{"id":"W2097440812","doi":"10.1111/j.1539-6924.2007.00905.x","title":"Risk‐Management and Risk‐Analysis‐Based Decision Tools for Attacks on Electric Power","year":2007,"lang":"en","type":"article","venue":"Risk Analysis","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Department of Homeland Security","keywords":"Reliability (semiconductor); Electric power; Logistic regression; Risk analysis (engineering); Duration (music); Binomial regression; Risk management; Engineering; Operations research; Reliability engineering; Computer science; Power (physics); Statistics; Business; Mathematics; Finance","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":[0.007537921,0.001291141,0.0008751617,0.004671433,0.0006728439,0.003348655,0.001248488,0.001021972,0.008072542],"category_scores_gemma":[0.02239413,0.0006070284,0.001060379,0.001879435,0.0006232012,0.003773296,0.001693372,0.001349472,0.000900134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001987678,"about_ca_system_score_gemma":0.002095612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00599963,"about_ca_topic_score_gemma":0.005808909,"domain_scores_codex":[0.9965813,0.00220655,0.0003140144,0.0002075556,0.000567665,0.0001230828],"domain_scores_gemma":[0.9844363,0.01243454,0.00119549,0.0005109765,0.001166589,0.0002561506],"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":[0.0003583795,0.0004385953,0.009168753,0.0003135259,0.0001821478,0.0002616342,0.0005760893,0.7271113,0.001079719,0.06532946,0.0121168,0.1830636],"study_design_scores_gemma":[0.00005733288,0.00008113874,0.001395056,0.00009143569,0.00003912109,0.0000671555,0.000279682,0.9493684,0.0008661025,0.04203621,0.00567804,0.0000403068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09020307,0.0007060768,0.8799626,0.003007585,0.00009877016,0.0007581625,0.002355101,0.004485511,0.01842313],"genre_scores_gemma":[0.5187967,0.0006532245,0.4750461,0.0001439924,0.00007019183,0.0008817856,0.00166246,0.0001561021,0.00258949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008072542,"threshold_uncertainty_score":0.03986478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005274620728249226,"score_gpt":0.2499161738215722,"score_spread":0.244641553093323,"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."}}