{"id":"W4384915497","doi":"10.2139/ssrn.4505225","title":"Revisit cost-benefit analysis in energy infrastructure: Current methodology, practice, and limitations toward digital investment","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Energy Efficiency and Management","field":"Energy","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Current (fluid); Investment (military); Energy (signal processing); Risk analysis (engineering); Environmental economics; Business; Computer science; Economics; Engineering; Political science; Electrical engineering; Physics; Politics","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":[0.001926902,0.0002247908,0.0003412784,0.0009802884,0.0001651697,0.0001538267,0.0002592606,0.00008645274,0.00001742927],"category_scores_gemma":[0.0008014394,0.0002028637,0.0001597589,0.00215313,0.00006755839,0.0004809896,0.0001502808,0.0009095035,0.00001480422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000680551,"about_ca_system_score_gemma":0.0003803619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000248469,"about_ca_topic_score_gemma":0.004032506,"domain_scores_codex":[0.9969826,0.0002707099,0.0004916883,0.0003645934,0.0003249509,0.001565461],"domain_scores_gemma":[0.9987285,0.0005798666,0.0002419327,0.0002253344,0.00009699982,0.0001274388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002624723,0.00004456854,0.0003043045,0.000004698109,0.0005068602,0.000008990993,0.0002174361,0.07898523,0.00001070558,0.605917,0.0001162616,0.3138577],"study_design_scores_gemma":[0.000949236,0.0002623296,0.007554799,0.00002671085,0.0007241972,0.0001141752,0.00428988,0.006280455,0.00002155285,0.569519,0.4098441,0.0004135524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3371096,0.1184312,0.4190906,0.0296399,0.003322091,0.001402284,0.00005386659,0.001049237,0.08990128],"genre_scores_gemma":[0.92078,0.07682689,0.0007245412,0.0005352077,0.0001475575,0.00004399392,0.00008200373,0.00002788146,0.0008319091],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5836704,"threshold_uncertainty_score":0.8272543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04129104141461416,"score_gpt":0.3109856760520295,"score_spread":0.2696946346374153,"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."}}