning theory); Power (physics); Voltage; Trajectory; Shading; Computer science; Mathematics; Engineering; Physics; Artificial intelligence","score_opus":0.04474805521770682,"score_gpt":0.3262589835086157,"score_spread":0.2815109282909089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376456770","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":[0.106890924,0.000015252991,0.8902227,0.000048530594,0.00011944566,0.0005262986,0.000097636155,0.0017331655,0.00034599402],"genre_scores_gemma":[0.99535906,0.000024805593,0.0024343904,0.00014260745,0.000033607477,0.00092951517,0.00007451011,0.00011077032,0.00089072494],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99715245,0.00037508825,0.00061644206,0.0007362445,0.00033672203,0.0007830475],"domain_scores_gemma":[0.9980822,0.00024654192,0.00018674211,0.000770293,0.00043924953,0.00027494167],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006033371,0.00039907987,0.00044417856,0.0010073916,0.0008082517,0.00019314789,0.0002335773,0.0002469898,0.00029160385],"category_scores_gemma":[0.00002260289,0.00042623573,0.00015093578,0.0017702226,0.00019991129,0.00068670796,0.000005778505,0.00024453655,0.0000037987172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008978601,0.00019933633,0.000011724848,0.000074502204,0.00008138776,0.000034755594,0.00014032454,0.72866786,0.26880896,0.001495073,0.000029940133,0.0003663453],"study_design_scores_gemma":[0.0004494451,0.0001809311,0.000012713849,0.00002857717,0.00007061889,0.000009298347,0.0021266243,0.34522963,0.64908946,0.002045623,0.00039602723,0.00036104931],"about_ca_topic_score_codex":0.016041381,"about_ca_topic_score_gemma":0.0008907094,"teacher_disagreement_score":0.88846815,"about_ca_system_score_codex":0.0006388657,"about_ca_system_score_gemma":0.0003641202,"threshold_uncertainty_score":0.9998189},"labels":[],"label_agreement":null},{"id":"W4381434041","doi":"10.1109/tste.2023.3281111","title":"IEEE Industry Applications Society Information","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Human auditory perception and evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Systems engineering; Engineering","score_opus":0.013220812798144875,"score_gpt":0.23818250187125897,"score_spread":0.2249616890731141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381434041","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":[0.011667781,0.00000712916,0.97632194,0.00012488081,0.00070290576,0.0002110902,0.00001860204,0.0018155492,0.009130104],"genre_scores_gemma":[0.96879417,0.0001763837,0.0001159665,0.0003099504,0.00026950546,0.0008319338,0.000058126418,0.000041468917,0.02940249],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99900776,0.000019760595,0.00024220091,0.00012815252,0.00025306654,0.00034905848],"domain_scores_gemma":[0.99946177,0.000032291162,0.00002848898,0.000248104,0.00013026227,0.00009907762],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00017133314,0.0001535149,0.00010689169,0.0002910176,0.00035680708,0.000078515244,0.00011375237,0.00027665988,0.002381067],"category_scores_gemma":[0.0000016295664,0.00017655607,0.00011232015,0.0008972385,0.000035184148,0.0006526563,8.1988776e-7,0.00033541693,0.0030552472],"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":[0.0000037025786,0.000020679046,7.2294154e-7,0.00006457938,0.000031111424,8.302792e-7,0.0004751264,0.8907143,0.00058278616,0.00022422339,0.08557491,0.022307029],"study_design_scores_gemma":[0.00050716155,0.00003741595,0.00012206818,0.000012108142,0.00003337827,0.0000034682666,0.005816536,0.21213782,0.008137695,0.0006240666,0.77219564,0.00037263532],"about_ca_topic_score_codex":0.000011340588,"about_ca_topic_score_gemma":0.000009284944,"teacher_disagreement_score":0.976206,"about_ca_system_score_codex":0.00032238994,"about_ca_system_score_gemma":0.000059382204,"threshold_uncertainty_score":0.99853086},"labels":[],"label_agreement":null},{"id":"W4386078221","doi":"10.1109/tste.2023.3307633","title":"Optimal Design of V2G Incentives and V2G-Capable Electric Vehicles Parking Lots Considering Cost-Benefit Financial Analysis and User Participation","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; York University","keywords":"Revenue; Vehicle-to-grid; Electric vehicle; Grid; Incentive; Profit (economics); Profit maximization; Computer science; Transport engineering; Finance; Engineering; Business; Power (physics); Economics","score_opus":0.00883708406185952,"score_gpt":0.21253807889192008,"score_spread":0.20370099483006057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386078221","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":[0.49846843,0.00024666873,0.50099766,0.000011297688,0.00003135014,0.00009615041,0.00000397684,0.000114788076,0.000029661167],"genre_scores_gemma":[0.9976402,0.0010687622,0.00080093154,0.000017635848,0.000021403244,0.00007574947,0.000003291549,0.000031376327,0.00034065585],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870974,0.00003687078,0.00036718437,0.0002448529,0.000152135,0.0004892376],"domain_scores_gemma":[0.999389,0.0001904407,0.00009051489,0.00013785376,0.000102913706,0.000089279216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019355348,0.00019314146,0.00032257775,0.00068439374,0.00021904027,0.00006034443,0.00006241734,0.00012704264,0.00002177438],"category_scores_gemma":[0.000022035656,0.00020522329,0.0000685088,0.0019966583,0.000042865056,0.00037798184,0.00000311069,0.00016122214,6.7381796e-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":[0.000047956244,0.000018938796,0.00026862873,0.00007432177,0.0002097283,0.00001394686,0.00021412066,0.9710339,0.01076874,0.0006550711,0.00005754934,0.016637135],"study_design_scores_gemma":[0.000518391,0.00017674956,0.008467014,0.0000321369,0.00038396617,0.000006028906,0.00048713948,0.7635401,0.22460811,0.0007799107,0.00064630236,0.0003541588],"about_ca_topic_score_codex":0.00026480728,"about_ca_topic_score_gemma":0.00006528665,"teacher_disagreement_score":0.50019675,"about_ca_system_score_codex":0.0000911412,"about_ca_system_score_gemma":0.000046602887,"threshold_uncertainty_score":0.8368763},"labels":[],"label_agreement":null},{"id":"W4387789659","doi":"10.1109/tste.2023.3325882","title":"A