{"meta":{"query_hash":"fdb946dc9080","filters":{"venue":"Journal of Modern Power Systems and Clean Energy"},"cohort_total":37,"direct_labels_cover":0,"predictions_cover":37,"exported":37,"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/fdb946dc9080","api":"https://metacan.xera.ac/api/v1/cohort?venue=Journal+of+Modern+Power+Systems+and+Clean+Energy"},"results":[{"id":"W2024640482","doi":"10.1007/s40565-014-0063-1","title":"Overview of control, integration and energy management of microgrids","year":2014,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":143,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Microgrid; Interfacing; Smart grid; Renewable energy; Grid; Distributed generation; Energy management; Interface (matter); Engineering; Systems engineering; Power electronics; Key (lock); Control (management); Control engineering; Computer science; Energy (signal processing); Electrical engineering","score_opus":0.005757653224791547,"score_gpt":0.18412454750918097,"score_spread":0.17836689428438943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024640482","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058920914,0.5153636,0.3792321,0.0017869822,0.0018372977,0.0003650472,0.00050096127,0.0015582655,0.09346374],"genre_scores_gemma":[0.12553808,0.5986908,0.2212293,0.0011809432,0.004113062,0.00046559205,0.0016779706,0.0002207669,0.04688348],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99963486,0.000046204634,0.000049746886,0.000071388764,0.00016989559,0.000027909335],"domain_scores_gemma":[0.9998548,0.000029507035,0.000018330598,0.000015086896,0.00006785444,0.000014364762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035289265,0.00078427873,0.0006789422,0.0009408067,0.00033130072,0.0016409126,0.00075315224,0.0009156361,0.003420761],"category_scores_gemma":[0.0002833296,0.00038852048,0.00042467,0.0014077277,0.0002554537,0.0012312821,0.00057454733,0.0008148926,0.0017004302],"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":[0.0000984724,0.00012743472,0.0005900529,0.0045173476,0.00010224112,0.0002673864,0.0001650531,0.04564432,0.011612234,0.08385857,0.026016787,0.8270002],"study_design_scores_gemma":[0.000020794354,0.00028756328,0.0014547677,0.0011006226,0.00008415724,0.000637526,0.00009815164,0.05245058,0.003387364,0.032331664,0.90808874,0.00005796257],"about_ca_topic_score_codex":0.001879969,"about_ca_topic_score_gemma":0.0013438783,"teacher_disagreement_score":0.003420761,"about_ca_system_score_codex":0.00053243834,"about_ca_system_score_gemma":0.0007445485,"threshold_uncertainty_score":0.011443615},"labels":[],"label_agreement":null},{"id":"W2067997433","doi":"10.1007/s40565-015-0112-4","title":"Multi-agents modelling of EV purchase willingness based on questionnaires","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council; State Grid Corporation of China; National Natural Science Foundation of China","keywords":"Computer science; Operations research; Business; Engineering","score_opus":0.043021938708993755,"score_gpt":0.2495337327964161,"score_spread":0.20651179408742235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067997433","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":[0.496754,0.00018209958,0.49038085,0.00074608834,0.00006517849,0.00025574517,0.00024848295,0.00013907436,0.011228408],"genre_scores_gemma":[0.97528875,0.00008955095,0.019787796,0.000038884005,0.000013129068,0.00023445406,0.000051867326,0.000011781241,0.00448374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999373,0.0003724814,0.000027240576,0.000097941534,0.00006177677,0.00006749453],"domain_scores_gemma":[0.9966492,0.0026137754,0.0002854594,0.0001140445,0.00024127822,0.00009617038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021183286,0.0005284736,0.00069711637,0.00043691523,0.00038299413,0.0012776405,0.0015784175,0.0013080275,0.003531452],"category_scores_gemma":[0.005421207,0.00045590592,0.00092610327,0.00045272434,0.00077275647,0.0013339199,0.0007365858,0.0008943774,0.00029024662],"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":[0.00009536649,0.00008357246,0.0020496831,0.00003086109,0.000026590355,0.00014664528,0.00017821224,0.964937,0.0006029003,0.029257314,0.0001526371,0.0024392388],"study_design_scores_gemma":[0.000008043562,0.000016474753,0.00016487979,0.0000016852537,0.0000032912633,0.0000055775295,0.000017238048,0.9978204,0.000044568627,0.0018487979,0.000065571585,0.0000035481244],"about_ca_topic_score_codex":0.0083514415,"about_ca_topic_score_gemma":0.003426406,"teacher_disagreement_score":0.0083514415,"about_ca_system_score_codex":0.00083972514,"about_ca_system_score_gemma":0.00070527685,"threshold_uncertainty_score":0.016605675},"labels":[],"label_agreement":null},{"id":"W2081227144","doi":"10.1007/s40565-014-0079-6","title":"Frequency regulation by fuzzy and binary control in a hybrid islanded microgrid","year":2014,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Microgrid Control and Optimization","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 Calgary","funders":"","keywords":"Microgrid; Diesel generator; Automatic frequency control; Frequency regulation; Controller (irrigation); Control theory (sociology); Control engineering; Engineering; Generator (circuit theory); Automatic Generation Control; Fuzzy logic; Control (management); Renewable energy; Wind power; Computer science; Power (physics); Electric power system; Diesel fuel; Automotive engineering; Electrical engineering","score_opus":0.0021001837622565325,"score_gpt":0.15367674231262538,"score_spread":0.15157655855036883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081227144","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":[0.3716444,0.0003625614,0.6167975,0.0001612852,0.00006873671,0.0000601399,0.00006037436,0.0004885935,0.010356533],"genre_scores_gemma":[0.9904084,0.00003531308,0.00876514,0.000010309961,0.0000047238914,0.000015638674,0.000009414411,0.0000040485234,0.00074703956],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99988043,0.000023690423,0.000009939567,0.000033591914,0.000036195204,0.00001608958],"domain_scores_gemma":[0.9998379,0.000053725067,0.00003471677,0.000017488948,0.000045053406,0.0000111775225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026119355,0.00028243795,0.0002937462,0.00022819142,0.00029024744,0.0005790041,0.00038233184,0.00026760093,0.0008039901],"category_scores_gemma":[0.00040315243,0.0001227751,0.0001909932,0.0001787617,0.00033648525,0.00032663843,0.00028909196,0.0002387638,0.000104642124],"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":[0.0005158873,0.0001406031,0.0016059516,0.00015311365,0.000070236245,0.00028102886,0.00025629462,0.851855,0.04230596,0.010419864,0.0006888042,0.09170733],"study_design_scores_gemma":[0.000017190801,0.00007364984,0.00039324514,0.000005434792,0.000012110718,0.000023283676,0.000017129385,0.99554586,0.0021825181,0.0013783227,0.00034536686,0.0000058924784],"about_ca_topic_score_codex":0.0043834895,"about_ca_topic_score_gemma":0.003536278,"teacher_disagreement_score":0.0043834895,"about_ca_system_score_codex":0.0003005427,"about_ca_system_score_gemma":0.00023220257,"threshold_uncertainty_score":0.008715987},"labels":[],"label_agreement":null},{"id":"W2286133046","doi":"10.1007/s40565-016-0193-8","title":"Frequency aware robust economic dispatch","year":2016,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Electric Power System 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 Alberta","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Robust optimization; Mathematical optimization; Economic dispatch; Exploit; Bilinear interpolation; Computer science; Affine transformation; Optimization problem; Complementarity (molecular biology); Robustness (evolution); Electric power system; Mathematics","score_opus":0.0059508518811549555,"score_gpt":0.17252370282814086,"score_spread":0.1665728509469859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2286133046","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":[0.005084741,0.00013932481,0.9887067,0.00008481862,0.000043375843,0.000017906175,0.000044021195,0.00010622447,0.005772968],"genre_scores_gemma":[0.8330527,0.0004629767,0.15948816,0.00009554,0.00014297747,0.00009920719,0.00021385675,0.00014797793,0.006296609],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937254,0.00019427678,0.000029971307,0.00010987876,0.00021955694,0.0000736846],"domain_scores_gemma":[0.9995302,0.0002142541,0.00008760144,0.00006012513,0.00008484746,0.000022979872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008793037,0.0009925762,0.0012132133,0.00052609807,0.00032013954,0.0013235637,0.00108213,0.0008032879,0.0025588423],"category_scores_gemma":[0.00165431,0.00034314964,0.0007453582,0.00048160728,0.00048011486,0.0014253489,0.0010833348,0.000909685,0.00038053768],"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":[0.00003142263,0.000013138486,0.00009892734,0.00003044738,0.000022902108,0.0000560673,0.000012724667,0.94588643,0.0010943728,0.034027204,0.0005531491,0.0181732],"study_design_scores_gemma":[0.0000031840152,0.000007683622,0.000028787588,0.0000018264916,0.0000034697068,0.000009581255,0.0000026481737,0.99234504,0.00023446088,0.0066884086,0.00067060336,0.0000043679083],"about_ca_topic_score_codex":0.0010620336,"about_ca_topic_score_gemma":0.00084308285,"teacher_disagreement_score":0.0025588423,"about_ca_system_score_codex":0.00066697114,"about_ca_system_score_gemma":0.00068506063,"threshold_uncertainty_score":0.00856024},"labels":[],"label_agreement":null},{"id":"W2564616218","doi":"10.1007/s40565-016-0255-y","title":"Hierarchical and distributed demand response control strategy for thermostatically controlled appliances in smart grid","year":2016,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Engineering and Physical Sciences Research Council; State Grid Corporation of China; National Natural Science Foundation of China","keywords":"Demand response; Control (management); Smart grid; Frequency regulation; Renewable energy; Grid; Computer science; Feature (linguistics); Power (physics); Engineering; Control engineering; Electric power system; Electricity; Artificial