{"id":"W7122603626","doi":"10.32996/jcsts.2026.5.1.7","title":"AI-Enhanced Sustainable Energy Management and Policy Recommendations for the U.S. Power Sector","year":2025,"lang":"","type":"article","venue":"Frontiers in Computer Science and Artificial Intelligence","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Sustainability; Demand forecasting; Context (archaeology); Renewable energy; Energy management; Smart grid; Electricity; Demand management; Energy policy; Electricity generation","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":[0.001098482,0.0002627174,0.0002505454,0.0008285052,0.001209639,0.0007572052,0.0005843351,0.00008497033,0.000007368144],"category_scores_gemma":[0.00008308166,0.0002356827,0.0000477521,0.002311982,0.0007323029,0.0005383288,0.0004425017,0.0002349401,6.194885e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002305347,"about_ca_system_score_gemma":0.0002092746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002007733,"about_ca_topic_score_gemma":0.00006271221,"domain_scores_codex":[0.9978302,0.00003517092,0.0004987649,0.0006226866,0.000210217,0.0008029771],"domain_scores_gemma":[0.9990729,0.0002168308,0.00006238562,0.0003277951,0.0002056628,0.0001144109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002057609,0.00003167879,0.00005140127,0.00009379773,0.00003793697,0.000002770066,0.001546835,0.02398521,0.00004770125,0.2712768,0.003612394,0.6992929],"study_design_scores_gemma":[0.00006747667,0.00007743405,0.00009811714,0.000247214,0.00002304049,0.000001561025,0.002363757,0.8569633,0.00710673,0.08505788,0.047707,0.0002864989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001002323,0.002413533,0.9852821,0.005686551,0.004236228,0.0003680369,0.00000589436,0.00003869475,0.0009667018],"genre_scores_gemma":[0.9531923,0.002515733,0.04144432,0.00166517,0.0002793632,0.00009439955,0.00000207813,0.00001803672,0.0007886097],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.95219,"threshold_uncertainty_score":0.9610861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01641132009360267,"score_gpt":0.2664521766512264,"score_spread":0.2500408565576238,"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."}}