{"meta":{"query_hash":"51e82e4efc67","filters":{"venue":"CSEE Journal of Power and Energy Systems"},"cohort_total":10,"direct_labels_cover":0,"predictions_cover":10,"exported":10,"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/51e82e4efc67","api":"https://metacan.xera.ac/api/v1/cohort?venue=CSEE+Journal+of+Power+and+Energy+Systems"},"results":[{"id":"W2767241943","doi":"10.17775/cseejpes.2017.0016","title":"Key techniques in real time digital simulation for closed-loop testing of HVDC systems","year":2017,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","topic":"Real-time simulation and control systems","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":"RTDS Technologies (Canada)","funders":"","keywords":"Key (lock); Loop (graph theory); Computer science; Closed loop; Electronic engineering; Control engineering; Reliability engineering; Engineering; Computer security; Mathematics","score_opus":0.014703483865838725,"score_gpt":0.24577067548064707,"score_spread":0.23106719161480835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767241943","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0019097249,0.00020983326,0.9940545,0.00006863264,0.0000415021,0.000045477802,0.00004448243,0.0007178834,0.0029079586],"genre_scores_gemma":[0.18426685,0.0015997164,0.8084972,0.0001331722,0.000075477445,0.0004137476,0.0002931327,0.00056106556,0.004159703],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990804,0.00032685933,0.000075418124,0.00008249682,0.0003877048,0.000047095644],"domain_scores_gemma":[0.9985403,0.00078666705,0.00010155918,0.0003028824,0.00023041769,0.000038194645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011253817,0.0010277854,0.00042940388,0.0006600199,0.00032672315,0.00095289556,0.0012089584,0.0006648771,0.0045152055],"category_scores_gemma":[0.003450551,0.00046362134,0.00066169054,0.000518282,0.00077532337,0.0014070066,0.00076492375,0.0017574012,0.0013419477],"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":[0.0002036383,0.00012778494,0.00081241125,0.0006307906,0.00006369046,0.00022340032,0.00037128784,0.57748944,0.04378699,0.19742066,0.0031664742,0.1757034],"study_design_scores_gemma":[0.000061685,0.00013566953,0.00015769838,0.00014169708,0.00002313856,0.00019484035,0.000030080673,0.90696174,0.026036296,0.029817028,0.036409006,0.00003105745],"about_ca_topic_score_codex":0.00084935693,"about_ca_topic_score_gemma":0.00056056003,"teacher_disagreement_score":0.0045152055,"about_ca_system_score_codex":0.00056149345,"about_ca_system_score_gemma":0.000590595,"threshold_uncertainty_score":0.01510483},"labels":[],"label_agreement":null},{"id":"W2883201518","doi":"10.17775/cseejpes.2016.01550","title":"A harmonic compensation approach for interlinking voltage source converters in hybrid AC-DC microgrids with low switching frequency","year":2018,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","topic":"Microgrid Control and Optimization","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 Alberta","funders":"","keywords":"Converters; Compensation (psychology); Harmonic; Electrical engineering; Voltage; Electronic engineering; Computer science; Engineering; Physics; Acoustics","score_opus":0.004383786575930513,"score_gpt":0.17399346375983563,"score_spread":0.1696096771839051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883201518","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033104733,0.00042343934,0.9597301,0.00005886635,0.00004486643,0.00005566613,0.000016656844,0.00047305154,0.006092571],"genre_scores_gemma":[0.9176417,0.00022250606,0.07859944,0.000042449992,0.000032717646,0.000057064342,0.000026343223,0.000020319128,0.003357395],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999101,0.000016303227,0.000005998057,0.00002384999,0.000034719276,0.000009052652],"domain_scores_gemma":[0.9999609,0.000006915479,0.000008223032,0.0000061165874,0.000014677297,0.000003204681