intelligence","score_opus":0.00854508436138541,"score_gpt":0.21100375311103275,"score_spread":0.20245866874964735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2564616218","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":[0.1350603,0.0003626844,0.851104,0.00028695268,0.000096115735,0.00013780067,0.000051701376,0.0008802211,0.012020135],"genre_scores_gemma":[0.9903352,0.000043107615,0.008578928,0.000030416893,0.000011356949,0.000031917032,0.000020189378,0.0000069480593,0.00094185333],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996418,0.00005022967,0.000023981787,0.00011684006,0.000104424194,0.00006280243],"domain_scores_gemma":[0.99979025,0.00003920824,0.00005296099,0.000019529618,0.000076376935,0.000021759994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003632376,0.0005598422,0.00044160953,0.00026532516,0.000494902,0.0005933136,0.00080784684,0.0003866249,0.0012233858],"category_scores_gemma":[0.00034402474,0.00018818119,0.00031584586,0.00029247944,0.00036544315,0.00053260487,0.0005273296,0.0003537415,0.00019736879],"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":[0.00035257085,0.0002991146,0.0012855125,0.00018372673,0.00005145351,0.00026886433,0.0003669828,0.842979,0.033358075,0.014452903,0.002728735,0.103673026],"study_design_scores_gemma":[0.000023122147,0.00009010757,0.0003221698,0.0000030961735,0.0000093674935,0.000021666609,0.000022961778,0.99599236,0.0017552715,0.0013035142,0.00044739066,0.000008993444],"about_ca_topic_score_codex":0.006137106,"about_ca_topic_score_gemma":0.006884951,"teacher_disagreement_score":0.006137106,"about_ca_system_score_codex":0.00068264146,"about_ca_system_score_gemma":0.00055326015,"threshold_uncertainty_score":0.01220274},"labels":[],"label_agreement":null},{"id":"W2729846375","doi":"10.1007/s40565-017-0301-4","title":"Application of new directional logic to improve DC side fault discrimination for high resistance faults in HVDC grids","year":2017,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"HVDC Systems and Fault Protection","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 Manitoba","funders":"","keywords":"Circuit breaker; Transient (computer programming); Relay; Fault (geology); Inductor; Modular design; Grid; Engineering; Electrical engineering; Transmission line; Electronic engineering; Fault current limiter; Line (geometry); Voltage; Transient voltage suppressor; Sensitivity (control systems); Current limiting; Computer science; Electric power system; Power (physics)","score_opus":0.011089673276262492,"score_gpt":0.23909091583137146,"score_spread":0.22800124255510898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2729846375","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":[0.15413375,0.00044679904,0.83838457,0.0001130649,0.000058203925,0.00010938662,0.00005018244,0.0014820623,0.0052220137],"genre_scores_gemma":[0.89498484,0.00016974205,0.103575185,0.00005920149,0.000025694198,0.00002095324,0.000039295126,0.000034224006,0.00109081],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979967,0.000039487495,0.000019799041,0.00005065761,0.00007394506,0.000016496148],"domain_scores_gemma":[0.99946517,0.0001375943,0.00014958355,0.00010592334,0.00011821563,0.000023586057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023774858,0.00045642836,0.00019129027,0.00042878027,0.00015980065,0.0005594802,0.0005417962,0.00024269636,0.0010417884],"category_scores_gemma":[0.00068497675,0.00011748731,0.00014534124,0.00021255045,0.0002446374,0.00070027716,0.00025911254,0.00028228696,0.00024541252],"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":[0.000675281,0.00014506685,0.0031304318,0.0003191778,0.000027109434,0.00033415048,0.00020319922,0.026688889,0.6039345,0.010342708,0.0007670568,0.35343233],"study_design_scores_gemma":[0.00013624915,0.002173948,0.004218269,0.000054685235,0.000110156245,0.0016082063,0.00010454418,0.36983737,0.5973178,0.005055976,0.01931943,0.000063365726],"about_ca_topic_score_codex":0.00019309217,"about_ca_topic_score_gemma":0.00039911512,"teacher_disagreement_score":0.0010417884,"about_ca_system_score_codex":0.00021089432,"about_ca_system_score_gemma":0.00015658946,"threshold_uncertainty_score":0.0034851432},"labels":[],"label_agreement":null},{"id":"W2920411562","doi":"10.1007/s40565-019-0501-1","title":"Sizing battery storage for islanded microgrid systems to enhance robustness against attacks on energy sources","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":32,"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":"State Grid Corporation of China","keywords":"Microgrid; Robustness (evolution); Sizing; Reliability engineering; Computer science; Energy storage; Electric power system; Battery (electricity); Engineering; Operations research; Power (physics); Voltage; Electrical engineering","score_opus":0.004578664914302578,"score_gpt":0.19358148789517518,"score_spread":0.1890028229808726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2920411562","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":[0.14477775,0.00040705994,0.84898037,0.00017892668,0.000036377376,0.00012173971,0.0000586209,0.00062950514,0.0048095942],"genre_scores_gemma":[0.97540796,0.00010215588,0.023801545,0.000016407941,0.000008811331,0.000032968786,0.00002503853,0.000019684385,0.00058547297],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999087,0.000025494563,0.0000084282165,0.00002135431,0.000021920165,0.000014056843],"domain_scores_gemma":[0.9997869,0.00008771582,0.00005587507,0.000018389723,0.000038838487,0.000012270426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035147546,0.0006334649,0.00054748973,0.00032993563,0.00024091998,0.0006537255,0.00055607856,0.00031401828,0.0010543118],"category_scores_gemma":[0.0007659493,0.0002131644,0.00026307523,0.00019482819,0.00028915232,0.00059896015,0.0005369162,0.00036499454,0.000188101],"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":[0.00011664454,0.000037111386,0.00092016876,0.00013190988,0.000041660445,0.000077104756,0.00011069138,0.9140305,0.015568998,0.0033655325,0.00039232968,0.06520743],"study_design_scores_gemma":[0.000011369394,0.000062634324,0.00020478449,0.0000066003568,0.000013125037,0.000019901969,0.000022175798,0.99603385,0.0020579817,0.0012156476,0.00034763035,0.0000043569603],"about_ca_topic_score_codex":0.0016506441,"about_ca_topic_score_gemma":0.0024532822,"teacher_disagreement_score":0.0016506441,"about_ca_system_score_codex":0.00030839746,"about_ca_system_score_gemma":0.0005389356,"threshold_uncertainty_score":0.0035270452},"labels":[],"label_agreement":null},{"id":"W2922529414","doi":"10.1007/s40565-019-0510-0","title":"Enhancing scalability of peer-to-peer energy markets using adaptive segmentation method","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Smart Grid Energy Management","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":"Polytechnique Montréal","funders":"","keywords":"Market segmentation; Scalability; Computer science; Cluster analysis; Peer-to-peer; Novelty; Market clearing; Clearing; Segmentation; Energy market; Distributed computing; Artificial intelligence; Business; Economics; Microeconomics; Marketing; Engineering","score_opus":0.01051726490520023,"score_gpt":0.23468933896600636,"score_spread":0.22417207406080614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922529414","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":[0.06457918,0.00044839917,0.9281099,0.00025781663,0.000079252066,0.0001592793,0.00004391143,0.00085512525,0.005467037],"genre_scores_gemma":[0.884016,0.00016388127,0.11318951,0.00008400536,0.000055987075,0.00012150651,0.00007211343,0.00007075911,0.0022262307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911755,0.00025130986,0.00004494262,0.00018892626,0.00027296002,0.0001242747],"domain_scores_gemma":[0.99867886,0.00063953357,0.00011480062,0.0001556721,0.00029995138,0.00011117142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011758937,0.0005290209,0.0009537643,0.00062463694,0.00094547577,0.0010155254,0.0017070278,0.0008794365,0.0024456216],"category_scores_gemma":[0.0032568767,0.00027833012,0.0004253385,0.00069516915,0.0006805913,0.0025508432,0.0014384682,0.0007297564,0.00039735626],"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":[0.0006359476,0.0003727596,0.0025878716,0.00024007852,0.00012816093,0.000577911,0.0005916281,0.60147625,0.053011537,0.05929803,0.0063825864,0.27469724],"study_design_scores_gemma":[0.000027413926,0.000046114787,0.00018235951,0.0000029346256,0.00000870201,0.00005922577,0.00004288769,0.9895824,0.0021329243,0.0066629094,0.0012415369,0.000010475517],"about_ca_topic_score_codex":0.002149876,"about_ca_topic_score_gemma":0.0020535053,"teacher_disagreement_score":0.0024456216,"about_ca_system_score_codex":0.0006540973,"about_ca_system_score_gemma":0.00088699994,"threshold_uncertainty_score":0.008181393},"labels":[],"label_agreement":null},{"id":"W2936642067","doi":"10.1007/s40565-019-0521-x","title":"Field validation of generic wind park models using fault records","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Wind Turbine Control Systems","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":"Polytechnique Montréal","funders":"National Technical University of Athens; National and Kapodistrian University of Athens; Hong Kong Polytechnic University; Polytechnique Montréal; Georgia Institute of Technology","keywords":"Phasor; Transient (computer programming); Fault (geology); Generator (circuit theory); Relay; Reliability engineering; Sequence (biology); Field (mathematics); Engineering; Wind power; Computer science; Control engineering; Electric power system; Electrical engineering","score_opus":0.012869561679748455,"score_gpt":0.1999989738730136,"score_spread":0.18712941219326515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936642067","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":[0.9182239,0.00006262232,0.07372136,0.00009422237,0.00004384899,0.00016215535,0.0020248776,0.0013996421,0.004267296],"genre_scores_gemma":[0.9941188,0.00003018449,0.0047145872,0.000008231929,0.0000022269865,0.00004542864,0.0006332669,0.000032366897,0.000414868],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999571,0.00013939131,0.000056381738,0.00008281914,0.000102576545,0.000047835274],"domain_scores_gemma":[0.99848783,0.00047585418,0.00015883367,0.00055031537,0.00028605008,0.0000411972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082660996,0.0006357436,0.00050817296,0.00052529486,0.00024253833,0.00041384008,0.0010260112,0.00086292304,0.001944957],"category_scores_gemma":[0.0023701477,0.00020892512,0.00041536093,0.00042354528,0.0004967748,0.00080357806,0.00039648748,0.0005732368,0.00031825036],"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":[0.00012501517,0.00014393413,0.0030539455,0.0000929931,0.000023083485,0.00014862919,0.00008060786,0.97889084,0.0102151735,0.00088301656,0.00041278094,0.0059299413],"study_design_scores_gemma":[0.000061482024,0.0003155985,0.0029281392,0.000011105762,0.000011030218,0.00004695536,0.000047909107,0.9815633,0.013852111,0.00044593192,0.0007035715,0.00001293401],"about_ca_topic_score_codex":0.004266656,"about_ca_topic_score_gemma":0.0029329946,"teacher_disagreement_score":0.004266656,"about_ca_system_score_codex":0.000512698,"about_ca_system_score_gemma":0.000353286,"threshold_uncertainty_score":0.008483648},"labels":[],"label_agreement":null},{"id":"W2945146924","doi":"10.1007/s40565-019-0531-8","title":"Large-signal modeling of three-phase dual active bridge converters for electromagnetic transient analysis in DC grids","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Bombardier (Canada); Polytechnique Montréal","funders":"","keywords":"Converters; Transient (computer