New Closed-Loop Solar Power Forecasting Method With Sample Selection","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":17,"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 Calgary","funders":"","keywords":"Selection (genetic algorithm); Sample (material); Power (physics); Solar power; Computer science; Photovoltaic system; Control theory (sociology); Engineering; Electrical engineering; Artificial intelligence; Control (management); Physics","score_opus":0.017239083973880843,"score_gpt":0.24759844200955425,"score_spread":0.2303593580356734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387789659","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":[0.0011205171,0.000012219367,0.9962902,0.00034063222,0.00033297873,0.00014303517,0.0000039763154,0.0007634122,0.0009930357],"genre_scores_gemma":[0.7708125,0.000036001347,0.17860806,0.0009836174,0.00013073103,0.00015803827,0.000010138304,0.00008889568,0.049172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981936,0.00011414722,0.00021924192,0.0004828524,0.0003666428,0.0006235196],"domain_scores_gemma":[0.99870926,0.00038210972,0.000082976076,0.0003900624,0.00022221131,0.00021336263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036176748,0.00021725764,0.00018659477,0.0005522821,0.0005872138,0.00024360522,0.0003569884,0.0001158126,0.00012869465],"category_scores_gemma":[0.000024725101,0.00020768242,0.00010166106,0.0030740597,0.000015644871,0.0006692611,0.0000049266455,0.00024152684,0.000026812342],"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":[0.00015122659,0.00017033622,0.000042102296,0.00004700063,0.0001800063,0.00014593768,0.0021355997,0.7153658,0.0013509486,0.044644937,0.007048166,0.22871791],"study_design_scores_gemma":[0.0012651036,0.0007150206,0.00007907492,0.000023242892,0.000037378493,0.00010714807,0.00093952555,0.77094173,0.08583957,0.0084471805,0.13098879,0.00061625405],"about_ca_topic_score_codex":0.0034475063,"about_ca_topic_score_gemma":0.0003237335,"teacher_disagreement_score":0.81768215,"about_ca_system_score_codex":0.00020144589,"about_ca_system_score_gemma":0.00045894945,"threshold_uncertainty_score":0.84690434},"labels":[],"label_agreement":null},{"id":"W4389988021","doi":"10.1109/tste.2023.3341579","title":"IEEE Industry Applications Society Information","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Human auditory perception and evaluation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Engineering; Systems engineering","score_opus":0.013220812798144875,"score_gpt":0.23818250187125897,"score_spread":0.2249616890731141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389988021","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":[0.011667781,0.00000712916,0.97632194,0.00012488081,0.00070290576,0.0002110902,0.00001860204,0.0018155492,0.009130104],"genre_scores_gemma":[0.96879417,0.0001763837,0.0001159665,0.0003099504,0.00026950546,0.0008319338,0.000058126418,0.000041468917,0.02940249],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99900776,0.000019760595,0.00024220091,0.00012815252,0.00025306654,0.00034905848],"domain_scores_gemma":[0.99946177,0.000032291162,0.00002848898,0.000248104,0.00013026227,0.00009907762],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00017133314,0.0001535149,0.00010689169,0.0002910176,0.00035680708,0.000078515244,0.00011375237,0.00027665988,0.002381067],"category_scores_gemma":[0.0000016295664,0.00017655607,0.00011232015,0.0008972385,0.000035184148,0.0006526563,8.1988776e-7,0.00033541693,0.0030552472],"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":[0.0000037025786,0.000020679046,7.2294154e-7,0.00006457938,0.000031111424,8.302792e-7,0.0004751264,0.8907143,0.00058278616,0.00022422339,0.08557491,0.022307029],"study_design_scores_gemma":[0.00050716155,0.00003741595,0.00012206818,0.000012108142,0.00003337827,0.0000034682666,0.005816536,0.21213782,0.008137695,0.0006240666,0.77219564,0.00037263532],"about_ca_topic_score_codex":0.000011340588,"about_ca_topic_score_gemma":0.000009284944,"teacher_disagreement_score":0.976206,"about_ca_system_score_codex":0.00032238994,"about_ca_system_score_gemma":0.000059382204,"threshold_uncertainty_score":0.99853086},"labels":[],"label_agreement":null},{"id":"W4390187331","doi":"10.1109/tste.2023.3346282","title":"Dual Current Control of Renewable Energy Sources for Recent Grid Code Compliance and Reliability Enhancement","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":6,"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":"Grid code; Reliability engineering; Grid; Renewable energy; Dual (grammatical number); Reliability (semiconductor); Engineering; Fault (geology); Computer science; Low voltage ride through; Controller (irrigation); AC power; Voltage; Control theory (sociology); Power (physics); Electrical engineering; Control (management)","score_opus":0.011771174418299814,"score_gpt":0.22698238628733852,"score_spread":0.21521121186903872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390187331","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":[0.0019318969,0.0017369785,0.99477947,0.0001454587,0.00065293576,0.0002257607,0.00011392962,0.00022937972,0.00018416937],"genre_scores_gemma":[0.9863853,0.009713206,0.00035262352,0.00004638135,0.00010306361,0.00051830837,0.00003982573,0.000044646255,0.002796685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987472,0.000033839744,0.0003514356,0.00027836394,0.00015292228,0.00043623388],"domain_scores_gemma":[0.9992257,0.00014160748,0.00005908301,0.00023597272,0.00024883857,0.00008882929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019194206,0.00019653808,0.00029020646,0.00017715292,0.00017738102,0.000029833387,0.00008755549,0.00007590358,0.00004562228],"category_scores_gemma":[0.000009239971,0.00020236403,0.00008352368,0.00038677792,0.00005437251,0.00012272349,0.0000019861557,0.00007432284,0.0000011842963],"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":[0.00014519971,0.00008530656,0.0000023081975,0.00024997824,0.000049421826,0.0000015066253,0.00006391732,0.9670566,0.0015464615,0.00023125722,0.0022451337,0.02832292],"study_design_scores_gemma":[0.0017238046,0.00018521507,0.000009949741,0.00004920392,0.000064134576,0.0000015022031,0.00026332887,0.5698878,0.096166365,0.00068687764,0.33069968,0.00026212065],"about_ca_topic_score_codex":0.00038991132,"about_ca_topic_score_gemma":0.00019639652,"teacher_disagreement_score":0.99442685,"about_ca_system_score_codex":0.0001360082,"about_ca_system_score_gemma":0.000048186084,"threshold_uncertainty_score":0.82521653},"labels":[],"label_agreement":null},{"id":"W4390357321","doi":"10.1109/tste.2023.3345489","title":"An Adaptive BESS Controller for Stability Enhancement of Islanded Low Voltage Microgrids","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","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":"University of New Brunswick","funders":"Indo-US Science and Technology Forum","keywords":"Voltage droop; Microgrid; Control theory (sociology); Controller (irrigation); Compensation (psychology); Voltage; Benchmark (surveying); Converters; Computer science; SIGNAL (programming language); Voltage source; Engineering; Electronic engineering; Control (management); Electrical engineering","score_opus":0.007642520159863937,"score_gpt":0.20858144608046772,"score_spread":0.20093892592060378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390357321","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":[0.022708774,0.00013444263,0.97587764,0.000019163406,0.00026537845,0.00042466962,0.00009514896,0.00028617817,0.00018858044],"genre_scores_gemma":[0.99752593,0.00023742496,0.00036609636,0.000027708309,0.00004923311,0.0004966121,0.000033048967,0.000044512304,0.0012194498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881417,0.00002981078,0.00031644962,0.00025532415,0.00013800853,0.00044625415],"domain_scores_gemma":[0.9992446,0.00010076859,0.000043210483,0.00025677506,0.00027414516,0.000080537975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020952529,0.00019697497,0.00029437296,0.0002246628,0.0001375047,0.000028346569,0.00013183159,0.00010916245,0.000100354955],"category_scores_gemma":[0.0000038155695,0.00020015704,0.00014044257,0.00042149983,0.00004049498,0.00019460282,9.566908e-7,0.00008764505,0.0000036140289],"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":[0.0004926841,0.00022844976,0.0000010517043,0.0001586731,0.00014705714,0.0000034402462,0.00029474363,0.91119003,0.060927138,0.0004048546,0.00026215534,0.025889728],"study_design_scores_gemma":[0.0017515445,0.00039849657,0.000006437605,0.000013663571,0.00004787978,4.3778843e-7,0.0013237488,0.56600565,0.42750776,0.00032502552,0.0024149376,0.00020445102],"about_ca_topic_score_codex":0.00015702649,"about_ca_topic_score_gemma":0.000083593884,"teacher_disagreement_score":0.97551155,"about_ca_system_score_codex":0.00015634547,"about_ca_system_score_gemma":0.000050579518,"threshold_uncertainty_score":0.8162167},"labels":[],"label_agreement":null},{"id":"W4400410835","doi":"10.1109/tste.2024.3424389","title":"Fault Current Limiting and Grid Code Compliance for Grid-Forming Inverters — Part II: Solution","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":9,"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 Toronto","funders":"","keywords":"Grid code; Grid; Limiting; Computer science; Code (set theory); Current (fluid); Electrical engineering; Electronic engineering; Reliability engineering; Engineering; AC power; Voltage; Set (abstract data type); Mechanical engineering; Mathematics","score_opus":0.026425664595154188,"score_gpt":0.25191821813471355,"score_spread":0.22549255353955935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400410835","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":[0.0030106027,0.0019209372,0.98987025,0.00009881546,0.0036426166,0.00031464698,0.000076147364,0.000634567,0.00043139845],"genre_scores_gemma":[0.99501204,0.0005318508,0.00021390512,0.000025981524,0.0005745678,0.0005650564,0.0000125801935,0.000062337815,0.0030016527],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881256,0.00001846655,0.00028206134,0.00029388454,0.0001318004,0.00046120715],"domain_scores_gemma":[0.9995921,0.00006329506,0.000025035573,0.00014353625,0.000080698104,0.00009528756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018141368,0.00021027804,0.00018420503,0.00021311322,0.0005412853,0.000120051685,0.00006543977,0.000105614345,0.000011373832],"category_scores_gemma":[0.000004860413,0.0002197487,0.00009731426,0.0002860631,0.000031397463,0.00041036907,0.0000019644592,0.00021950295,0.000003817053],"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":[0.000043246262,0.000056833716,9.575841e-7,0.0027136914,0.00013183137,0.000015914333,0.0007096633,0.42381012,0.0021249498,0.0022493785,0.0060691894,0.5620742],"study_design_scores_gemma":[0.00022696426,0.00008619851,0.0000018181668,0.00029913298,0.000029954936,0.000019598545,0.0004762012,0.5533886,0.0072883177,0.00013876382,0.43782634,0.00021810262],"about_ca_topic_score_codex":0.00018696433,"about_ca_topic_score_gemma":0.00015090746,"teacher_disagreement_score":0.9920015,"about_ca_system_score_codex":0.0003271001,"about_ca_system_score_gemma":0.00003753892,"threshold_uncertainty_score":0.8961092},"labels":[],"label_agreement":null},{"id":"W4400410966","doi":"10.1109/tste.2024.3424731","title":"Per-Phase