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001094038,0.00048027709,0.0003051496,0.00032804185,0.00031751848,0.00042334202,0.0005080066,0.0003133615,0.0019396704],"category_scores_gemma":[0.00012633885,0.00010503441,0.00022679822,0.00027666442,0.00018002234,0.00035513664,0.00024527663,0.0002958248,0.0002844287],"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":[0.00028290856,0.00017835581,0.00085249374,0.00040855145,0.0000882193,0.00031099666,0.00022277834,0.19645189,0.20368029,0.023157535,0.0016991122,0.5726668],"study_design_scores_gemma":[0.00003286912,0.00032929485,0.00055825256,0.000021216636,0.000045530618,0.0001916353,0.000048896814,0.9595654,0.029415935,0.0038173343,0.0059527657,0.000020759415],"about_ca_topic_score_codex":0.0010726542,"about_ca_topic_score_gemma":0.0014036127,"teacher_disagreement_score":0.0019396704,"about_ca_system_score_codex":0.00022191413,"about_ca_system_score_gemma":0.00021519755,"threshold_uncertainty_score":0.0064889193},"labels":[],"label_agreement":null},{"id":"W2883374508","doi":"10.17775/cseejpes.2017.01260","title":"Bi-level planning for integrated energy systems incorporating demand response and energy storage under uncertain environments using novel metamodel","year":2018,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":121,"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 Victoria","funders":"","keywords":"Sizing; Renewable energy; Energy storage; Demand response; Electric power system; Distributed generation; Computer science; Energy supply; Energy planning; Mathematical optimization; Energy (signal processing); Reliability engineering; Power (physics); Engineering; Electrical engineering; Electricity","score_opus":0.030915892714661115,"score_gpt":0.2395908221539412,"score_spread":0.2086749294392801,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883374508","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011150534,0.00014631257,0.9837775,0.00009564787,0.000018898054,0.00004472284,0.00010952663,0.00019344929,0.004463381],"genre_scores_gemma":[0.69801724,0.0004454319,0.29682162,0.00008450205,0.000020500695,0.00038534473,0.00036742614,0.00011034469,0.0037475682],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969697,0.00008853715,0.000015232793,0.00005819535,0.00009795094,0.000043069675],"domain_scores_gemma":[0.99977154,0.000103796316,0.000037355734,0.000024723195,0.00004620227,0.000016392933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068646576,0.00070289953,0.0006912786,0.0005116713,0.00040448728,0.0011530081,0.0007935979,0.0007521549,0.0019598308],"category_scores_gemma":[0.0007529412,0.0004951561,0.0012561788,0.00060238055,0.0005630192,0.0008140194,0.00084248214,0.0008582972,0.00023047376],"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":[0.000008528035,0.0000063745947,0.00011276569,0.000016113803,0.000007906799,0.000020737569,0.000011294171,0.9906126,0.0005697005,0.0058023008,0.000079829806,0.0027518168],"study_design_scores_gemma":[0.0000024910046,0.0000069702364,0.000029381441,0.0000027625233,0.0000031656934,0.0000036399433,0.0000038113697,0.99750453,0.00013717504,0.0019862663,0.00031792477,0.0000018740003],"about_ca_topic_score_codex":0.007870967,"about_ca_topic_score_gemma":0.008317638,"teacher_disagreement_score":0.007870967,"about_ca_system_score_codex":0.0009923422,"about_ca_system_score_gemma":0.0016043923,"threshold_uncertainty_score":0.015650332},"labels":[],"label_agreement":null},{"id":"W2883924988","doi":"10.17775/cseejpes.2017.00510","title":"Introduction of damping, synchronizing and inertial effects using controlled power injection devices","year":2017,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","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":"University of Manitoba","funders":"Indian Institute of Technology Bombay","keywords":"Synchronizing; Inertial frame of reference; Control theory (sociology); Power (physics); Renewable