{"id":"W2708946506","doi":"10.1109/ccece.2017.7946739","title":"Impact of demand response management on improving social welfare of remote communities through integrating renewable energy resources","year":2017,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Resources Canada","keywords":"Demand response; Renewable energy; Environmental economics; Renewable resource; Load management; Social Welfare; Computer science; Demand management; Diesel generator; Energy management; Welfare; Business; Energy (signal processing); Economics; Diesel fuel; Engineering; Electricity; Automotive engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004291112,0.0002239737,0.0003204122,0.0001553169,0.0004176122,0.00007559767,0.0005901058,0.00007380837,0.00007857806],"category_scores_gemma":[0.00003856536,0.0001939232,0.0001597586,0.00008024586,0.0001152847,0.0001988849,0.0003290409,0.0001047501,7.03402e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001368486,"about_ca_system_score_gemma":0.000007052376,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0244197,"about_ca_topic_score_gemma":0.00159311,"domain_scores_codex":[0.9988811,0.00009647377,0.000370699,0.0001322257,0.0002456992,0.0002738114],"domain_scores_gemma":[0.998804,0.00007875244,0.0001988093,0.0008383084,0.00004999212,0.00003015411],"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":[0.0009199891,0.00008764042,0.001093734,0.000492933,0.001022764,0.00001973706,0.005374982,0.9415717,0.003839024,0.01158368,0.003762638,0.03023118],"study_design_scores_gemma":[0.005200006,0.002027395,0.2251239,0.001324344,0.0004244217,0.000008452241,0.04133369,0.6036814,0.06618282,0.002868805,0.04965205,0.002172757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8293179,0.0000539182,0.02261044,0.000150616,0.0001989776,0.0001053154,0.00001100821,0.0001668542,0.1473849],"genre_scores_gemma":[0.9937503,0.00004184884,0.004990635,0.00001491198,0.00005965535,0.000005992188,0.000005843821,0.0000431638,0.001087695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3378903,"threshold_uncertainty_score":0.9820768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01660852556553652,"score_gpt":0.2529737881791002,"score_spread":0.2363652626135637,"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."}}