{"id":"W4366728292","doi":"10.1109/tsg.2023.3265786","title":"IEEE Transactions on Smart Grid Publication Information","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Power Systems and Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Universidade de São Paulo; Zhejiang University; University of Waterloo; Kungliga Tekniska Högskolan; Tsinghua University; Nanyang Technological University; Hunan University; Pacific Northwest National Laboratory; York University; Universidad de Chile; Mississippi State University; National University of Singapore; Iowa State University; University of Tehran; University of Central Florida; Florida International University; University of Alberta; Rensselaer Polytechnic Institute","keywords":"Smart grid; Computer science; Grid; Telecommunications; Engineering; Electrical engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002349063,0.0003189286,0.0002681574,0.000975399,0.0003636425,0.000151665,0.0002816971,0.0002954285,0.0001684065],"category_scores_gemma":[0.000006516864,0.0003266128,0.000201963,0.001286666,0.0000581176,0.001072791,4.963759e-7,0.000575478,0.003320495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002019648,"about_ca_system_score_gemma":0.00003624201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001126785,"about_ca_topic_score_gemma":0.0001435328,"domain_scores_codex":[0.9983166,0.00003065589,0.0005401167,0.0002595431,0.000382302,0.0004707976],"domain_scores_gemma":[0.9989865,0.00009780775,0.00006846683,0.0006163041,0.0001100901,0.0001208683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001075511,0.0003588508,0.00003449697,0.0004274505,0.0005550068,0.00001349642,0.001627223,0.5945235,0.00523836,0.0003333233,0.1323968,0.2643839],"study_design_scores_gemma":[0.001950537,0.000535109,0.001393375,0.0002609395,0.0001627006,0.00007049099,0.0008318061,0.1319185,0.2743402,0.0001654834,0.5868056,0.001565262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02290792,0.00002084461,0.949422,0.0009873883,0.0139821,0.0006320777,0.0005552201,0.006402635,0.005089804],"genre_scores_gemma":[0.9977651,0.0002192672,0.0001889307,0.000136579,0.0001390056,0.0005034737,0.00006201048,0.00005634209,0.0009292898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9748572,"threshold_uncertainty_score":0.9999186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551280541888257,"score_gpt":0.2133948324412565,"score_spread":0.1978820270223739,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}