Unsymmetrical Adaptive Derivative Optimized Droop for Mitigating Voltage Quality Issues of Unbalanced Islanded Microgrids","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Advanced Technology Research Council","keywords":"Voltage droop; Microgrid; Control theory (sociology); Controller (irrigation); Benchmark (surveying); Voltage; Engineering; Inverter; Voltage controller; Voltage regulation; AC power; Three-phase; Nonlinear system; Computer science; Voltage regulator; Control (management); Electrical engineering","score_opus":0.01221258132318145,"score_gpt":0.27511852235237944,"score_spread":0.262905941029198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400410966","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":[0.006745474,0.0026181012,0.98884505,0.00007983615,0.0003618237,0.0003683982,0.00015961238,0.00043352824,0.00038818875],"genre_scores_gemma":[0.9852773,0.00052671594,0.0113302935,0.000037088987,0.00010544521,0.00031244973,0.000042961037,0.00007719783,0.0022905641],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99840504,0.000061001385,0.0005169122,0.00034815917,0.00018843522,0.00048044408],"domain_scores_gemma":[0.9988883,0.00042235793,0.00005804969,0.0002166986,0.00031867457,0.00009589635],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025151737,0.00029214783,0.000461282,0.00042708393,0.00014368247,0.000087381304,0.00014201568,0.00016923298,0.000085894746],"category_scores_gemma":[0.000025588835,0.00029016385,0.00026326784,0.00083778973,0.00007198979,0.00027731698,0.0000020358505,0.00020499622,0.0000024688534],"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":[0.000514777,0.0002249867,5.513757e-7,0.00045853466,0.00043510715,0.000016984739,0.0008520112,0.90996164,0.029584419,0.004105021,0.00052134076,0.053324632],"study_design_scores_gemma":[0.0029445684,0.00037916293,0.000002304371,0.00008399644,0.00011789249,0.0000038948815,0.0023763832,0.7046474,0.28115132,0.0007468234,0.0071612773,0.0003849712],"about_ca_topic_score_codex":0.00030581557,"about_ca_topic_score_gemma":0.00001802191,"teacher_disagreement_score":0.97853184,"about_ca_system_score_codex":0.00024398915,"about_ca_system_score_gemma":0.00009263321,"threshold_uncertainty_score":0.99995506},"labels":[],"label_agreement":null},{"id":"W4400411401","doi":"10.1109/tste.2024.3424405","title":"Fault Current Limiting and Grid Code Compliance for Grid-Forming Inverters—Part I: Problem Statement","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":9,"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 Toronto","funders":"","keywords":"Grid code; Grid; Limiting; Statement (logic); Computer science; Compliance (psychology); Code (set theory); Current (fluid); Electrical engineering; Reliability engineering; Fault (geology); Engineering; Set (abstract data type); AC power; Voltage; Programming language; Mechanical engineering; Mathematics; Geology","score_opus":0.025945942096071463,"score_gpt":0.2614473228674847,"score_spread":0.23550138077141322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400411401","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":[0.0012448757,0.0017419491,0.99243563,0.00009576097,0.0025249065,0.0005407269,0.00011840636,0.00060251454,0.0006952191],"genre_scores_gemma":[0.99132127,0.0008385478,0.00072558864,0.000035505487,0.0005392127,0.0014272382,0.000018568746,0.00010011752,0.004993958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986021,0.000021318781,0.00038496635,0.000327739,0.00015967072,0.00050419575],"domain_scores_gemma":[0.99954015,0.00006819989,0.000031850428,0.00015427764,0.00009619529,0.000109353314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023464217,0.0002385577,0.00020782763,0.00021901079,0.0003208422,0.00018101395,0.000075280404,0.00008249072,0.000017084576],"category_scores_gemma":[0.000002632111,0.00023916012,0.00008845044,0.00028028933,0.000026473512,0.00040106688,0.000001906626,0.00021923552,0.000005617711],"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":[0.000041361716,0.00006496061,0.0000011730472,0.005109388,0.00017096136,0.000023543162,0.0007771487,0.5300264,0.0009903832,0.0022863715,0.0064744167,0.4540339],"study_design_scores_gemma":[0.0003030447,0.00010408036,9.59207e-7,0.00043012906,0.00003169268,0.000015887805,0.0008907335,0.3795222,0.008027437,0.00024010133,0.61017776,0.00025600975],"about_ca_topic_score_codex":0.00018413947,"about_ca_topic_score_gemma":0.00015834512,"teacher_disagreement_score":0.99171007,"about_ca_system_score_codex":0.00038963763,"about_ca_system_score_gemma":0.00004788901,"threshold_uncertainty_score":0.97526664},"labels":[],"label_agreement":null},{"id":"W4408358080","doi":"10.1109/tste.2025.3550563","title":"Energy Management of Multi-Energy Communities: A Hierarchical MIQP-Constrained Deep Reinforcement Learning Approach","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Smart