{"id":"W2900270437","doi":"10.1108/ijesm-07-2018-0017","title":"Determining the efficacy of consolidating municipal electric utilities in Ontario, Canada","year":2018,"lang":"en","type":"article","venue":"International Journal of Energy Sector Management","topic":"Electric Power System Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Equity (law); Consolidation (business); Shareholder; Electricity; Finance; Business; Operational efficiency; Debt; Mergers and acquisitions; Government (linguistics); Electric power distribution; Electric utility; Wilcoxon signed-rank test; Accounting; Economics; Marketing; Engineering; Economic growth; Corporate governance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002125325,0.0001894446,0.0002391014,0.001074928,0.003068524,0.002391388,0.001267153,0.0003893606,0.001843632],"category_scores_gemma":[0.0160223,0.0002646198,0.0001813278,0.002770842,0.001866247,0.0007095159,0.001128145,0.0004597998,0.0001738931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.064489,"about_ca_system_score_gemma":0.07720598,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9897254,"about_ca_topic_score_gemma":0.9961851,"domain_scores_codex":[0.9961551,0.0003732638,0.0002025183,0.0002780013,0.002134368,0.0008568777],"domain_scores_gemma":[0.9786227,0.002530492,0.004919678,0.0005200005,0.01139935,0.002007694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002324711,0.00008305374,0.9480543,0.0001592248,0.00004617108,0.0003496805,0.006473108,0.001360209,0.001590603,0.001686951,0.002086867,0.03787725],"study_design_scores_gemma":[0.00001034114,0.00007507314,0.9793786,0.00005355406,0.00002451002,0.00005783355,0.01155452,0.0008923009,0.0005838613,0.0001101885,0.007241412,0.00001792427],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882916,0.0002661271,0.0001927966,0.0006278025,0.000006109914,0.00008229935,0.0003372128,0.00001236067,0.0101837],"genre_scores_gemma":[0.9963858,0.0002619997,0.0002900246,0.00006403926,0.000003217673,0.00001363313,0.0001986014,0.000002511992,0.002780081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.064489,"threshold_uncertainty_score":0.4679027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009803151229255328,"score_gpt":0.2084233762538426,"score_spread":0.1986202250245873,"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."}}