{"id":"W2110830467","doi":"10.1109/epc.2008.4763375","title":"Evaluating capacity probability distributions of aged power equipment: Method and example","year":2008,"lang":"en","type":"article","venue":"","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Unavailability; Reliability engineering; Reliability (semiconductor); Probability distribution; Computer science; Transmission (telecommunications); Component (thermodynamics); Probability model; Power (physics); Power transmission; Engineering; Statistics; Mathematics; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.0009381244,0.0001029157,0.0002087762,0.00002099233,0.00008085297,0.000006008486,0.00007368215,0.00005492557,0.0001000898],"category_scores_gemma":[0.0002182619,0.00008947701,0.00004770841,0.0001187842,0.00009704512,0.0001042187,0.00003952095,0.00009930339,0.000003438741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006947625,"about_ca_system_score_gemma":0.00001817042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000212221,"about_ca_topic_score_gemma":0.00004571904,"domain_scores_codex":[0.999096,0.00009682609,0.0002909557,0.0001760328,0.0001432126,0.0001969277],"domain_scores_gemma":[0.9994048,0.0001435572,0.00003179389,0.000274881,0.00007819624,0.00006671537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001538879,0.001419988,0.06331793,0.006424494,0.0008719945,0.00002396121,0.04367542,0.03357572,0.6604687,0.1576693,0.01019922,0.02219933],"study_design_scores_gemma":[0.004312312,0.000886499,0.5200594,0.0005119215,0.0001738092,0.0004083566,0.0008145761,0.1308675,0.2554776,0.07414026,0.01015687,0.002190817],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6559699,0.00006132972,0.339006,0.00001992438,0.00008729135,0.000218182,0.00002802951,0.0001117646,0.004497525],"genre_scores_gemma":[0.9512342,0.000007816343,0.04863439,0.000005815239,0.00000645036,0.00002580434,0.000003967892,0.000006880801,0.00007474145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4567415,"threshold_uncertainty_score":0.3648767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08706507984177957,"score_gpt":0.2963408399830146,"score_spread":0.209275760141235,"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."}}