Grid Energy Management","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":"University of Waterloo","funders":"","keywords":"Reinforcement learning; Energy management; Computer science; Energy (signal processing); Artificial intelligence","score_opus":0.008362335759426905,"score_gpt":0.2064536769525201,"score_spread":0.19809134119309318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408358080","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":[0.00041190695,0.00026537586,0.92188823,0.000042321695,0.00047184975,0.00013336437,0.0000026216987,0.0005276984,0.076256655],"genre_scores_gemma":[0.9546174,0.0011940799,0.002915608,0.00016039844,0.00003371501,0.0009359643,0.000040716146,0.000090755544,0.040011358],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99736345,0.00016412472,0.0007433813,0.0003911441,0.00042480972,0.0009130786],"domain_scores_gemma":[0.9986332,0.00015441104,0.00008595497,0.0008197344,0.0001522465,0.00015443724],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024455987,0.0005282567,0.0005356236,0.0011107344,0.0004293322,0.000074732445,0.000589401,0.00021190527,0.00015481716],"category_scores_gemma":[0.0000025435995,0.0005948948,0.00027484496,0.001216611,0.00020425487,0.00021645358,0.000028826209,0.0003951808,0.0000019740837],"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":[0.00007506545,0.00028162356,0.0000017305431,0.0005004643,0.00088916987,0.00003884187,0.00020422722,0.83940786,0.000052271444,0.13897943,0.00024880675,0.01932053],"study_design_scores_gemma":[0.0015210072,0.0001100287,0.0000086955315,0.00014564078,0.00019616046,0.00000503038,0.008021673,0.91999394,0.008598288,0.00038155616,0.060498323,0.0005196569],"about_ca_topic_score_codex":0.002055428,"about_ca_topic_score_gemma":0.00017807586,"teacher_disagreement_score":0.9542055,"about_ca_system_score_codex":0.0005803644,"about_ca_system_score_gemma":0.00006427984,"threshold_uncertainty_score":0.99965024},"labels":[],"label_agreement":null},{"id":"W4408441656","doi":"10.1109/tste.2025.3551495","title":"Optimal Design and Technology Selection for Electrolyzer Hydrogen Plants Considering Hydrogen Supply and Provision of Grid Services","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Grid; Hydrogen; Selection (genetic algorithm); Hydrogen production; Environmental economics; Computer science; Engineering; Business; Electrical engineering; Environmental science; Waste management; Automotive engineering; Economics; Chemistry","score_opus":0.005146618663895479,"score_gpt":0.21417618220823598,"score_spread":0.2090295635443405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408441656","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":[0.47543824,0.0010639115,0.52190506,0.00019913173,0.00017596006,0.0005704351,0.000015546726,0.00027149523,0.00036021834],"genre_scores_gemma":[0.99127525,0.00029752892,0.0026351581,0.000055443732,0.000043601845,0.0005278575,0.00001058767,0.000059060392,0.005095513],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99797237,0.000118489625,0.00048261395,0.00059822074,0.0001734056,0.00065488147],"domain_scores_gemma":[0.9989775,0.0002456377,0.00014938432,0.00028427085,0.00024445372,0.00009874554],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029207137,0.00033885808,0.0004912966,0.0010604083,0.00042580746,0.000053488548,0.00016849316,0.0003183438,0.0000137652],"category_scores_gemma":[0.00001140075,0.00034618186,0.000074699994,0.000752859,0.00012340346,0.00025872243,0.000008549842,0.0001582679,5.993419e-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":[0.00053628295,0.00013397915,0.000047031197,0.00045881976,0.0003772209,0.000015668073,0.00011499213,0.8522247,0.12362019,0.005869473,0.000077809185,0.016523805],"study_design_scores_gemma":[0.001326278,0.00044658498,0.0000021249705,0.00010963081,0.00010539563,0.00009047315,0.0009774347,0.09429767,0.8834603,0.0016018046,0.017305864,0.000276444],"about_ca_topic_score_codex":0.005139515,"about_ca_topic_score_gemma":0.0008249732,"teacher_disagreement_score":0.75984013,"about_ca_system_score_codex":0.00018230274,"about_ca_system_score_gemma":0.0002568175,"threshold_uncertainty_score":0.999899},"labels":[],"label_agreement":null},{"id":"W4408805405","doi":"10.1109/tste.2025.3550555","title":"An Iterative Cleaning Method for Abnormal Wind Power Data in Wind Farms Based on Wasserstein Distance","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Smart Grid and Power Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Key Research and Development Program of Zhejiang Province; Science and Technology Innovation 2025 Major Project of Ningbo; Zhejiang University","keywords":"Wind power; Iterative method; Wind power forecasting; Computer science; Power (physics); Meteorology; Environmental science; Marine engineering; Mathematical optimization; Electric power system; Electrical