programming); Electronic engineering; Grid; Computer science; Time domain; Small-signal model; Computation; Power (physics); Control theory (sociology); Engineering; Electrical engineering; Mathematics; Algorithm; Voltage; Physics","score_opus":0.008603629993561292,"score_gpt":0.21881946648252137,"score_spread":0.21021583648896008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2945146924","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":[0.036413647,0.0001733914,0.95667493,0.00008387196,0.00002433016,0.00003163081,0.00007893143,0.00034808117,0.0061712046],"genre_scores_gemma":[0.9624215,0.00032736603,0.033770178,0.000034464596,0.00002005205,0.000077282,0.00010960944,0.00005679125,0.0031828566],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999255,0.00003050196,0.0000033453061,0.00000918932,0.000025221962,0.000006173955],"domain_scores_gemma":[0.99991095,0.000041824154,0.000011324925,0.000010521589,0.000021038491,0.000004374504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019058696,0.00036101206,0.0003009619,0.00019597064,0.0001898582,0.00047933398,0.00053437444,0.0004211212,0.0012383307],"category_scores_gemma":[0.00038862976,0.000130444,0.00031043642,0.00026624143,0.00020932949,0.00055239233,0.00019990155,0.00041365804,0.0002727276],"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":[0.00003245489,0.000023305283,0.00034464645,0.000047050053,0.0000091885295,0.00007106053,0.00004770496,0.9666842,0.0076397597,0.01263343,0.00040722056,0.012060077],"study_design_scores_gemma":[0.000001214403,0.0000084318635,0.000040059753,0.0000013703108,0.0000012706122,0.000007364572,0.0000037549466,0.9983077,0.0004092022,0.0009203113,0.00029838114,9.3268466e-7],"about_ca_topic_score_codex":0.0018198574,"about_ca_topic_score_gemma":0.0013829949,"teacher_disagreement_score":0.0018198574,"about_ca_system_score_codex":0.00023414116,"about_ca_system_score_gemma":0.00024676212,"threshold_uncertainty_score":0.0041425824},"labels":[],"label_agreement":null},{"id":"W2977793042","doi":"10.1007/s40565-019-0545-2","title":"Robust subsynchronous interaction damping controller for DFIG-based wind farms","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"HVDC Systems and Fault Protection","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Controller (irrigation); Engineering; Electric power system; Converters; Induction generator; Electric power transmission; Wind power; Robust control; Transmission line; Control engineering; Power (physics); Control system; Computer science; Voltage; Control (management)","score_opus":0.012015829087956991,"score_gpt":0.20193874118006697,"score_spread":0.18992291209210999,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977793042","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":[0.047889274,0.00057630864,0.94441825,0.00011472174,0.00012063127,0.000066245,0.000051569525,0.0014163313,0.005346685],"genre_scores_gemma":[0.9752635,0.00014359126,0.023118421,0.00004840831,0.00003334115,0.00007307199,0.00005399956,0.000028419536,0.0012371867],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997677,0.000031697535,0.000018722085,0.00005421839,0.0001018089,0.000025893309],"domain_scores_gemma":[0.9998099,0.00005092124,0.000053857457,0.000017212893,0.000059756618,0.000008342787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003260666,0.00071431964,0.0003675659,0.00023254863,0.0002913334,0.0004684716,0.0007171527,0.00037456898,0.0011634378],"category_scores_gemma":[0.00049150956,0.00017111165,0.0002863775,0.00015322569,0.00022617306,0.00028386794,0.00028609397,0.00050852523,0.0002612613],"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":[0.00046322568,0.00015681748,0.00089662406,0.0004464635,0.00016997573,0.0003706574,0.00020124455,0.63335294,0.08945183,0.009638129,0.0039165844,0.26093554],"study_design_scores_gemma":[0.00005597966,0.00026275488,0.00041359698,0.000012471528,0.0000218946,0.000047566806,0.000007915487,0.9895281,0.006825116,0.0005971363,0.002217739,0.00000976223],"about_ca_topic_score_codex":0.0014183485,"about_ca_topic_score_gemma":0.0016673624,"teacher_disagreement_score":0.0014183485,"about_ca_system_score_codex":0.00029610388,"about_ca_system_score_gemma":0.00025300775,"threshold_uncertainty_score":0.003892064},"labels":[],"label_agreement":null},{"id":"W2987285336","doi":"10.1007/s40565-019-00573-3","title":"Schedulable capacity forecasting for electric vehicles based on big data analysis","year":2019,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Electric Vehicles and Infrastructure","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 New Brunswick","funders":"International Science and Technology Cooperation Programme; National Natural Science Foundation of China","keywords":"Computer science; Big data; Random forest; Decision tree; Boosting (machine learning); Scale (ratio); Gradient boosting; Smart grid; Ensemble learning; k-nearest neighbors algorithm; Data mining; Artificial intelligence; Engineering","score_opus":0.02524584325366714,"score_gpt":0.2024741273801286,"score_spread":0.17722828412646147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2987285336","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":[0.3434503,0.0014584519,0.6454072,0.0009492589,0.00030115744,0.000103583865,0.0014055058,0.0020459574,0.00487853],"genre_scores_gemma":[0.9755653,0.00029016344,0.022692883,0.000039210223,0.000046866462,0.000043296717,0.0007837948,0.00003658844,0.00050194305],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996146,0.00008027824,0.000025580623,0.000086043714,0.00013555915,0.000057853686],"domain_scores_gemma":[0.99909043,0.00041620265,0.00011609517,0.000096732234,0.00021558997,0.00006498829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007905806,0.0008099222,0.0008046826,0.0011964861,0.0004257005,0.0007847325,0.00083336496,0.00048079237,0.00053351966],"category_scores_gemma":[0.0025197433,0.00035569404,0.000580063,0.0010315998,0.00028967936,0.0016787186,0.00049691595,0.000859925,0.0002031188],"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":[0.00009394082,0.000069822476,0.0066484236,0.00005077577,0.000049115475,0.00010761826,0.000030178127,0.9384575,0.0014668131,0.0019550335,0.0016664547,0.049404297],"study_design_scores_gemma":[0.0000011620151,0.0000046364785,0.00056118256,0.0000015722815,0.0000021150056,0.00000439934,0.0000061452606,0.99814105,0.00025700775,0.00091332174,0.00010477379,0.000002650902],"about_ca_topic_score_codex":0.013102451,"about_ca_topic_score_gemma":0.010772634,"teacher_disagreement_score":0.013102451,"about_ca_system_score_codex":0.0007487069,"about_ca_system_score_gemma":0.000916308,"threshold_uncertainty_score":0.026052356},"labels":[],"label_agreement":null},{"id":"W3026273933","doi":"10.35833/mpce.2019.000163","title":"Data-driven Operation Risk Assessment of Wind-integrated Power Systems via Mixture Models and Importance Sampling","year":2020,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":36,"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; SaskPower","keywords":"Wind power; Reliability engineering; Electric power system; Monte Carlo method; Computer science; Reliability (semiconductor); Wind speed; Computation; Cross entropy; Cluster analysis; Entropy (arrow of time); Engineering; Power (physics); Principle of maximum entropy; Statistics; Algorithm; Meteorology","score_opus":0.02302556683721001,"score_gpt":0.24078742286096724,"score_spread":0.21776185602375722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026273933","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":[0.022249881,0.00008900333,0.9771136,0.000043653436,0.000010103984,0.000029600871,0.000024125035,0.000085577754,0.00035441288],"genre_scores_gemma":[0.8363756,0.00023624835,0.16191241,0.000035797522,0.00004348516,0.00015530454,0.00022930163,0.000049739487,0.0009621079],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879897,0.0005638068,0.00005643622,0.00014315185,0.0003664907,0.00007115963],"domain_scores_gemma":[0.9963806,0.0025493805,0.0003206934,0.00022539942,0.00041484428,0.00010905873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025559939,0.0009091699,0.0009789463,0.0010770479,0.00032293887,0.00097411947,0.0012659681,0.00055947836,0.000639203],"category_scores_gemma":[0.0073907953,0.000712794,0.0009008796,0.00071809447,0.00060020824,0.0015535176,0.0011660579,0.0010573892,0.000097970675],"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":[0.000060511375,0.000034708486,0.0016242668,0.000034070552,0.0000524394,0.000048445636,0.000036131376,0.97131324,0.0007541655,0.008718672,0.0001259687,0.017197374],"study_design_scores_gemma":[0.0000011347629,0.000005403645,0.00008588716,0.0000011421644,0.0000020096927,0.0000039975553,0.0000015300619,0.9986841,0.00011545561,0.0010652054,0.0000323126,0.0000018405624],"about_ca_topic_score_codex":0.0042988104,"about_ca_topic_score_gemma":0.0036017527,"teacher_disagreement_score":0.0042988104,"about_ca_system_score_codex":0.0007984199,"about_ca_system_score_gemma":0.00085826125,"threshold_uncertainty_score":0.013517559},"labels":[],"label_agreement":null},{"id":"W3135349110","doi":"10.35833/mpce.2019.000237","title":"Multi-microgrid Energy Management Systems: Architecture, Communication, and Scheduling Strategies","year":2021,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":272,"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":"State Key Laboratory Of Alternate Electrical Power System With Renewable Energy Sources; National Natural Science Foundation of China","keywords":"Microgrid; Distributed computing; Renewable energy; Scheduling (production processes); Distributed generation; Computer science; Energy management; Energy storage; Architecture; Systems engineering; Engineering; Energy (signal processing); Power (physics); Operations management; Electrical engineering","score_opus":0.006016470741433802,"score_gpt":0.18943700045036918,"score_spread":0.18342052970893538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135349110","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":[0.08429258,0.023586897,0.8396208,0.0024022753,0.00023464665,0.0002990611,0.0002599103,0.0012418987,0.04806191],"genre_scores_gemma":[0.91026235,0.007861628,0.075199336,0.00015415008,0.00014418154,0.00014823466,0.00018322385,0.000051268602,0.0059955823],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99986506,0.000044492543,0.000011259952,0.000030609244,0.000030815325,0.000017723787],"domain_scores_gemma":[0.99989974,0.000021273461,0.000021843176,0.000013954352,0.000029411012,0.00001379912],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003131429,0.00052796863,0.00032496738,0.00037770308,0.0004190399,0.0014349909,0.0007925338,0.00042701594,0.0015241681],"category_scores_gemma":[0.00030448468,0.00019886035,0.00022814312,0.0005878541,0.00032270467,0.0012469705,0.00051852927,0.00039453575,0.00038628798],"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":[0.00014456024,0.000109318215,0.004101625,0.0008405373,0.00011937207,0.00036019235,0.0003528179,0.5199705,0.0150190955,0.10522829,0.00747963,0.34627408],"study_design_scores_gemma":[0.000016685624,0.00015978325,0.001850062,0.00010733244,0.000053504966,0.0002713819,0.00040882043,0.9224997,0.0044094543,0.03773133,0.032456994,0.000034974186],"about_ca_topic_score_codex":0.0019044752,"about_ca_topic_score_gemma":0.0029594684,"teacher_disagreement_score":0.0019044752,"about_ca_system_score_codex":0.00071396783,"about_ca_system_score_gemma":0.00065449293,"threshold_uncertainty_score":0.0051802993},"labels":[],"label_agreement":null},{"id":"W3138167674","doi":"10.35833/mpce.2020.000413","title":"Connection