energy; Grid; Electric power system; Control engineering; Computer science; Engineering; Control (management); Topology (electrical circuits); Physics; Electrical engineering; Mathematics; Classical mechanics","score_opus":0.004255827720790439,"score_gpt":0.19686005216590644,"score_spread":0.192604224445116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883924988","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014531528,0.0024850923,0.94906425,0.00029182422,0.000266248,0.00007241089,0.000033984223,0.00015840052,0.03309625],"genre_scores_gemma":[0.8875354,0.0057534007,0.09325433,0.00023490457,0.00042792296,0.00018979044,0.00004296623,0.00007140788,0.012489734],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977857,0.000057246343,0.000015432423,0.000053719836,0.00007833129,0.000016815393],"domain_scores_gemma":[0.9996062,0.00023911979,0.000049608447,0.000049070437,0.000046242098,0.000009882537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003027294,0.00078212563,0.000512852,0.0004098864,0.00030087386,0.0009313612,0.000608071,0.00071334717,0.0030438316],"category_scores_gemma":[0.0010445302,0.00031206434,0.0006485262,0.00022165064,0.0013265738,0.001273671,0.0006231697,0.0009112343,0.00023132884],"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":[0.00006706526,0.000091616654,0.00045407304,0.000635557,0.000057349844,0.00042949236,0.00037626893,0.1728884,0.024128389,0.7407495,0.0010134006,0.059108853],"study_design_scores_gemma":[0.000050989525,0.0004872153,0.0006468518,0.00019735351,0.00008670865,0.00051533146,0.000086072614,0.79581404,0.013865781,0.15473005,0.033456728,0.00006285088],"about_ca_topic_score_codex":0.0006539243,"about_ca_topic_score_gemma":0.0004121957,"teacher_disagreement_score":0.0030438316,"about_ca_system_score_codex":0.0003149597,"about_ca_system_score_gemma":0.00026550557,"threshold_uncertainty_score":0.010182619},"labels":[],"label_agreement":null},{"id":"W2883995124","doi":"10.17775/cseejpes.2018.00500","title":"A demand response system for wind power integration: greenhouse gas mitigation and reduction of generator cycling","year":2018,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":21,"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 Victoria","funders":"","keywords":"Cycling; Greenhouse gas; Reduction (mathematics); Environmental science; Generator (circuit theory); Automotive engineering; Wind power; Power (physics); Electrical engineering; Engineering; Geology; Mathematics; Physics","score_opus":0.0073681934478022305,"score_gpt":0.20521633223563593,"score_spread":0.1978481387878337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883995124","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8775909,0.00019056739,0.10479865,0.00068420824,0.00008347127,0.00023943822,0.00034443248,0.00060621713,0.015462119],"genre_scores_gemma":[0.99480516,0.000035103116,0.003996349,0.000026426156,0.00000386256,0.00003125836,0.00005357468,0.000011014254,0.001037138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998274,0.000078494246,0.000007280452,0.0000277344,0.000027458642,0.000031643245],"domain_scores_gemma":[0.9996625,0.00018045494,0.000046623765,0.000017821152,0.000045538603,0.000047076188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004780238,0.00059181213,0.00057668897,0.0002471313,0.00036368577,0.0007164641,0.0006572827,0.000853745,0.00323374],"category_scores_gemma":[0.0006797292,0.00027154604,0.00036688114,0.00025237072,0.0002904426,0.0007400249,0.0007237849,0.00063722406,0.00025636575],"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":[0.0003493439,0.0002367978,0.001668317,0.000067843255,0.000035864017,0.0002824447,0.00004500501,0.983557,0.0035097487,0.002146818,0.00058999815,0.0075109173],"study_design_scores_gemma":[0.00005889615,0.00014854678,0.00042807386,0.000002468491,0.000010790524,0.000019467712,0.000027466733,0.99778986,0.0005062294,0.0006260074,0.00037603723,0.000006218167],"about_ca_topic_score_codex":0.005154679,"about_ca_topic_score_gemma":0.0059423284,"teacher_disagreement_score":0.005154679,"about_ca_system_score_codex":0.0006209941,"about_ca_system_score_gemma":0.0005106932,"threshold_uncertainty_score":0.010817885},"labels":[],"label_agreement":null},{"id":"W2884724231","doi":"10.17775/cseejpes.2016.00970","title":"Wind