engineering; Engineering; Mathematics; Algorithm; Physics","score_opus":0.009308735629421102,"score_gpt":0.26432788821920417,"score_spread":0.2550191525897831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408805405","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":[0.004384945,0.00007448066,0.9888847,0.00009310881,0.0020322101,0.00029866365,0.00012680773,0.00017552369,0.0039295717],"genre_scores_gemma":[0.9945079,0.000006248452,0.0018065072,0.00020715279,0.00012356185,0.00007457394,0.00005683142,0.000054069907,0.0031631237],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983671,0.00011413838,0.00034286262,0.00046991158,0.0001699419,0.0005360748],"domain_scores_gemma":[0.9986476,0.00031462195,0.000033913177,0.00082950515,0.000085774074,0.00008863133],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044700864,0.0002805887,0.00030691762,0.00047585214,0.00020653228,0.00012031359,0.00039088845,0.00014759148,0.000036235666],"category_scores_gemma":[0.000009721231,0.00029003306,0.00007679498,0.0006577498,0.00002225349,0.0005253491,0.0000022633199,0.00025241173,0.0000018148011],"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":[0.00024622245,0.00014278364,0.000040685303,0.00014149584,0.00006214885,0.00003121698,0.00045309542,0.9929777,0.00034456965,0.0025824094,0.0009886472,0.0019890415],"study_design_scores_gemma":[0.0017819674,0.00031224603,0.00011031782,0.00019274314,0.000039399678,0.0000022191998,0.0047774324,0.8255169,0.015951786,0.000092957955,0.15074107,0.0004809752],"about_ca_topic_score_codex":0.00027733058,"about_ca_topic_score_gemma":0.00044071343,"teacher_disagreement_score":0.990123,"about_ca_system_score_codex":0.00032410023,"about_ca_system_score_gemma":0.000108219916,"threshold_uncertainty_score":0.9999552},"labels":[],"label_agreement":null},{"id":"W4408858231","doi":"10.1109/tste.2025.3555194","title":"Dual-Loop Geometric Control of Stator Flux for Improved LVRT Response in DFIG-Based Wind Turbine Systems","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Calgary","funders":"","keywords":"Stator; Doubly fed electric machine; Control theory (sociology); Turbine; Wind power; Loop (graph theory); Induction generator; Control system; AC power; Engineering; Computer science; Control (management); Electrical engineering; Aerospace engineering; Voltage; Mathematics","score_opus":0.006133702390655489,"score_gpt":0.22778941181603118,"score_spread":0.22165570942537569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408858231","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":[0.036846645,0.0014152766,0.95600224,0.00042906657,0.0022444192,0.0009187718,0.0001959083,0.00018531585,0.0017623623],"genre_scores_gemma":[0.88625735,0.000028543922,0.000087186985,0.00021766816,0.00007252415,0.0006875421,0.000024245379,0.00008090898,0.11254404],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962357,0.0004662802,0.0011736145,0.0007077666,0.00033396928,0.0010826119],"domain_scores_gemma":[0.9966247,0.0013778058,0.00029032058,0.0008446432,0.0006678238,0.00019472181],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011616693,0.00050104543,0.0010167414,0.0031038995,0.00027248732,0.000085935026,0.00034435897,0.0004466114,0.000079838],"category_scores_gemma":[0.00014435126,0.00047447838,0.00037108458,0.0032391727,0.000109376066,0.00022299243,0.000004088098,0.00023719332,0.000002690302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0070835785,0.00065870455,0.0000059891076,0.00052379724,0.00030607192,0.000052422445,0.000040593328,0.9598097,0.017977051,0.010093782,0.0007806492,0.00266762],"study_design_scores_gemma":[0.025140878,0.0025446971,0.000113220885,0.00055756106,0.00034141634,0.0000146087705,0.0033499843,0.20334849,0.2724176,0.0005520393,0.4902987,0.0013208138],"about_ca_topic_score_codex":0.028939681,"about_ca_topic_score_gemma":0.0011655658,"teacher_disagreement_score":0.95591503,"about_ca_system_score_codex":0.0008417858,"about_ca_system_score_gemma":0.001167148,"threshold_uncertainty_score":0.9997707},"labels":[],"label_agreement":null},{"id":"W4412972833","doi":"10.1109/tste.2025.3589982","title":"Aggregation Optimization-Based Secondary Control for DC Microgrids","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":2,"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":"Fundamental Research Funds for the Central Universities; China Scholarship Council; National Natural Science Foundation of China","keywords":"Control (management); Control theory (sociology); Computer science; Control engineering; Mathematical optimization; Engineering; Mathematics; Artificial intelligence","score_opus":0.0024656488926698052,"score_gpt":0.1828832111455844,"score_spread":0.18041756225291458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412972833","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":[0.00007757294,0.0008009804,0.99535215,0.0002591497,0.00061887625,0.0004091803,0.00005586639,0.00044767113,0.0019785454],"genre_scores_gemma":[0.9854294,0.00021025864,0.0062785223,0.00085451273,0.00007747164,0.0008216989,0.00007274723,0.00006577143,0.006189602],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892896,0.000028556582,0.0003015717,0.00024668302,0.00009337549,0.00040085617],"domain_scores_gemma":[0.99921083,0.00016399207,0.000036897898,0.00024078935,0.00028434172,0.000063130305],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011087232,0.00022681683,0.00022598937,0.00043670388,0.00029320412,0.000095109404,0.00013021308,0.00016451551,0.0001421366],"category_scores_gemma":[0.0000076114893,0.00025358747,0.00015706332,0.00049264246,0.000032615564,0.00020202757,4.690423e-7,0.00013059056,0.0000022807944],"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":[0.00012316073,0.00006827261,8.463951e-7,0.00013373986,0.00010238083,0.0000023690475,0.000014556549,0.9623809,0.0004100366,0.0008920124,0.0012311764,0.034640554],"study_design_scores_gemma":[0.002726741,0.00006305082,0.0000015650314,0.0000281265,0.000091458,7.948845e-7,0.00010030151,0.9262996,0.034324363,0.00023336442,0.035907865,0.00022281826],"about_ca_topic_score_codex":0.0000569585,"about_ca_topic_score_gemma":0.000028895736,"teacher_disagreement_score":0.98907363,"about_ca_system_score_codex":0.00025899816,"about_ca_system_score_gemma":0.00018109602,"threshold_uncertainty_score":0.99999166},"labels":[],"label_agreement":null},{"id":"W4412972838","doi":"10.1109/tste.2025.3589980","title":"Fast