Between Damping Torque Analysis and Energy Flow Analysis in Damping Performance Evaluation for Electromechanical Oscillations in Power Systems","year":2022,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Power System Optimization and Stability","field":"Engineering","cited_by":14,"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":"Damping torque; Control theory (sociology); Torque; Damping ratio; Magnetic damping; Thermoelastic damping; Electric power system; Power (physics); Energy flow; Attenuation; Vibration; Energy (signal processing); Spectral density; Engineering; Computer science; Physics; Mathematics; Acoustics; Voltage; Direct torque control; Statistics; Electrical engineering","score_opus":0.013353056581726351,"score_gpt":0.23091911779367236,"score_spread":0.217566061211946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138167674","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":[0.01394444,0.00074181246,0.9832013,0.000054828066,0.000033342614,0.000030077763,0.000013179144,0.00007163685,0.001909359],"genre_scores_gemma":[0.85312086,0.0018803457,0.14311235,0.0000709538,0.00020739267,0.00013038097,0.000070210066,0.00008665653,0.0013208383],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894375,0.00038348476,0.00007281941,0.00014829525,0.0003934632,0.00005832323],"domain_scores_gemma":[0.9982274,0.0010258952,0.00022795452,0.00013380808,0.0003532488,0.00003160864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016007874,0.0012068086,0.00054174307,0.0019635435,0.0002757627,0.0009933974,0.00042229847,0.0005269985,0.0010121072],"category_scores_gemma":[0.0045299414,0.0002130959,0.00062203425,0.00093408325,0.00096672936,0.0015909949,0.00074710505,0.00076007383,0.00023274872],"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":[0.0002127137,0.00021114845,0.0036416093,0.0007186342,0.0001595302,0.00031122487,0.00048356268,0.5468675,0.059980184,0.10008785,0.0009827962,0.28634328],"study_design_scores_gemma":[0.000009167926,0.00011550378,0.0018532565,0.000053813208,0.00003102753,0.00009553726,0.000070012306,0.96886796,0.0064914185,0.020219533,0.0021554031,0.00003746156],"about_ca_topic_score_codex":0.0008939723,"about_ca_topic_score_gemma":0.00039708114,"teacher_disagreement_score":0.0019635435,"about_ca_system_score_codex":0.0003062238,"about_ca_system_score_gemma":0.0003311915,"threshold_uncertainty_score":0.008465886},"labels":[],"label_agreement":null},{"id":"W3183173808","doi":"10.35833/mpce.2020.000177","title":"Impact Assessment and Mitigation Techniques for High Penetration Levels of Renewable Energy Sources in Distribution Networks: Voltage-control Perspective","year":2022,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Optimal Power Flow Distribution","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Natural Resources Canada","funders":"Government of Canada","keywords":"Tap changer; Renewable energy; Distributed generation; Voltage; Computer science; Reliability engineering; Penetration (warfare); Engineering; Electrical engineering; Operations research","score_opus":0.005879913540605153,"score_gpt":0.23243666361226226,"score_spread":0.2265567500716571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183173808","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":[0.5617082,0.0017363807,0.4090575,0.00055305945,0.00007279962,0.000244412,0.00027053733,0.00058961654,0.025767444],"genre_scores_gemma":[0.9868881,0.00028543343,0.012042218,0.0000130686985,0.000010605582,0.000018117084,0.000041382787,0.000015540849,0.0006855971],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997032,0.000115467556,0.000008231049,0.000023192099,0.00011859387,0.00003129708],"domain_scores_gemma":[0.99939346,0.00037757124,0.000080040874,0.00003190094,0.000102956685,0.000014087488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057705294,0.00076891994,0.00035175652,0.0009125307,0.0001765575,0.0006004022,0.00041009215,0.00046664343,0.0011944557],"category_scores_gemma":[0.0013192665,0.00015113529,0.0003796729,0.0006080081,0.00023622226,0.0007643652,0.00028224362,0.0003571616,0.000084649524],"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":[0.000080362064,0.00007767609,0.0023992218,0.000101393016,0.000029207706,0.00009742663,0.000034631696,0.95252484,0.007014109,0.0019941083,0.00022502297,0.035421945],"study_design_scores_gemma":[0.000011312286,0.00021487828,0.002937384,0.000020681964,0.000039784478,0.000036787053,0.00005746798,0.9885464,0.0058832876,0.0016743137,0.00056759367,0.000010221252],"about_ca_topic_score_codex":0.003885296,"about_ca_topic_score_gemma":0.004866364,"teacher_disagreement_score":0.003885296,"about_ca_system_score_codex":0.0005487004,"about_ca_system_score_gemma":0.00033578457,"threshold_uncertainty_score":0.007725358},"labels":[],"label_agreement":null},{"id":"W3192429335","doi":"10.35833/mpce.2020.00647","title":"Short-term Load Prediction of Integrated Energy System with Wavelet Neural Network Model Based on Improved Particle Swarm Optimization and Chaos Optimization Algorithm","year":2021,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Energy Load and Power Forecasting","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":"Concordia University","funders":"","keywords":"Particle swarm optimization; Inertia; Artificial neural network; Convergence (economics); Computer science; Energy (signal processing); Local optimum; Mathematical optimization; Multi-swarm optimization; Jump; Algorithm; Control theory (sociology); Artificial intelligence; Mathematics; Statistics","score_opus":0.007516345431435144,"score_gpt":0.1746521456579459,"score_spread":0.16713580022651076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3192429335","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":[0.123527765,0.0004218136,0.8710921,0.00021716894,0.00008805737,0.00004216867,0.00009731542,0.0003020337,0.004211669],"genre_scores_gemma":[0.9727542,0.00032527183,0.02370596,0.00002377266,0.000025113914,0.00007035819,0.00012057346,0.000028977258,0.0029456527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998276,0.000031979573,0.000012092278,0.000043548953,0.0000651324,0.000019688747],"domain_scores_gemma":[0.9998658,0.00004527757,0.000019529492,0.00000942842,0.00005368401,0.0000063754037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037450006,0.0005095155,0.0005530366,0.0003030092,0.00026335154,0.00064137176,0.0007044097,0.00044439433,0.0008081156],"category_scores_gemma":[0.0007474572,0.00027875238,0.00051450427,0.00043672055,0.00023569337,0.0010405504,0.00034118883,0.0006215548,0.00012590097],"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":[0.000040099,0.000026440957,0.0016050787,0.00003440421,0.000037364865,0.00004718337,0.000031176372,0.9712233,0.0013101037,0.0018887123,0.00037898213,0.023377163],"study_design_scores_gemma":[0.0000011379138,0.000003908971,0.00010156447,7.90068e-7,0.000001901829,0.0000020519697,0.0000012195571,0.99963653,0.00007767273,0.00013900976,0.000032970074,0.0000010710386],"about_ca_topic_score_codex":0.013744752,"about_ca_topic_score_gemma":0.008282906,"teacher_disagreement_score":0.013744752,"about_ca_system_score_codex":0.0004364028,"about_ca_system_score_gemma":0.00064102834,"threshold_uncertainty_score":0.027329504},"labels":[],"label_agreement":null},{"id":"W3209711571","doi":"10.35833/mpce.2020.000580","title":"Dynamic-decision-based Real-time Dispatch for Reducing Constraint Violations","year":2022,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Electric Power System Optimization","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 Saskatchewan","funders":"","keywords":"Economic dispatch; Constraint (computer-aided design); Process (computing); Computer science; Electric power system; Point (geometry); Identification (biology); Moment (physics); Mathematical optimization; Power (physics); Operations research; Engineering; Mathematics","score_opus":0.004726863144434747,"score_gpt":0.20273304703731346,"score_spread":0.19800618389287872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209711571","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":[0.008759126,0.0001413523,0.988342,0.00008542592,0.000044594603,0.000035392513,0.000026791318,0.00026194283,0.002303462],"genre_scores_gemma":[0.7873552,0.00015749286,0.20941782,0.00010456735,0.000057874047,0.00011568204,0.00012889091,0.000102672435,0.0025598258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989262,0.0002915635,0.00006186003,0.00023956888,0.00035514322,0.00012567514],"domain_scores_gemma":[0.9992969,0.00027410945,0.00013852971,0.0000512108,0.00018196194,0.000057356167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010475777,0.0010967829,0.0010072793,0.0005514336,0.0005427509,0.00096673815,0.0014652803,0.0004987476,0.0022227194],"category_scores_gemma":[0.0015108509,0.0004233021,0.00044368644,0.00066363695,0.00044917906,0.0011298766,0.0007916051,0.0011451287,0.0003424372],"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":[0.0002032076,0.0001413242,0.00038619476,0.00010426369,0.000053350537,0.00010141305,0.000080793325,0.8466311,0.00789145,0.015950948,0.0023012005,0.12615475],"study_design_scores_gemma":[0.000013626503,0.000023509281,0.000059219397,0.0000024704605,0.0000042294496,0.000010062799,0.000003735289,0.99742573,0.0007925168,0.0011474567,0.0005106402,0.0000066448406],"about_ca_topic_score_codex":0.0032085977,"about_ca_topic_score_gemma":0.0034158619,"teacher_disagreement_score":0.0032085977,"about_ca_system_score_codex":0.00075828476,"about_ca_system_score_gemma":0.0014957564,"threshold_uncertainty_score":0.007435739},"labels":[],"label_agreement":null},{"id":"W340997383","doi":"10.1007/s40565-015-0122-2","title":"Residential electrical vehicle charging strategies: the good, the bad and the ugly","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":52,"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; H2020 European Research Council; Science Foundation Ireland; Queen's University Belfast; National University of Ireland","keywords":"Testbed; Variety (cybernetics); Electric vehicle; Range (aeronautics); Computer science; Electric power system; Power (physics); Operations research; Automotive engineering; Engineering; Artificial intelligence; Aerospace