power forecasting using wavelet transforms and neural networks with tapped delay","year":2018,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Wavelet; Artificial neural network; Wavelet transform; Wind power; Power (physics); Computer science; Electrical engineering; Electronic engineering; Environmental science; Engineering; Artificial intelligence; Physics","score_opus":0.012229016742131437,"score_gpt":0.193312828189157,"score_spread":0.18108381144702554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884724231","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14860044,0.001110123,0.8461327,0.00025204927,0.00016177478,0.000034704284,0.00013980946,0.0005065039,0.0030619272],"genre_scores_gemma":[0.91030777,0.0010209833,0.08656384,0.00004241288,0.000072239825,0.000034906556,0.00020263271,0.000032099546,0.0017230336],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998115,0.000048680093,0.00001963085,0.00004169336,0.000059325503,0.000019146515],"domain_scores_gemma":[0.9997019,0.00015999323,0.00003875837,0.000027955879,0.0000621493,0.000009217305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054416945,0.00057829067,0.00038072694,0.0004086876,0.00014835192,0.0006404784,0.00053764525,0.00040253435,0.0006376092],"category_scores_gemma":[0.0017038228,0.00020187077,0.00044048135,0.0007276065,0.00020288983,0.0013759735,0.00035563775,0.0007067029,0.00020958894],"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":[0.0001508976,0.00008823731,0.002458296,0.000087346576,0.000075353055,0.00009629056,0.000035207166,0.8000787,0.005340398,0.0035758752,0.00049904315,0.18751432],"study_design_scores_gemma":[0.0000017947589,0.00001782941,0.00016787248,0.00000198603,0.000004539785,0.0000050892036,0.000002643905,0.9987293,0.0005650593,0.0004064977,0.00009517551,0.0000021933465],"about_ca_topic_score_codex":0.0043478613,"about_ca_topic_score_gemma":0.003748525,"teacher_disagreement_score":0.0043478613,"about_ca_system_score_codex":0.00028930287,"about_ca_system_score_gemma":0.00025157962,"threshold_uncertainty_score":0.008645117},"labels":[],"label_agreement":null},{"id":"W3136419918","doi":"10.17775/cseejpes.2020.00900","title":"Modelling and analysis of PV configurations (alternate TCT-BL, total cross tied, series, series parallel, bridge linked and honey comb) to extract maximum power under partial shading conditions","year":2020,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","topic":"Photovoltaic System Optimization Techniques","field":"Energy","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Series (stratigraphy); Shading; Series and parallel circuits; Mathematics; Power (physics); Computer science; Physics; Biology; Computer graphics (images); Thermodynamics","score_opus":0.02834505545176791,"score_gpt":0.2684696072308472,"score_spread":0.24012455177907926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136419918","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58353335,0.0012157081,0.362596,0.00028750507,0.00006627936,0.00011178239,0.00059030176,0.00042733265,0.05117171],"genre_scores_gemma":[0.9851071,0.00034984478,0.0111467885,0.000014263262,0.000007675858,0.000058514346,0.00013848742,0.00003258137,0.0031447138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998975,0.000022539813,0.000003549402,0.000016952801,0.000045435852,0.000014016366],"domain_scores_gemma":[0.9998976,0.00003757197,0.000019410645,0.0000127389685,0.000027579907,0.0000051156157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011340338,0.00032184712,0.00028