{"id":"W7117367618","doi":"10.2139/ssrn.5976040","title":"QLoRA-Enhanced Prompt-Driven DeepSeek Large Language Model for State of Charge Estimation of Containerized Lithium-Ion Battery Energy Storage Systems","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"State of charge; Estimator; Robustness (evolution); Generalization; Energy storage; State estimator; Stability (learning theory); Computer data 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":[0.0007282381,0.001132274,0.0009692624,0.0004892221,0.0004028445,0.0009752347,0.001506646,0.001303455,0.006444926],"category_scores_gemma":[0.002906752,0.0005164883,0.0009591431,0.0005065398,0.0002953911,0.001697673,0.001133531,0.002093817,0.003758075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006131977,"about_ca_system_score_gemma":0.001603043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01817935,"about_ca_topic_score_gemma":0.03436157,"domain_scores_codex":[0.9996803,0.000088332,0.0000168064,0.0001036744,0.00005967871,0.00005116839],"domain_scores_gemma":[0.9993743,0.00036582,0.00003123086,0.00008156343,0.0001119225,0.00003519809],"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":[0.001585367,0.0005310737,0.005137789,0.0005476896,0.0004370076,0.0005114111,0.0001883675,0.6041707,0.01965642,0.008983757,0.07821116,0.2800393],"study_design_scores_gemma":[0.0000282871,0.00002284206,0.0001855504,0.000004814234,0.00001001397,0.00001293785,0.000008986403,0.9951509,0.001558651,0.002065585,0.0009403805,0.00001104864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1583853,0.002726006,0.7165627,0.001889591,0.0008371512,0.0001985708,0.027615,0.08646479,0.005320887],"genre_scores_gemma":[0.7685592,0.0004902824,0.1722332,0.0008496669,0.0002690785,0.0003994838,0.04394015,0.002740604,0.01051828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01817935,"threshold_uncertainty_score":0.03614706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01060022452295007,"score_gpt":0.2726892097077372,"score_spread":0.2620889851847872,"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."}}