engineering; Computer network","score_opus":0.006103781520911534,"score_gpt":0.19208790577313967,"score_spread":0.18598412425222813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W340997383","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":[0.33966985,0.03492691,0.5319536,0.020847823,0.00049231754,0.00015512882,0.00019632254,0.0008972949,0.070860825],"genre_scores_gemma":[0.9628692,0.0044233617,0.028969968,0.0005774405,0.00016056704,0.000020200509,0.000023287015,0.000058201356,0.0028976696],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9982659,0.0008903625,0.000065007844,0.00013752439,0.0005257945,0.000115468916],"domain_scores_gemma":[0.9977743,0.0011548301,0.00028013063,0.00032667146,0.00035852188,0.00010557265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030521238,0.00055468315,0.00084815954,0.0006204285,0.0007244798,0.0028281088,0.0009550037,0.0013654375,0.0012952313],"category_scores_gemma":[0.005345238,0.00023244889,0.0003330047,0.0011346866,0.0018080712,0.0028201041,0.0010214376,0.0009062556,0.00037162713],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011955495,0.00027641127,0.007596013,0.00075136515,0.00025442036,0.0003016713,0.00062650564,0.27765828,0.004956611,0.2550703,0.00910256,0.44221047],"study_design_scores_gemma":[0.00021099814,0.001218441,0.00851749,0.0004007437,0.00020032573,0.0011317227,0.002273347,0.6632524,0.008955534,0.26955104,0.044113472,0.00017450075],"about_ca_topic_score_codex":0.0012189628,"about_ca_topic_score_gemma":0.0025873997,"teacher_disagreement_score":0.0030521238,"about_ca_system_score_codex":0.0009786601,"about_ca_system_score_gemma":0.000527795,"threshold_uncertainty_score":0.016141415},"labels":[],"label_agreement":null},{"id":"W4286445786","doi":"10.35833/mpce.2021.000182","title":"Dual Control Strategy for Grid-tied Battery Energy Storage Systems to Comply with Emerging Grid Codes and Fault Ride Through Requirements","year":2022,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Microgrid Control and Optimization","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":"Polytechnique Montréal","funders":"","keywords":"Grid code; Voltage droop; Grid; Battery (electricity); Control (management); Dual (grammatical number); Fault (geology); Reliability engineering; Computer science; Code (set theory); Voltage; Energy storage; Engineering; Control theory (sociology); Electrical engineering; AC power; Set (abstract data type); Voltage source; Power (physics)","score_opus":0.012278142377566364,"score_gpt":0.21084297431442892,"score_spread":0.19856483193686256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286445786","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":[0.23817478,0.00038733255,0.74567854,0.00030217072,0.00020354989,0.00021840842,0.000042995973,0.00072130095,0.014270867],"genre_scores_gemma":[0.99286735,0.000034199962,0.0061648292,0.000036747406,0.000016355589,0.00003073838,0.000012199686,0.000005092264,0.0008324889],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997415,0.00003745903,0.000026480808,0.000062900464,0.000088917724,0.000042826206],"domain_scores_gemma":[0.9997193,0.000032744018,0.00008247514,0.00003350722,0.000100150355,0.00003185655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026088694,0.000527631,0.00040430936,0.00036493537,0.00030049199,0.0008949012,0.0007398461,0.00037135746,0.0013399886],"category_scores_gemma":[0.0004447777,0.00014081325,0.00022676493,0.00016966148,0.0003231178,0.00046815356,0.00054519245,0.00036927708,0.00024020528],"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":[0.0017695186,0.0008100017,0.003094173,0.0005228034,0.00015256379,0.0010478923,0.0006389,0.3413549,0.2671125,0.025154147,0.003939497,0.35440314],"study_design_scores_gemma":[0.0001385698,0.0006298267,0.0009967905,0.000019850655,0.000040903342,0.00024171543,0.00006088817,0.9773745,0.016158514,0.0024960376,0.0018179645,0.000024444727],"about_ca_topic_score_codex":0.0014999654,"about_ca_topic_score_gemma":0.001632768,"teacher_disagreement_score":0.0014999654,"about_ca_system_score_codex":0.000268617,"about_ca_system_score_gemma":0.00045237405,"threshold_uncertainty_score":0.004482746},"labels":[],"label_agreement":null},{"id":"W4312973683","doi":"10.35833/mpce.2021.000336","title":"Improved Synergetic Current Control for Grid-connected Microgrids and Distributed Generation Systems","year":2022,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Microgrid Control and Optimization","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":"Queen's University; Royal Military College of Canada","funders":"","keywords":"Control theory (sociology); Integral sliding mode; Microgrid; Controller (irrigation); Overshoot (microwave communication); Convergence (economics); Inverter; DSPACE; Grid; Computer science; Control engineering; Control (management); Engineering; Voltage; Sliding mode control; Mathematics; Algorithm; Nonlinear system; Electrical engineering","score_opus":0.005973554208080451,"score_gpt":0.1825101898985744,"score_spread":0.17653663569049394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312973683","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":[0.025743281,0.0006135793,0.96554315,0.000088405104,0.00008514729,0.000043576332,0.000019599964,0.0006184637,0.007244767],"genre_scores_gemma":[0.92299056,0.00043535387,0.07308931,0.000041661275,0.00006435632,0.000064058055,0.00004015423,0.000032298387,0.0032422096],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982494,0.000024992449,0.000011710809,0.000031224237,0.0000955121,0.000011676718],"domain_scores_gemma":[0.99988127,0.000024361334,0.000024508701,0.000015739424,0.000046595604,0.0000074941104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003486498,0.00039965005,0.00033134274,0.0003706185,0.00020373579,0.00042185572,0.00044372134,0.00022130559,0.0013009333],"category_scores_gemma":[0.00037673826,0.000107118874,0.0002177619,0.0003022818,0.00026748815,0.00055594416,0.00041259217,0.0003854377,0.00021574403],"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":[0.000285625,0.00022356618,0.0007560136,0.00061495363,0.000067499815,0.0002441999,0.00027978333,0.36257628,0.111461334,0.037375934,0.0027270282,0.48338777],"study_design_scores_gemma":[0.000034891196,0.00028533573,0.0004921912,0.00001768581,0.000017290575,0.00009049492,0.000018401051,0.9790101,0.011114222,0.0032951983,0.0056127673,0.000011324208],"about_ca_topic_score_codex":0.0003963796,"about_ca_topic_score_gemma":0.0006432266,"teacher_disagreement_score":0.0013009333,"about_ca_system_score_codex":0.00024992236,"about_ca_system_score_gemma":0.00033745397,"threshold_uncertainty_score":0.004352033},"labels":[],"label_agreement":null},{"id":"W4385273673","doi":"10.35833/mpce.2022.000138","title":"Hierarchical Frequency-dependent Chance Constrained Unit Commitment for Bulk AC/DC Hybrid Power Systems with Wind Power Generation","year":2023,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Energy Load and Power Forecasting","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 Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Electric power system; Power system simulation; Wind power; Control theory (sociology); Upgrade; Frequency deviation; Power (physics); Computer science; Engineering; Automatic frequency control; Electrical engineering","score_opus":0.019725909539199598,"score_gpt":0.21813267736259695,"score_spread":0.19840676782339736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385273673","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":[0.1512722,0.00035925908,0.83919704,0.00030104342,0.000060161903,0.000112502756,0.00014054358,0.00027773943,0.008279531],"genre_scores_gemma":[0.98248005,0.00006294038,0.015941247,0.000033706077,0.000010433374,0.00005689108,0.000050533523,0.000015822101,0.0013483994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996586,0.00014315566,0.000016703323,0.000057635836,0.00007547868,0.00004854387],"domain_scores_gemma":[0.99961734,0.00020674795,0.00006197619,0.000032083113,0.00004684137,0.000034991346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000635766,0.0004744005,0.0005622518,0.00017715109,0.0003447896,0.0006500017,0.0008012185,0.00044110784,0.0021532266],"category_scores_gemma":[0.0012928668,0.00035459874,0.0003651628,0.00042817948,0.00046429643,0.0006232686,0.00059875293,0.00078435644,0.00017274113],"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":[0.000028682483,0.0000063508674,0.00015117483,0.00000957809,0.00000842564,0.000025770538,0.000010510008,0.9930414,0.0002228108,0.0028213619,0.0001599634,0.0035139667],"study_design_scores_gemma":[0.000003142279,0.000010830287,0.000041954154,7.293977e-7,0.0000014489339,0.000002700493,0.000002034551,0.999057,0.000037990572,0.0007924904,0.00004822625,0.0000013829662],"about_ca_topic_score_codex":0.011875336,"about_ca_topic_score_gemma":0.012595857,"teacher_disagreement_score":0.011875336,"about_ca_system_score_codex":0.0007129231,"about_ca_system_score_gemma":0.00080334564,"threshold_uncertainty_score":0.02361244},"labels":[],"label_agreement":null},{"id":"W4385320205","doi":"10.35833/mpce.2022.000245","title":"An Improved Perturb and Observed Maximum Power Point Tracking Algorithm for Photovoltaic Power Systems","year":2023,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"solar cell performance optimization","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Duty cycle; Maximum power point tracking; Maximum power principle; Photovoltaic system; Power (physics); Algorithm; Control theory (sociology); Boost converter; Oscillation (cell signaling); Computer science; Mathematics; Voltage; Engineering; Electrical engineering; Physics","score_opus":0.014204542654730612,"score_gpt":0.20926337614516313,"score_spread":0.19505883349043251,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385320205","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":[0.0043152794,0.000103604834,0.9936718,0.000039331648,0.000040930594,0.0000310156,0.000020120468,0.00071840815,0.0010595993],"genre_scores_gemma":[0.17762819,0.00026434945,0.8164212,0.00008888761,0.00009456642,0.00016959946,0.00018873707,0.00017273516,0.0049717654],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995303,0.000058099922,0.000026526264,0.00010184589,0.00025725306,0.00002590274],"domain_scores_gemma":[0.9996623,0.00010890998,0.000041378313,0.00004213017,0.00013153336,0.000013781299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048460675,0.0007029239,0.00077603303,0.00059414544,0.00041115808,0.00069871824,0.0009308183,0.0006961252,0.0019962718],"category_scores_gemma":[0.0014745649,0.0002958581,0.00042429124,0.00082113896,0.00025891673,0.00095203164,0.0005817259,0.0009781134,0.0009462337],"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":[0.00024244611,0.00011067351,0.0010434048,0.00015232738,0.000055942695,0.00014018276,0.00013728194,0.22114632,0.036517072,0.0069124224,0.0030871944,0.73045474],"study_design_scores_gemma":[0.000028163708,0.000059073685,0.0003428599,0.0000072996886,0.000010727636,0.000070580136,0.0000063854964,0.9884438,0.0057949275,0.0011530895,0.0040698014,0.000013355319],"about_ca_topic_score_codex":0.0017141257,"about_ca_topic_score_gemma":0.0019192082,"teacher_disagreement_score":0.0019962718,"about_ca_system_score_codex":0.00042014144,"about_ca_system_score_gemma":0.0005107277,"threshold_uncertainty_score":0.0066782236},"labels":[],"label_agreement":null},{"id":"W4386879915","doi":"10.35833/mpce.2022.000088","title":"Power