Frequency Response in Low Inertia Grids via Integrated Supercapacitor Energy Storage Systems and Wind Turbine Generators","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":4,"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 Power Generation; Abbotsford Veterinary Clinic; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation","keywords":"Energy storage; Wind power; Turbine; Supercapacitor; Pumped-storage hydroelectricity; Inertia; Frequency response; Electrical engineering; Automotive engineering; Engineering; Computer science; Renewable energy; Power (physics); Distributed generation; Aerospace engineering; Capacitance; Physics","score_opus":0.0036828104148312365,"score_gpt":0.18675773094885423,"score_spread":0.183074920534023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412972838","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":[0.3507002,0.008807656,0.6309491,0.00025511105,0.0071051056,0.00076323794,0.00016287324,0.00044839366,0.00080833514],"genre_scores_gemma":[0.9758221,0.0005324811,0.000067632805,0.00014226226,0.00046568486,0.0005591672,0.000028168244,0.00027044726,0.022112086],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9921906,0.0014432076,0.0020832196,0.001519247,0.000652549,0.0021111488],"domain_scores_gemma":[0.9964955,0.00062177505,0.00019842645,0.0013867539,0.0007232933,0.0005742615],"candidate_categories":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0011410674,0.001551195,0.00175455,0.0037828635,0.000613121,0.000588586,0.00065553415,0.001260345,0.00013016316],"category_scores_gemma":[0.00008193228,0.0016674823,0.00035846388,0.004279816,0.0002870554,0.001054982,0.000014114148,0.0013412873,0.000010717705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019376915,0.0004234358,0.000048615195,0.001157299,0.00070972944,0.00094978884,0.00072317215,0.9388177,0.04839465,0.003531514,0.00046854233,0.0028378842],"study_design_scores_gemma":[0.0098736705,0.0014877443,0.000359949,0.002707652,0.0005431282,0.00019555926,0.010804905,0.89124197,0.059243076,0.0003278733,0.0198991,0.003315371],"about_ca_topic_score_codex":0.03476072,"about_ca_topic_score_gemma":0.0014822165,"teacher_disagreement_score":0.6308814,"about_ca_system_score_codex":0.0049192403,"about_ca_system_score_gemma":0.0013102037,"threshold_uncertainty_score":0.9997237},"labels":[],"label_agreement":null},{"id":"W4414955876","doi":"10.1109/tste.2025.3619196","title":"Coordination of Power and Transportation Networks With Integrated Electricity-Hydrogen Stations: A Reinforcement Learning Approach Considering Delayed Reward","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University; National Natural Science Foundation of China; Queen's University Belfast","keywords":"Reinforcement learning; Markov decision process; Dynamic pricing; Markov process; Revenue; Q-learning; Traffic congestion; Process (computing); Vehicle dynamics","score_opus":0.0025627650295312054,"score_gpt":0.17813403998431046,"score_spread":0.17557127495477926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414955876","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":[0.11369052,0.00021923949,0.8847312,0.000018003851,0.000028904175,0.00016810898,0.0000020882867,0.00014114608,0.0010008122],"genre_scores_gemma":[0.99760985,0.00019301684,0.00085662364,0.000031943902,0.0000045817474,0.000075780656,0.000030401457,0.000025931313,0.0011718427],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908406,0.000029866358,0.00028975488,0.00018149982,0.00012862885,0.00028619712],"domain_scores_gemma":[0.999529,0.000054551623,0.00005652828,0.00010742961,0.00020761858,0.0000448755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000090990194,0.00017986636,0.00020353126,0.000379823,0.00017483089,0.000030137197,0.000054286593,0.00011721112,0.0000151675],"category_scores_gemma":[0.0000034047537,0.0001721445,0.00004056906,0.0010378232,0.00003559089,0.0001942749,4.0899195e-7,0.00028541463,7.2046625e-8],"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":[0.00010585171,0.000022650029,0.000023472572,0.00008169826,0.00018492911,0.0000037996022,0.0002389236,0.9893587,0.0010122476,0.003077185,0.000060167065,0.0058303517],"study_design_scores_gemma":[0.0009180823,0.00036813453,0.00008072643,0.000051939085,0.00011256862,0.0000062030103,0.0018317824,0.9638384,0.030770967,0.00025507138,0.0015336624,0.00023248952],"about_ca_topic_score_codex":0.00041170165,"about_ca_topic_score_gemma":0.00006616737,"teacher_disagreement_score":0.88391936,"about_ca_system_score_codex":0.00017680784,"about_ca_system_score_gemma":0.000080698665,"threshold_uncertainty_score":0.7019849},"labels":[],"label_agreement":null},{"id":"W4417131495","doi":"10.1109/tste.2025.3640949","title":"A Novel Framework for Centralized Remote Power Smoothing as a Prospective Ancillary Service","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Independent Electricity System Operator; York University","funders":"Independent Electricity System Operator","keywords":"Smoothing; Flywheel; Renewable energy; Grid; Electric power system; Power (physics); Wind power; Electricity generation; Automatic Generation