{"id":"W3208255100","doi":"10.32920/ryerson.14655681.v1","title":"Probabilistic power transmission system reliability evaluation","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Probabilistic logic; Upgrade; Reliability engineering; Transmission system; Transmission (telecommunications); Reliability (semiconductor); Electric power system; Power transmission; Plan (archaeology); Fault (geology); Business system planning; Computer science; Asset (computer security); Engineering; Power (physics); Telecommunications; Systems engineering; Computer security","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"],"consensus_categories":[],"category_scores_codex":[0.002040452,0.0004449034,0.0006511122,0.00007557125,0.00005637175,0.0001354991,0.0003546949,0.0006260644,0.0004155142],"category_scores_gemma":[0.0002182273,0.0003953115,0.0003097437,0.0001631923,0.00004849213,0.0001172351,0.0001619848,0.0007049807,0.00004987546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00131925,"about_ca_system_score_gemma":0.000313677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007478007,"about_ca_topic_score_gemma":0.00001556431,"domain_scores_codex":[0.9969732,0.0003098862,0.0008164849,0.0008028178,0.0007085517,0.0003890482],"domain_scores_gemma":[0.9976745,0.00009641033,0.00008100794,0.001406023,0.0005707481,0.0001713246],"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":[0.0000286444,0.0001797187,0.00008462809,0.02757362,0.0001833332,0.00002507478,0.001933085,0.9548343,0.001041235,0.001520616,0.003874298,0.008721422],"study_design_scores_gemma":[0.0004433753,0.00003335428,0.001111966,0.00352484,0.0002107562,0.00002686769,0.0007060418,0.9838158,0.00140832,0.0009944147,0.006837722,0.000886509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.311313,0.006242279,0.4800472,0.0003037195,0.0125328,0.006272211,0.00007141296,0.00444573,0.1787716],"genre_scores_gemma":[0.996823,0.00003743742,0.002191922,0.00001301313,0.00006945543,0.0005023887,0.0001018736,0.00006044063,0.0002005065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6855099,"threshold_uncertainty_score":0.9998499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01374749653317043,"score_gpt":0.2313525030617961,"score_spread":0.2176050065286256,"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."}}