and Voltage Control Based on DC Offset Injection for Bipolar Low-voltage DC Distribution System","year":2023,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Advanced DC-DC Converters","field":"Engineering","cited_by":13,"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","funders":"National Natural Science Foundation of China","keywords":"Electrical engineering; Overcurrent; Voltage; Low voltage; Offset (computer science); Engineering; Control theory (sociology); Computer science; Control (management)","score_opus":0.004798668984107225,"score_gpt":0.19201067036263225,"score_spread":0.18721200137852503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386879915","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":[0.13782112,0.0008349343,0.8296961,0.0001789672,0.00016373066,0.00014951444,0.000100628255,0.0010855354,0.029969385],"genre_scores_gemma":[0.9907885,0.00018264813,0.007585392,0.000021303336,0.000015229221,0.000018971517,0.000019373761,0.000010371293,0.0013583363],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99991715,0.000013309523,0.000004343462,0.000017368959,0.000037660448,0.000010155011],"domain_scores_gemma":[0.99994755,0.000010278036,0.000014053434,0.0000049590353,0.000019813475,0.000003376683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009384125,0.00038690786,0.00023652293,0.00022922724,0.00028937214,0.00055256,0.00036320585,0.00015851238,0.001671144],"category_scores_gemma":[0.00014177129,0.00008527069,0.00014140825,0.0002500823,0.00022738436,0.00028734296,0.00016190697,0.00027768922,0.00017132421],"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":[0.0010383461,0.00038362204,0.0034635754,0.0008559961,0.0000781478,0.00076124683,0.00052823295,0.28270465,0.35022402,0.05689012,0.005332227,0.2977398],"study_design_scores_gemma":[0.000056662582,0.0003117209,0.0009470569,0.00003027335,0.00003353755,0.00013158513,0.000039225597,0.9721662,0.019776292,0.003140307,0.0033527494,0.00001445911],"about_ca_topic_score_codex":0.0018544508,"about_ca_topic_score_gemma":0.002296111,"teacher_disagreement_score":0.0018544508,"about_ca_system_score_codex":0.00035847662,"about_ca_system_score_gemma":0.00026184582,"threshold_uncertainty_score":0.0055904984},"labels":[],"label_agreement":null},{"id":"W4388925078","doi":"10.35833/mpce.2022.000499","title":"Fault Detection for Microgrid Feeders Using Features Based on Superimposed Positive-sequence Power","year":2023,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Microgrid Control and Optimization","field":"Engineering","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":"Microgrid; Fault (geology); Scheme (mathematics); Fault detection and isolation; Synchronization (alternating current); Computer science; Power (physics); Sequence (biology); Engineering; Topology (electrical circuits); Reliability engineering; Voltage; Artificial intelligence; Mathematics; Electrical engineering","score_opus":0.010504699819610204,"score_gpt":0.21505909087923092,"score_spread":0.20455439105962073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388925078","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":[0.28952545,0.0002444796,0.7035885,0.00009927202,0.00007730295,0.00014033605,0.00009358744,0.0027016262,0.0035294516],"genre_scores_gemma":[0.96285564,0.000046191923,0.03658604,0.000017888575,0.00001703502,0.000016508024,0.00004958142,0.000014219384,0.0003968589],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983203,0.000029815252,0.000012231138,0.000036060013,0.00007564983,0.000014049774],"domain_scores_gemma":[0.9995523,0.000110050816,0.00011876917,0.00007547822,0.000112068425,0.000031207866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023828076,0.0005467667,0.00034405914,0.00061692484,0.00028818878,0.00040953915,0.00055942056,0.00024037457,0.0012800338],"category_scores_gemma":[0.0010003452,0.00015481222,0.00022465701,0.0004526553,0.00028751476,0.0006063048,0.0003719291,0.00027100704,0.00022982642],"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":[0.0019341072,0.0002625645,0.0054148487,0.00028884725,0.00011684784,0.00072013546,0.00029924858,0.18025246,0.17088974,0.006045129,0.0018835423,0.63189256],"study_design_scores_gemma":[0.000045902194,0.00048773547,0.0041701756,0.000017574095,0.000048744132,0.00036734593,0.000021915372,0.95813763,0.034531023,0.0010654046,0.001086936,0.000019666031],"about_ca_topic_score_codex":0.0010996924,"about_ca_topic_score_gemma":0.0020408127,"teacher_disagreement_score":0.0012800338,"about_ca_system_score_codex":0.00035071498,"about_ca_system_score_gemma":0.00024257258,"threshold_uncertainty_score":0.0042821765},"labels":[],"label_agreement":null},{"id":"W4393196971","doi":"10.35833/mpce.2023.000085","title":"Improved State-space Modelling for Microgrids Without Virtual Resistances","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Microgrid Control and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Research Manitoba; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"State space; Space (punctuation); State (computer science); Computer science; Engineering; Simulation; Mathematics; Algorithm; Operating system; Statistics","score_opus":0.0058337121601773866,"score_gpt":0.19045360492036176,"score_spread":0.18461989276018437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393196971","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":[0.014378323,0.00010067718,0.9789707,0.00006875579,0.000023426961,0.000033792974,0.0000728179,0.00046131609,0.005890197],"genre_scores_gemma":[0.889038,0.00040843745,0.10110723,0.00003904497,0.000025681273,0.00018657306,0.00021308124,0.00013242495,0.008849535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998398,0.00006520572,0.000010463913,0.000022414915,0.000052374282,0.000009730604],"domain_scores_gemma":[0.9998153,0.0000723499,0.00003106059,0.00003834469,0.000036575257,0.0000063823454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003190758,0.00070190144,0.00056188373,0.00025596886,0.00030843008,0.000813684,0.00068147463,0.0005236978,0.0030289895],"category_scores_gemma":[0.0007192279,0.00026359194,0.00065130513,0.0002701279,0.00039645238,0.0012333884,0.00051844504,0.00085702445,0.00066515786],"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":[0.000016945283,0.0000116378405,0.00014252597,0.000032917305,0.000007804049,0.000035721994,0.00005360124,0.9793931,0.0028466808,0.010416083,0.00020236886,0.0068405652],"study_design_scores_gemma":[0.0000017552763,0.000009477557,0.00002990552,0.0000025731279,0.0000022566649,0.000005959303,0.000004117218,0.9976089,0.0003175099,0.0015009745,0.00051439885,0.0000021371684],"about_ca_topic_score_codex":0.0029951134,"about_ca_topic_score_gemma":0.002934091,"teacher_disagreement_score":0.0030289895,"about_ca_system_score_codex":0.00032686992,"about_ca_system_score_gemma":0.00048406498,"threshold_uncertainty_score":0.010132968},"labels":[],"label_agreement":null},{"id":"W4393197043","doi":"10.35833/mpce.2023.000729","title":"Virtual Transmission Solution Based on Battery Energy Storage Systems to Boost Transmission Capacity","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Power Systems and Renewable Energy","field":"Energy","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":"Polytechnique Montréal","funders":"","keywords":"Transmission (telecommunications); Energy storage; Battery (electricity); Computer science; Transmission system; Energy (signal processing); Electrical engineering; Engineering; Telecommunications; Mathematics; Physics","score_opus":0.012432951026422756,"score_gpt":0.21222993552867006,"score_spread":0.1997969845022473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393197043","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":[0.40310657,0.0012306438,0.56792396,0.00049167924,0.00021775896,0.00013285795,0.00026098898,0.0022567993,0.024378737],"genre_scores_gemma":[0.9927227,0.000119266515,0.0058304383,0.000020880814,0.000008358975,0.0000164909,0.000031616288,0.00001316468,0.0012370647],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999212,0.00002613345,0.0000049446526,0.000011922484,0.000021604812,0.000014299642],"domain_scores_gemma":[0.9998841,0.000030771334,0.000021508748,0.000014359595,0.000035946112,0.000013255566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014170412,0.00033631496,0.0003234997,0.0002602579,0.00023009018,0.0004844148,0.0005357749,0.00021251905,0.0029534495],"category_scores_gemma":[0.00024603127,0.00010315435,0.00020969268,0.00024770122,0.00021545788,0.0006736455,0.000368339,0.00027224753,0.0002703201],"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":[0.000626443,0.00017060632,0.0013631263,0.00029935263,0.00009420976,0.0005638856,0.00014017493,0.7914601,0.06741963,0.01852108,0.0040830057,0.11525835],"study_design_scores_gemma":[0.00005005005,0.00022251329,0.00040000404,0.00001497336,0.000028595683,0.000105080275,0.00004065045,0.98595166,0.0077879643,0.00263075,0.0027555174,0.000012142124],"about_ca_topic_score_codex":0.0015085205,"about_ca_topic_score_gemma":0.0020775462,"teacher_disagreement_score":0.0029534495,"about_ca_system_score_codex":0.00027666995,"about_ca_system_score_gemma":0.00030021567,"threshold_uncertainty_score":0.009880245},"labels":[],"label_agreement":null},{"id":"W4401039360","doi":"10.35833/mpce.2023.000234","title":"Communication-less燤anagement燬trategy爁or燛lectric燰ehicle燙harging爄n燚roop-controlled營slanded燤icrogrids","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Advanced Manufacturing and Logistics 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":false,"ca_institutions":"York University; Independent Electricity System Operator","funders":"","keywords":"Computer science; Operations