Control","score_opus":0.006710002352494388,"score_gpt":0.2355395643465373,"score_spread":0.22882956199404292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417131495","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":[0.0017799255,0.0020300855,0.9770624,0.0022366762,0.0043399837,0.002427613,0.000113584334,0.00070953276,0.0093001975],"genre_scores_gemma":[0.9583218,0.00013871671,0.009005971,0.0017391013,0.0003238996,0.00069892977,0.0000075996786,0.0002827918,0.029481195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.994662,0.00012420413,0.0011706438,0.001257784,0.0005682125,0.0022171608],"domain_scores_gemma":[0.9959101,0.000902713,0.00022300819,0.0012242252,0.0013599193,0.0003800063],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005282168,0.0010693468,0.001209299,0.0009575837,0.0010261612,0.0004407806,0.00064600015,0.00110142,0.0002173918],"category_scores_gemma":[0.0001246903,0.0012546034,0.0007053044,0.0028905047,0.000074323594,0.00063368963,0.0000095254345,0.0011359951,0.000025521362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002453193,0.00080290204,0.0000042888573,0.0029904938,0.0027334522,0.00014276644,0.0030876736,0.78681976,0.0045896494,0.18717414,0.0006483905,0.008553321],"study_design_scores_gemma":[0.023910439,0.0014258904,0.0001352154,0.0053988933,0.0021946237,0.00015427082,0.020114899,0.37885767,0.071913004,0.08835157,0.40300757,0.004535953],"about_ca_topic_score_codex":0.0068193446,"about_ca_topic_score_gemma":0.00032503635,"teacher_disagreement_score":0.96805644,"about_ca_system_score_codex":0.0029133973,"about_ca_system_score_gemma":0.0010957173,"threshold_uncertainty_score":0.9997943},"labels":[],"label_agreement":null},{"id":"W4417439007","doi":"10.1109/tste.2025.3644854","title":"Reinforcement Learning-Based Flexible Control in MTDC System for Offshore Wind Farm Integration","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Voltage droop; Offshore wind power; Control theory (sociology); Robustness (evolution); Wind power; Initialization; Reinforcement learning; Heuristic; Electric power system","score_opus":0.00622892692756925,"score_gpt":0.22336029770163657,"score_spread":0.21713137077406733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417439007","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":[0.00063242397,0.00045106263,0.9887985,0.00015371812,0.002243201,0.0021593557,0.000019549636,0.00045588665,0.00508629],"genre_scores_gemma":[0.950478,0.000049291517,0.00008827874,0.00008604955,0.00012441682,0.0019017726,0.000022449689,0.000093496725,0.047156207],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99649364,0.00021019999,0.0012180128,0.0006743316,0.0003448537,0.0010589851],"domain_scores_gemma":[0.9984031,0.00024735386,0.00018821334,0.0004978263,0.00051987276,0.000143657],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00081680337,0.00061978877,0.0007626246,0.0015820207,0.0007084499,0.00024135601,0.0002302401,0.0006267987,0.000054462944],"category_scores_gemma":[0.000027402992,0.0006915894,0.00038532197,0.0015379459,0.000053745694,0.00030228376,0.000001725331,0.0007139966,0.000008174541],"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":[0.0009591742,0.00016840991,0.0000039018446,0.0024285782,0.00022242009,0.000017069906,0.00023362403,0.9590335,0.0016254658,0.010148302,0.000073946256,0.02508561],"study_design_scores_gemma":[0.005431805,0.00069489965,0.00000721486,0.0011350749,0.00017467325,0.0000032817136,0.0077175386,0.8634956,0.0663251,0.000065955384,0.054433882,0.0005149794],"about_ca_topic_score_codex":0.0047829067,"about_ca_topic_score_gemma":0.00076327875,"teacher_disagreement_score":0.9887102,"about_ca_system_score_codex":0.0037215422,"about_ca_system_score_gemma":0.00050811475,"threshold_uncertainty_score":0.9995535},"labels":[],"label_agreement":null},{"id":"W4417508609","doi":"10.1109/tste.2025.3646475","title":"A Simplified Probabilistic Framework for Evaluating the Contribution of Solar Photovoltaic Generation to Power Systems","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Probabilistic logic; Photovoltaic system; Reliability (semiconductor); Electric power system; Probability density function; Electricity generation; Solar power; Solar energy; Function (biology)","score_opus":0.015235393235983344,"score_gpt":0.2755887932746912,"score_spread":0.2603534000387079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417508609","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":[0.007162689,0.0005758552,0.9834602,0.00019245748,0.0045651984,0.0032679497,0.00008263447,0.00020027065,0.00049278594],"genre_scores_gemma":[0.9865044,0.00006081599,0.0024037457,0.00015215798,0.00012303522,0.0039710174,0.000046254776,0.000121429934,0.006617183],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99574566,0.00045188033,0.0015037782,0.00072718365,0.0005365858,0.0010348889],"domain_scores_gemma":[0.99422234,0.0010613189,0.00032873874,0.0009769145,0.003266876,0.00014382217],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014914606,0.0006325051,0.00077588385,0.0008190182,0.001022109,0.00032304472,0.00041485444,0.0007433338,0.00004952132],"category_scores_gemma":[0.0006035497,0.00058284705,0.00034052684,0.0023887008,0.00009053831,0.00030148134,0.0000053237845,0.00049894815,0.0000047448216],"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":[0.00038028398,0.00015669448,4.0386044e-7,0.0005023693,0.00043146516,0.0000018513937,0.000441022,0.80385387,0.025056344,0.16800216,0.00034491697,0.0008286445],"study_design_scores_gemma":[0.0008871115,0.000970163,0.0000012368978,0.000721846,0.00042783996,0.000003867033,0.0029272493,0.87592554,0.113233864,0.0017310783,0.002720037,0.00045013614],"about_ca_topic_score_codex":0.0021058398,"about_ca_topic_score_gemma":0.00022012717,"teacher_disagreement_score":0.9810564,"about_ca_system_score_codex":0.0020509374,"about_ca_system_score_gemma":0.00078206183,"threshold_uncertainty_score":0.9996623},"labels":[],"label_agreement":null}]}