{"id":"W2105059868","doi":"10.1109/tpwrs.2013.2291446","title":"Use of Mobile Unit Substations in Redundant Customer Delivery Systems","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Power Systems","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro One (Canada)","funders":"","keywords":"Reliability engineering; Transformer; Probabilistic logic; Markov chain; Computer science; Markov model; Mobile telephony; Engineering; Operations research; Telecommunications; Electrical engineering; Mobile radio; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001653015,0.000228027,0.0002178437,0.0008163459,0.0003323102,0.000600117,0.0005746739,0.0004103279,0.001305508],"category_scores_gemma":[0.006006371,0.0001365512,0.0002760789,0.0008484752,0.0004249994,0.0007949197,0.0005935992,0.0002500885,0.000152636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009852744,"about_ca_system_score_gemma":0.0004828433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001586026,"about_ca_topic_score_gemma":0.003054452,"domain_scores_codex":[0.9974349,0.00171988,0.00007193261,0.0001242875,0.0004689703,0.0001800463],"domain_scores_gemma":[0.9917544,0.005008981,0.001646071,0.0006177408,0.0007838201,0.0001889999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004882106,0.0009540071,0.4228856,0.001248916,0.0004424263,0.005336949,0.00434965,0.1496338,0.03248215,0.03149589,0.001445935,0.3448426],"study_design_scores_gemma":[0.000368364,0.03431955,0.6068082,0.0005445401,0.001453584,0.01103295,0.007773739,0.2541918,0.04533086,0.01606624,0.02193671,0.0001735203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921108,0.0001572287,0.004731554,0.00006867392,0.000006198273,0.00002603811,0.0000579779,0.00001237878,0.002829103],"genre_scores_gemma":[0.9990767,0.00005176324,0.0007200183,0.000004658656,0.000003765477,0.000007947868,0.0000122009,0.000001343954,0.0001214267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001653015,"threshold_uncertainty_score":0.008742094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01839379888222706,"score_gpt":0.2131955654948154,"score_spread":0.1948017666125884,"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."}}