research; Engineering","score_opus":0.005774852620059897,"score_gpt":0.20264709622731833,"score_spread":0.19687224360725844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401039360","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":[0.13644254,0.00085991307,0.81100285,0.00044669217,0.00031706315,0.00018825059,0.00013128782,0.0027112677,0.047900073],"genre_scores_gemma":[0.97357947,0.00024530062,0.017250104,0.00009940291,0.00005321522,0.000045176657,0.00007969756,0.000040828072,0.008606811],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997727,0.00003468856,0.000014613422,0.00006895343,0.000064767715,0.00004424413],"domain_scores_gemma":[0.999801,0.000027421725,0.000037834187,0.000060729068,0.000050256167,0.00002278963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001603847,0.0004608303,0.00030198222,0.00022790614,0.0003854287,0.0008480372,0.000944184,0.0003555498,0.0032685583],"category_scores_gemma":[0.0003211774,0.0000990705,0.00025887424,0.00019331895,0.00041552365,0.0009366312,0.0008459138,0.00038115893,0.000757399],"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":[0.00061363133,0.00032684754,0.0029902495,0.00055196806,0.00011677716,0.0010842843,0.00066749007,0.18333599,0.11316472,0.053945266,0.009431095,0.63377166],"study_design_scores_gemma":[0.00007333675,0.0007517935,0.003254324,0.000072611525,0.00007367471,0.0008020767,0.00050777645,0.8646039,0.048838656,0.024927853,0.05602452,0.000069589296],"about_ca_topic_score_codex":0.0013669332,"about_ca_topic_score_gemma":0.0014806314,"teacher_disagreement_score":0.0032685583,"about_ca_system_score_codex":0.00034458798,"about_ca_system_score_gemma":0.0004124105,"threshold_uncertainty_score":0.010934472},"labels":[],"label_agreement":null},{"id":"W4401039592","doi":"10.35833/mpce.2023.000909","title":"A燜ault燚iagnosis燤ethod爁or燬mart燤eters爒ia燭wo-layer燬tacking燛nsemble燨ptimization燼nd燚ata燗ugmentation","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Electricity Theft Detection Techniques","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":"Concordia University","funders":"","keywords":"Computer science; Data mining; Pattern recognition (psychology); Classifier (UML); Artificial intelligence; Discriminative model; Imputation (statistics); Feature extraction; Autoencoder; Machine learning; Missing data; Deep learning","score_opus":0.007469101767333921,"score_gpt":0.2217330217041269,"score_spread":0.21426391993679297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401039592","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":[0.01819893,0.0005081719,0.9750243,0.0002699411,0.0001733495,0.000070507456,0.000110935216,0.0025453721,0.0030985877],"genre_scores_gemma":[0.5563126,0.0012679347,0.4237241,0.0005002102,0.0002491406,0.00018414836,0.0010968922,0.0003427994,0.01632205],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99929786,0.000094385396,0.00005677987,0.00022350495,0.00022756134,0.00009988613],"domain_scores_gemma":[0.99936646,0.000104639636,0.00008095099,0.0002532416,0.00016366855,0.000031068208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095542596,0.0010288174,0.00081043906,0.0009634078,0.000611655,0.0015991734,0.0013099306,0.001349609,0.004419883],"category_scores_gemma":[0.0021833521,0.00046560128,0.0010622203,0.0007527543,0.00083388435,0.002336037,0.0017862092,0.0016011777,0.002316361],"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":[0.00030452848,0.00016223575,0.0038508219,0.00018725758,0.00014791526,0.00038852697,0.00017860952,0.21865027,0.033087604,0.010889896,0.00699584,0.7251566],"study_design_scores_gemma":[0.000007011972,0.00006964969,0.0010021934,0.000018954166,0.000024367637,0.00018121299,0.000047251728,0.97244114,0.015360374,0.0046130545,0.0062137004,0.000020997444],"about_ca_topic_score_codex":0.0041601434,"about_ca_topic_score_gemma":0.0041001085,"teacher_disagreement_score":0.004419883,"about_ca_system_score_codex":0.0006643419,"about_ca_system_score_gemma":0.0010135493,"threshold_uncertainty_score":0.014786005},"labels":[],"label_agreement":null},{"id":"W4402877653","doi":"10.35833/mpce.2023.000352","title":"Adaptive Two-stage Unscented Kalman Filter for Dynamic State Estimation of Synchronous Generator Under Cyber Attacks Against Measurements","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":24,"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":"Kalman filter; Control theory (sociology); Computer science; Generator (circuit theory); State (computer science); Stage (stratigraphy); Estimation; Extended Kalman filter; Control engineering; Engineering; Artificial intelligence; Power (physics); Algorithm; Physics","score_opus":0.014465279274578378,"score_gpt":0.24164077202425055,"score_spread":0.22717549274967216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402877653","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":[0.005403697,0.00009485185,0.9938391,0.00003099722,0.000024327632,0.000013520675,0.00001710974,0.00020870204,0.00036779756],"genre_scores_gemma":[0.67359936,0.00064627884,0.32072973,0.00013008443,0.00010299882,0.00018698227,0.00037449473,0.00008596137,0.0041441345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931645,0.00012840558,0.000052573352,0.00019973586,0.00023873083,0.00006413146],"domain_scores_gemma":[0.99926215,0.0002822514,0.00009939168,0.00008179573,0.00025516583,0.000019322588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087190507,0.00075228536,0.0006296728,0.00042621093,0.0003754837,0.0005079904,0.0008738771,0.0008255057,0.0009345756],"category_scores_gemma":[0.003004647,0.00035511228,0.000729439,0.000459365,0.00039176925,0.0011200235,0.0005029176,0.0010215816,0.00043715394],"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":[0.00026833586,0.00007581193,0.0030204633,0.00022076094,0.00011118803,0.0001113354,0.00027500975,0.66397023,0.028090775,0.010307237,0.0015967244,0.2919521],"study_design_scores_gemma":[0.0000079660695,0.000045508812,0.00046195774,0.000005295111,0.000010097424,0.000020604835,0.000006467258,0.9951148,0.0030264005,0.00058612047,0.0007037937,0.000010902207],"about_ca_topic_score_codex":0.0086679105,"about_ca_topic_score_gemma":0.006861997,"teacher_disagreement_score":0.0086679105,"about_ca_system_score_codex":0.00051675254,"about_ca_system_score_gemma":0.0009475685,"threshold_uncertainty_score":0.017234921},"labels":[],"label_agreement":null},{"id":"W4402877661","doi":"10.35833/mpce.2023.000616","title":"Reliable Phase Selection Method for Transmission Systems Based on Relative Angles Between Sequence Voltages","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Power Systems and Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Selection (genetic algorithm); Sequence (biology); Voltage; Transmission (telecommunications); Phase (matter); Transmission system; Computer science; Three-phase; Electronic engineering; Algorithm; Engineering; Control theory (sociology); Electrical engineering; Physics; Artificial intelligence; Telecommunications; Biology","score_opus":0.021044800752073985,"score_gpt":0.2787465901487102,"score_spread":0.25770178939663624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402877661","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":[0.0047923215,0.00017869807,0.99406624,0.00002143793,0.000020389432,0.000020849975,0.0000131179495,0.00013031358,0.00075657625],"genre_scores_gemma":[0.5958851,0.0005278584,0.4017463,0.000034231067,0.0000581063,0.00010924188,0.0000825898,0.000061438834,0.0014951517],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999663,0.00010883251,0.000020523674,0.000058424925,0.00013227035,0.000016945078],"domain_scores_gemma":[0.99960333,0.00014323434,0.00009583834,0.000054954453,0.000093066155,0.000009665151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051333837,0.0005641728,0.00029409787,0.00052614673,0.00029280307,0.00052441336,0.00037810838,0.0002629536,0.0019707181],"category_scores_gemma":[0.001413902,0.00019555513,0.0002594574,0.0004699727,0.0003240581,0.0007840269,0.00034572682,0.00048928964,0.00047338952],"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":[0.0002398911,0.00004267548,0.0012948767,0.00033522234,0.000043266486,0.00010258768,0.00029992682,0.43013117,0.046879873,0.055157557,0.0024791972,0.4629938],"study_design_scores_gemma":[0.000022627179,0.000102897706,0.0002476088,0.00002158322,0.0000118852995,0.00007360748,0.000026334335,0.9823215,0.007295545,0.006280965,0.0035839197,0.000011545352],"about_ca_topic_score_codex":0.0007589173,"about_ca_topic_score_gemma":0.00091635477,"teacher_disagreement_score":0.0019707181,"about_ca_system_score_codex":0.00030537398,"about_ca_system_score_gemma":0.0004622421,"threshold_uncertainty_score":0.006592691},"labels":[],"label_agreement":null},{"id":"W4407122787","doi":"10.35833/mpce.2023.000939","title":"Power System Reliability Evaluation Based on Sequential Monte Carlo Simulation Considering Multiple Failure Modes of Components","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Smart Grid and Power Systems","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Monte Carlo method; Reliability engineering; Reliability (semiconductor); Computer science; Power (physics); Electric power system; Engineering; Mathematics; Physics","score_opus":0.018660731331649534,"score_gpt":0.2330663057051405,"score_spread":0.21440557437349098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407122787","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":[0.09513021,0.00016424037,0.9012729,0.00008162644,0.00002036308,0.00010403575,0.00008568453,0.00044237752,0.0026985027],"genre_scores_gemma":[0.92285234,0.000120980134,0.07600418,0.000022613134,0.000015947773,0.00016019883,0.00012387626,0.000037354504,0.0006624886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993037,0.00028984167,0.000036289213,0.000092972616,0.00021234226,0.00006485851],"domain_scores_gemma":[0.99804735,0.0012772602,0.00019170885,0.000119140124,0.00030631392,0.00005821013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011847691,0.0006983548,0.0007570678,0.0007579286,0.00040539828,0.0005514512,0.00070338,0.00042421036,0.0014374084],"category_scores_gemma":[0.0032212287,0.0004195165,0.00068890146,0.0006127669,0.000458079,0.0006693317,0.0004573242,0.0005194578,0.00012593412],"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":[0.000019983623,0.000010371619,0.00059422787,0.000013049183,0.000010114504,0.000020367737,0.0000105490235,0.9934273,0.00043057135,0.0013766554,0.000061339124,0.0040255156],"study_design_scores_gemma":[0.0000015025998,0.000005945675,0.000051066963,6.4376144e-7,0.0000019224537,0.000004162639,0.0000013538516,0.99948716,0.00010795669,0.00030559572,0.000031621803,0.0000010358555],"about_ca_topic_score_codex":0.011782883,"about_ca_topic_score_gemma":0.007721401,"teacher_disagreement_score":0.011782883,"about_ca_system_score_codex":0.00080532546,"about_ca_system_score_gemma":0.0015024358,"threshold_uncertainty_score":0.023428619},"labels":[],"label_agreement":null},{"id":"W4408823332","doi":"10.35833/mpce.2024.000264","title":"A Clearing Mechanism with Reduced Computational Complexity for Spot Flexibility Markets","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Auction Theory and Applications","field":"Decision Sciences","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":"Hydro-Québec; Université du Québec à Trois-Rivières; Innovation and Economic Development Trois Rivières","funders":"","keywords":"Clearing; Flexibility (engineering); Market clearing; Mechanism (biology); Spot market; Hot spot (computer programming); Computer science; Spot contract; Sweet spot; Computational complexity