{"id":"W4415169573","doi":"10.3390/pr13103267","title":"Optimal Configuration of Transformer–Energy Storage Deeply Integrated System Based on Enhanced Q-Learning with Hybrid Guidance","year":2025,"lang":"en","type":"article","venue":"Processes","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"Natural Science Foundation of Shaanxi Province","keywords":"Convergence (economics); Sizing; Reduction (mathematics); Dual (grammatical number); Grid; Electric power system; Power (physics); Optimization problem; Energy storage","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003254935,0.000611003,0.0006895001,0.0003264769,0.0003243245,0.0007239025,0.0005920254,0.0005951186,0.001574363],"category_scores_gemma":[0.0006125155,0.0003198817,0.0003686195,0.0003177535,0.0004535234,0.0005881481,0.0006715729,0.0004214086,0.0001626623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005134473,"about_ca_system_score_gemma":0.001020386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006091257,"about_ca_topic_score_gemma":0.005999155,"domain_scores_codex":[0.9998465,0.00003766694,0.000007889294,0.00003611677,0.0000392607,0.00003264908],"domain_scores_gemma":[0.9998167,0.00007322471,0.00003839938,0.00001094315,0.00004021539,0.00002064321],"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":[0.00003914827,0.00001876392,0.0004155787,0.00002364903,0.00001090359,0.00004588316,0.00002775025,0.9794526,0.001403188,0.001842122,0.0002853972,0.01643491],"study_design_scores_gemma":[0.000006729992,0.00001867208,0.00005612754,0.000001460934,0.000002961424,0.000006600093,0.000004849822,0.9990591,0.0001829922,0.0005571777,0.0001013713,0.000001879414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07772209,0.000205088,0.9156103,0.0001309832,0.00002681238,0.00008352307,0.00004157133,0.0002409088,0.005938789],"genre_scores_gemma":[0.9518101,0.00006955639,0.04663669,0.00003706219,0.000008001414,0.00006140427,0.00003902281,0.00001470489,0.001323421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006091257,"threshold_uncertainty_score":0.0121116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004504805511890982,"score_gpt":0.204964908784346,"score_spread":0.200460103272455,"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."}}