347145,0.0003190451,0.00018030389,0.00048496737,0.00046798287,0.00050573994,0.0013808964],"category_scores_gemma":[0.0002823529,0.00018369943,0.00062689406,0.00042482183,0.0002160289,0.00046598152,0.0001834717,0.0002480543,0.00023933336],"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":[0.000024261013,0.000022159596,0.0013724734,0.00008818393,0.000022027572,0.00014088782,0.000043468346,0.9730356,0.015260892,0.002051001,0.00039140022,0.00754765],"study_design_scores_gemma":[0.0000032507414,0.000034736866,0.000807274,0.000005996823,0.000007681378,0.000045626406,0.00001827476,0.9960395,0.0017804664,0.0006188675,0.0006335931,0.0000046663904],"about_ca_topic_score_codex":0.002099735,"about_ca_topic_score_gemma":0.00254232,"teacher_disagreement_score":0.002099735,"about_ca_system_score_codex":0.0003183053,"about_ca_system_score_gemma":0.00025252285,"threshold_uncertainty_score":0.004619539},"labels":[],"label_agreement":null},{"id":"W4400962172","doi":"10.17775/cseejpes.2023.06900","title":"Resilient Smart Power Grid Synchronization Estimation Method for System Resilience with Partial Missing Measurements","year":2024,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Resilience (materials science); Synchronization (alternating current); Power grid; Smart grid; Time synchronization; Computer science; Estimation; Power (physics); Reliability engineering; Real-time computing; Electrical engineering; Engineering; Telecommunications; Materials science","score_opus":0.010323952282713524,"score_gpt":0.23875754522968484,"score_spread":0.22843359294697133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400962172","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075167823,0.0001315301,0.99128234,0.000060465863,0.00003366048,0.00001667011,0.000018587665,0.00028596734,0.0006540391],"genre_scores_gemma":[0.8512062,0.00043249,0.14487611,0.000108159526,0.00008146181,0.00010659383,0.00017411762,0.00006578796,0.0029490641],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999551,0.00007312388,0.000035532972,0.00015080738,0.00014166921,0.000047843034],"domain_scores_gemma":[0.99960107,0.00013764201,0.00007754165,0.00004905115,0.00011763157,0.000017100665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000598719,0.00065172673,0.00061886705,0.0004957164,0.00043695397,0.0004915321,0.00065211416,0.00042974006,0.0017049456],"category_scores_gemma":[0.002084945,0.00027784283,0.00062172336,0.0005135975,0.00035300554,0.001309133,0.00063344295,0.00081647234,0.0002793574],"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":[0.00028025295,0.000045670717,0.0023063952,0.00017072061,0.00008878519,0.00017282265,0.0002987045,0.657439,0.013474524,0.017961385,0.0023290378,0.30543265],"study_design_scores_gemma":[0.0000111451445,0.000038504044,0.000305165,0.0000078160765,0.000014044058,0.000052694282,0.000014784305,0.9947667,0.0019582803,0.002013345,0.0008068989,0.000010663897],"about_ca_topic_score_codex":0.004789304,"about_ca_topic_score_gemma":0.0030549746,"teacher_disagreement_score":0.004789304,"about_ca_system_score_codex":0.00041579173,"about_ca_system_score_gemma":0.0008321556,"threshold_uncertainty_score":0.009522855},"labels":[],"label_agreement":null},{"id":"W4404363032","doi":"10.17775/cseejpes.2022.05800","title":"Recycling of Silicone Rubber from Composite Insulator with Pyrolysis Method","year":2024,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","topic":"Fiber-reinforced polymer composites","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":"Université du Québec à Chicoutimi","funders":"National Natural Science Foundation of China","keywords":"Silicone rubber; Composite number; Insulator (electricity); Materials science; Composite material; Pyrolysis; Silicone; Natural rubber; Process engineering; Waste