{"id":"W2900400407","doi":"","title":"Understanding the cost of power interruptions to U.S. electricity consumers","year":2004,"lang":"en","type":"article","venue":"Lawrence Berkeley National Laboratory","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Blackout; Electricity; Reliability (semiconductor); Electric power industry; Reliability engineering; Quality (philosophy); Computer science; Environmental economics; Electricity market; Electric power system; Power (physics); Electricity generation; Business; Risk analysis (engineering); Economics; Engineering; Electrical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00126352,0.0004454419,0.0002819123,0.001629194,0.0004384311,0.001831579,0.0007709864,0.001255927,0.002973255],"category_scores_gemma":[0.007704843,0.0003136733,0.0006202065,0.001658934,0.0004938542,0.002852597,0.0007532204,0.001247566,0.0002481395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003730889,"about_ca_system_score_gemma":0.001208121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05941207,"about_ca_topic_score_gemma":0.04527462,"domain_scores_codex":[0.9993,0.0002526249,0.0000393001,0.00009357154,0.0001629991,0.0001515173],"domain_scores_gemma":[0.9969947,0.001679115,0.0005568675,0.0001461318,0.0005009029,0.0001222502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002598113,0.0002916764,0.1724976,0.0001675633,0.0001765961,0.0005635223,0.0008533616,0.4727192,0.0008265509,0.2464084,0.01878768,0.08644795],"study_design_scores_gemma":[0.00003837848,0.0002622911,0.1850468,0.0001654347,0.0002378483,0.0004879896,0.003211153,0.6627529,0.001000076,0.1300378,0.0166338,0.0001254933],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8848989,0.002224872,0.04115291,0.009052156,0.00009062291,0.0001578458,0.004463742,0.0001680149,0.05779094],"genre_scores_gemma":[0.9931931,0.0008958151,0.003198677,0.0001755828,0.00003012629,0.00003174296,0.00083749,0.00001308147,0.001624471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05941207,"threshold_uncertainty_score":0.1181325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03548939390424717,"score_gpt":0.251232083713723,"score_spread":0.2157426898094758,"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."}}