theory; Business; Operations research; Economics; Engineering; Simulation; Microeconomics; Futures contract; Algorithm; Finance; Electrical engineering; Management","score_opus":0.09144401574047728,"score_gpt":0.34741176598393836,"score_spread":0.2559677502434611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408823332","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":[0.017846888,0.00012932988,0.9778511,0.0001545351,0.0000494003,0.00015545097,0.000026851769,0.00032069132,0.0034658208],"genre_scores_gemma":[0.6460052,0.00020994939,0.3489996,0.00012411278,0.000069056965,0.00036003345,0.0000921114,0.000083129096,0.0040567224],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989182,0.00039297537,0.000074658834,0.00015480563,0.00031252482,0.00014690665],"domain_scores_gemma":[0.9988606,0.00046195096,0.00018603631,0.00019308021,0.00021931392,0.00007911061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001856171,0.00054151093,0.0012069064,0.00063819165,0.0006899672,0.001559457,0.0017785041,0.0012724082,0.00424258],"category_scores_gemma":[0.0030677596,0.00033941,0.0006721686,0.00091730256,0.0008116815,0.001714516,0.0011307062,0.0011133988,0.0006053258],"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":[0.00024032423,0.00031736566,0.00045944194,0.00013675723,0.000051485415,0.0002676517,0.000121311175,0.73352385,0.010308422,0.11925072,0.0042297775,0.13109289],"study_design_scores_gemma":[0.000053810447,0.000082960636,0.0000939999,0.0000048128886,0.0000071640466,0.0000798059,0.000012177787,0.9870253,0.0010206839,0.010225716,0.0013821862,0.000011400806],"about_ca_topic_score_codex":0.001513741,"about_ca_topic_score_gemma":0.0012588636,"teacher_disagreement_score":0.00424258,"about_ca_system_score_codex":0.00073619204,"about_ca_system_score_gemma":0.0022809664,"threshold_uncertainty_score":0.01419282},"labels":[],"label_agreement":null},{"id":"W4408823756","doi":"10.35833/mpce.2023.000723","title":"Consideration on Present and Future of Battery Energy Storage System to Unlock Battery Value","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Advanced Battery Technologies Research","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":"Polytechnique Montréal","funders":"","keywords":"Battery (electricity); Energy storage; Value (mathematics); Automotive engineering; Energy (signal processing); Computer science; Reliability engineering; Battery storage; Engineering; Electrical engineering; Mathematics; Power (physics); Physics","score_opus":0.009011183538282645,"score_gpt":0.22895665125400133,"score_spread":0.21994546771571868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408823756","genre_codex":"other","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":[0.07584696,0.1808058,0.07605652,0.2484715,0.004889545,0.00011925715,0.0011768856,0.0002386516,0.41239494],"genre_scores_gemma":[0.85239905,0.09394238,0.013263975,0.008741848,0.0022622086,0.00009493901,0.00027322065,0.000057345795,0.028965032],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992735,0.00017451585,0.000039357295,0.00009621086,0.00032840174,0.00008809359],"domain_scores_gemma":[0.9987545,0.0004615307,0.00006947081,0.000046265308,0.00058014126,0.000088114124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017053727,0.0002831681,0.00028957275,0.00072912837,0.0007109132,0.0028310663,0.0008791856,0.0021942097,0.0062944936],"category_scores_gemma":[0.0028598392,0.00017799732,0.0003828096,0.00081483007,0.0011673577,0.0052946224,0.000697783,0.0019460039,0.0006899363],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007789923,0.000041599462,0.0023321037,0.00048697053,0.000023749995,0.0003949897,0.0002388117,0.016577099,0.0032771418,0.816497,0.025860038,0.13419265],"study_design_scores_gemma":[0.000020532163,0.00017638825,0.0044815806,0.0016625695,0.000043262502,0.0005466335,0.0014496479,0.036292855,0.0036476362,0.43507,0.5165219,0.00008697775],"about_ca_topic_score_codex":0.003746173,"about_ca_topic_score_gemma":0.0068119112,"teacher_disagreement_score":0.0062944936,"about_ca_system_score_codex":0.002049567,"about_ca_system_score_gemma":0.0027855267,"threshold_uncertainty_score":0.021057189},"labels":[],"label_agreement":null},{"id":"W4410734654","doi":"10.35833/mpce.2024.000469","title":"Cost-aware Flexibility Evaluation for Microgrids","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Smart Grid Energy Management","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 Calgary","funders":"","keywords":"Flexibility (engineering); Reliability engineering; Risk analysis (engineering); Computer science; Engineering; Business; Economics","score_opus":0.033498996096947356,"score_gpt":0.27394518338181967,"score_spread":0.24044618728487233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410734654","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":[0.15134695,0.00072365446,0.8381002,0.00031824847,0.000035863985,0.00014944653,0.00017578935,0.00018808614,0.008961727],"genre_scores_gemma":[0.97249275,0.00017682281,0.026503548,0.0000158513,0.000011023027,0.00004878243,0.000056148983,0.000027401913,0.0006676215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99918896,0.00043709102,0.000029473496,0.000058846028,0.00021420568,0.0000715568],"domain_scores_gemma":[0.9987117,0.0009329056,0.00012331523,0.00006279457,0.00011853004,0.00005065212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017168614,0.0010578184,0.0006602398,0.0010920402,0.00036627936,0.001077284,0.0006209799,0.000619572,0.0014774941],"category_scores_gemma":[0.004586504,0.00041136038,0.0007940582,0.0007660029,0.0005081512,0.0010994368,0.000890763,0.0006196237,0.0000864416],"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":[0.000021303833,0.000008004404,0.00039292173,0.000022640257,0.000014722801,0.000037105252,0.000011435857,0.98986536,0.00036779494,0.002954249,0.000073820695,0.006230544],"study_design_scores_gemma":[0.000001933013,0.000016436205,0.00017041805,0.0000060629873,0.0000043141454,0.000010759972,0.000010781491,0.9979381,0.00015464841,0.0015858109,0.000096787495,0.000003965351],"about_ca_topic_score_codex":0.004199884,"about_ca_topic_score_gemma":0.003917839,"teacher_disagreement_score":0.004199884,"about_ca_system_score_codex":0.0011046001,"about_ca_system_score_gemma":0.0006876064,"threshold_uncertainty_score":0.009079754},"labels":[],"label_agreement":null},{"id":"W4413255033","doi":"10.35833/mpce.2023.000986","title":"Detailed Equivalent Modeling and Simulation of Modular Multilevel Converters with Partially- integrated Battery Energy Storage","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"HVDC Systems and Fault Protection","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":"Manitoba Hydro; University of Manitoba","funders":"","keywords":"Modular design; Converters; Battery (electricity); Energy storage; Computer science; Energy (signal processing); Engineering; Automotive engineering; Electrical engineering; Voltage; Power (physics); Mathematics; Physics","score_opus":0.012215878605454119,"score_gpt":0.2103112509332604,"score_spread":0.19809537232780627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413255033","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":[0.12162519,0.00026371362,0.83985215,0.00020784988,0.000056254263,0.00013477038,0.0008053154,0.0009020764,0.036152657],"genre_scores_gemma":[0.97079754,0.00021942364,0.02266558,0.000042496504,0.0000151525655,0.00015278015,0.00029905685,0.00006062859,0.0057473537],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998634,0.00003665635,0.000006441098,0.000016934691,0.000058983267,0.000017617593],"domain_scores_gemma":[0.9998765,0.000045518562,0.000020176329,0.000021190901,0.000029355799,0.0000073283472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018872078,0.00046259785,0.00070232636,0.00035598138,0.00033317014,0.000735069,0.0011246498,0.00082778925,0.0030213185],"category_scores_gemma":[0.00046523658,0.00029551078,0.00075402437,0.00043472764,0.00032086644,0.0008173726,0.0003808271,0.00048733447,0.00038850252],"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":[0.000015234198,0.000010071822,0.00015070946,0.00001758902,0.000008966833,0.000049963022,0.000018966573,0.99194443,0.0014904656,0.003562764,0.00018065327,0.002550178],"study_design_scores_gemma":[0.0000022466568,0.000006504154,0.000049796014,0.0000013491792,0.0000018330926,0.0000062119916,0.000003270862,0.9988925,0.00016537445,0.00066574593,0.00020393595,0.0000012793143],"about_ca_topic_score_codex":0.004761898,"about_ca_topic_score_gemma":0.0040920903,"teacher_disagreement_score":0.004761898,"about_ca_system_score_codex":0.0005818889,"about_ca_system_score_gemma":0.00047910563,"threshold_uncertainty_score":0.010107338},"labels":[],"label_agreement":null},{"id":"W4416759722","doi":"10.35833/mpce.2025.000807","title":"Smart Grid Origins, Definitions, Technologies, and Emerging Trends: A Power Community Perspective","year":2024,"lang":"en","type":"article","venue":"Journal of Modern Power Systems and Clean Energy","topic":"Smart Grid Energy Management","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 Calgary","funders":"","keywords":"Panacea (medicine); Smart grid; Perspective (graphical); Term (time); Electricity; Power grid","score_opus":0.015236522179596652,"score_gpt":0.22101395572892477,"score_spread":0.20577743354932812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416759722","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038819473,0.06232774,0.04063583,0.35357502,0.0019009588,0.00008712811,0.00017608992,0.00016229265,0.5023155],"genre_scores_gemma":[0.8500716,0.08392174,0.009820258,0.021166401,0.0031561207,0.00015730207,0.00017431026,0.00018474608,0.03134739],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99785125,0.00089273916,0.00008593715,0.00022412158,0.00068940356,0.00025651522],"domain_scores_gemma":[0.9967163,0.0019391496,0.00023721984,0.00018340493,0.00062485156,0.00029897477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004296129,0.00042927207,0.00037038483,0.0035214436,0.0034491182,0.011308086,0.001061809,0.0038628827,0.0046135164],"category_scores_gemma":[0.004840184,0.0002805208,0.00026669976,0.006251817,0.011622543,0.019451126,0.0046568336,0.0062261173,0.00048442243],"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":[0.000004703336,0.00001150686,0.000240517,0.00006735981,0.0000014740724,0.000098080964,0.0040054084,0.00023369491,0.00007995079,0.9804582,0.0035961496,0.011203084],"study_design_scores_gemma":[0.000008669832,0.000034673867,0.0006181537,0.00050863257,0.0000042387214,0.00026865548,0.017778097,0.0012412128,0.0001969013,0.4675566,0.51176393,0.000020216836],"about_ca_topic_score_codex":0.00486863,"about_ca_topic_score_gemma":0.004939307,"teacher_disagreement_score":0.011308086,"about_ca_system_score_codex":0.0046744333,"about_ca_system_score_gemma":0.0039578876,"threshold_uncertainty_score":0.03391558},"labels":[],"label_agreement":null}]}