{"id":"W7133556799","doi":"10.1109/icpee65973.2025.11411039","title":"A Hybrid AI-ML Framework for Predictive Maintenance and Load Forecasting in Smart Grid Infrastructures","year":2025,"lang":"","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Smart grid; Predictive maintenance; Context (archaeology); Demand forecasting; Key (lock)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005001377,0.000626513,0.0006969173,0.0003542051,0.0002458197,0.0002102382,0.0002893421,0.0003570744,0.00009514559],"category_scores_gemma":[0.001525003,0.0006305806,0.0001630785,0.0005414145,0.000162461,0.0003615475,0.0002384425,0.001001021,0.000001890602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003573903,"about_ca_system_score_gemma":0.0002249754,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002557101,"about_ca_topic_score_gemma":0.0003300231,"domain_scores_codex":[0.9969268,0.00004584816,0.000891129,0.0007667326,0.000229708,0.001139722],"domain_scores_gemma":[0.9980286,0.001115718,0.00012511,0.0003630483,0.0001888199,0.0001787032],"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":[0.001416249,0.0001545435,0.06766386,0.004870031,0.00109884,0.0001525484,0.005851639,0.4450511,0.0004739407,0.2164621,0.02359179,0.2332133],"study_design_scores_gemma":[0.001825274,0.0002292899,0.006797322,0.005299716,0.0001059734,0.0000479144,0.0004079609,0.8380399,0.002964479,0.1310517,0.01245832,0.000772115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1487816,0.004155603,0.8112996,0.0005571024,0.004962406,0.001051949,0.0002592254,0.0002829487,0.02864954],"genre_scores_gemma":[0.9553332,0.0002812252,0.04228383,0.0006398213,0.0005030171,0.00014455,0.00002041806,0.00007749177,0.0007164401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8065516,"threshold_uncertainty_score":0.9996145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008535378544377617,"score_gpt":0.2298421164037657,"score_spread":0.2213067378593881,"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."}}