management; Engineering","score_opus":0.004129353098528505,"score_gpt":0.1997806119491641,"score_spread":0.1956512588506356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404363032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9526709,0.0022980985,0.041000936,0.00009042615,0.00006398734,0.000056729397,0.00011970062,0.00030030435,0.003398989],"genre_scores_gemma":[0.9742828,0.0009396281,0.022474332,0.000036359786,0.000011297279,0.00001881321,0.00007673327,0.000036683174,0.0021234797],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998554,0.000014148461,0.000009114292,0.00003473917,0.00006097821,0.000025652509],"domain_scores_gemma":[0.99994254,0.000009190476,0.000018261537,0.000010797905,0.000013894314,0.0000052337946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013691201,0.00034612208,0.0002153519,0.00046060875,0.0001949246,0.00014092984,0.00019280553,0.00024924846,0.0007883917],"category_scores_gemma":[0.00014503016,0.0001687845,0.00047288463,0.0002915407,0.00016281292,0.0003650777,0.00019870549,0.00032408623,0.00028007315],"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":[0.000056954254,0.000015013842,0.00023764165,0.00012325875,0.0000066101584,0.000108399974,0.000023635637,0.00021988216,0.99322236,0.000092359434,0.000047912883,0.0058460366],"study_design_scores_gemma":[0.0000046355217,0.00009485082,0.00077119016,0.0000048785055,0.000011268599,0.00027361084,0.00001497194,0.0009844204,0.9967698,0.000024362145,0.0010384101,0.000007694036],"about_ca_topic_score_codex":0.0002757338,"about_ca_topic_score_gemma":0.00072004605,"teacher_disagreement_score":0.0007883917,"about_ca_system_score_codex":0.00012591828,"about_ca_system_score_gemma":0.00017010403,"threshold_uncertainty_score":0.002637446},"labels":[],"label_agreement":null},{"id":"W4407925963","doi":"10.17775/cseejpes.2022.07380","title":"Improving Power Response of Single-Controllable VSG-Based Active Distribution Network","year":2025,"lang":"en","type":"article","venue":"CSEE Journal of Power and Energy Systems","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":"University of Victoria","funders":"","keywords":"Power (physics); Distribution (mathematics); Computer science; Engineering; Electronic engineering; Control theory (sociology); Mathematics; Physics","score_opus":0.005381599320822493,"score_gpt":0.20194650739519923,"score_spread":0.19656490807437674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407925963","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12828916,0.0004005448,0.8573964,0.00019551514,0.00007071675,0.00005458905,0.00006860498,0.0007177354,0.012806749],"genre_scores_gemma":[0.9925575,0.000101922604,0.006333222,0.000013578772,0.000009020499,0.000015523707,0.000019176898,0.000012973832,0.00093705725],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982685,0.00005482539,0.000006562838,0.000041396175,0.00005336397,0.000016985392],"domain_scores_gemma":[0.9998167,0.00009275177,0.00003649548,0.000013498488,0.00003328572,0.0000072779726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002897669,0.00047958834,0.00030749995,0.00018196675,0.000222764,0.00046799405,0.00043348086,0.00033572118,0.001211213],"category_scores_gemma":[0.0005052699,0.0001338234,0.00016062758,0.00024742977,0.00022699618,0.0003176281,0.00025618126,0.00029215505,0.00017526095],"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":[0.00014340617,0.000033683744,0.00058116124,0.00013038603,0.000021540578,0.000096385746,0.00009202965,0.9271733,0.016308533,0.0032955923,0.00097372517,0.051150303],"study_design_scores_gemma":[0.000003854793,0.000024389006,0.000080851496,0.0000023322975,0.0000030576448,0.000010147603,0.000007096096,0.99812204,0.0010458367,0.0004330757,0.00026566826,0.0000015366537],"about_ca_topic_score_codex":0.001940375,"about_ca_topic_score_gemma":0.0022077218,"teacher_disagreement_score":0.001940375,"about_ca_system_score_codex":0.00037598927,"about_ca_system_score_gemma":0.00018866212,"threshold_uncertainty_score":0.0040519834},"labels":[],"label_agreement":null}]}