{"id":"W3108247818","doi":"10.1017/bca.2020.25","title":"Averting Expenditures and Willingness to Pay for Electricity Supply Reliability","year":2020,"lang":"en","type":"article","venue":"Journal of Benefit-Cost Analysis","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Electricity; Willingness to pay; Economic shortage; Business; Mains electricity; Reliability (semiconductor); Service (business); Value (mathematics); Actuarial science; Environmental economics; Economics; Marketing; Microeconomics; Engineering; Government (linguistics); Power (physics); Computer science","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":[0.001739374,0.0002684637,0.0003072623,0.0005150528,0.0002602708,0.001318927,0.0003641024,0.001182719,0.00584506],"category_scores_gemma":[0.0102401,0.0002303169,0.0006103875,0.0004600502,0.0005580529,0.0009334507,0.0005547498,0.001305783,0.0002551803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00118162,"about_ca_system_score_gemma":0.0003871104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002651039,"about_ca_topic_score_gemma":0.002476304,"domain_scores_codex":[0.9991385,0.0004458158,0.00004179324,0.00007174451,0.0001028581,0.0001992158],"domain_scores_gemma":[0.9885792,0.007886646,0.002306861,0.0003547296,0.0003927328,0.0004797939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001064785,0.001326709,0.6694596,0.0002118906,0.0006680292,0.001291375,0.0009936838,0.2288023,0.003211658,0.04997426,0.00198948,0.04100621],"study_design_scores_gemma":[0.00009547687,0.002017932,0.4684846,0.0001276334,0.0003478142,0.001398127,0.003376247,0.4720795,0.001784741,0.04703338,0.003114338,0.0001402037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904153,0.00009892626,0.003997583,0.0005480494,0.00001002751,0.00003316052,0.0001765506,0.00001173854,0.00470861],"genre_scores_gemma":[0.999207,0.00002285976,0.0001927664,0.00001741769,0.000003759788,0.000005709754,0.00004222137,7.194442e-7,0.0005075155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00584506,"threshold_uncertainty_score":0.01955372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0536239802309804,"score_gpt":0.2336543095594796,"score_spread":0.1800303293284992,"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."}}