{"id":"W3157616196","doi":"10.18280/mmep.080201","title":"Optimal Location of Sectionners and Distributed Generation Resources to Improve Reliability in Distribution Networks","year":2021,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Blackout; Reliability (semiconductor); Downstream (manufacturing); Distribution (mathematics); Reliability engineering; Computer science; Power (physics); Distributed generation; Upstream (networking); Distributed computing; Engineering; Computer network; Electric power system; Operations management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004245852,0.0006373167,0.000838963,0.000598493,0.0004581794,0.0006475179,0.0006978496,0.0006747343,0.001611466],"category_scores_gemma":[0.001512208,0.0004034827,0.0003202745,0.0006041886,0.0005720156,0.001076765,0.0007503816,0.0004010427,0.0002848116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006676793,"about_ca_system_score_gemma":0.0007018787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002254203,"about_ca_topic_score_gemma":0.00336265,"domain_scores_codex":[0.999792,0.00006592264,0.000009872768,0.00006862588,0.00003042851,0.00003308482],"domain_scores_gemma":[0.9996449,0.0001653747,0.00008352759,0.00002820757,0.00004810429,0.00002982889],"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":[0.0001286811,0.00005184359,0.001330973,0.0000798129,0.00002080898,0.0001408445,0.00009990913,0.9325176,0.009882989,0.01735609,0.000735241,0.03765514],"study_design_scores_gemma":[0.00001463771,0.00009473327,0.000356367,0.00001246748,0.00001812875,0.0000634773,0.00006108628,0.9870057,0.003526952,0.007700139,0.001133307,0.00001304475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05989593,0.0002959826,0.9368434,0.0001110029,0.00004131495,0.00004991829,0.00004514854,0.0001801206,0.002537241],"genre_scores_gemma":[0.8100536,0.0004804805,0.1850535,0.00002539852,0.00003179023,0.00007943167,0.00005152486,0.00003993051,0.004184258],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002254203,"threshold_uncertainty_score":0.005390882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009619036762110929,"score_gpt":0.1797382039747118,"score_spread":0.1701191672126008,"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."}}