{"id":"W4400005946","doi":"10.1007/978-3-031-62881-8_30","title":"Machine Learning-Driven Three-Phase Current Relay Protection System for Small Transient Periods in Sustainable Power Systems","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Power Systems Fault Detection","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Relay; Transient (computer programming); Current (fluid); Phase (matter); Electric power system; Power (physics); Computer science; Electrical engineering; Engineering; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001017173,0.0009563816,0.001419032,0.0008294424,0.0001578283,0.0004242981,0.0002116428,0.001356284,0.00000348463],"category_scores_gemma":[0.0000348313,0.0008854446,0.0002566493,0.0002725391,0.00004610528,0.0001097344,0.00005028466,0.002236765,0.000007593073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001542092,"about_ca_system_score_gemma":0.00005113607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007076636,"about_ca_topic_score_gemma":0.00130085,"domain_scores_codex":[0.9963493,0.0001172797,0.001376548,0.0009335984,0.0003416722,0.0008816173],"domain_scores_gemma":[0.9987897,0.000183154,0.0002697132,0.0004530244,0.0001428797,0.0001614818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001248854,0.00001969051,0.0000538741,0.01531952,0.0001779416,0.0001246886,0.0006491393,0.9748265,0.00002856264,0.004130154,0.00003830573,0.004506748],"study_design_scores_gemma":[0.001001509,0.0003361609,0.000003754858,0.007637152,0.00009223916,0.0002077097,0.00007702269,0.7974109,0.00000287028,0.00005915051,0.1924748,0.0006966811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007254508,0.1821759,0.7917381,0.00001551447,0.01274771,0.007428996,0.00007669878,0.0008138918,0.0042777],"genre_scores_gemma":[0.9913509,0.0004515817,0.00001469551,0.000001535562,0.0009009454,0.001496957,0.0001040763,0.0003634001,0.005315898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9906254,"threshold_uncertainty_score":0.9999402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01254027770122684,"score_gpt":0.2247146295178095,"score_spread":0.2121743518165827,"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."}}