{"id":"W4416110345","doi":"10.1016/j.est.2025.119378","title":"A weighted ensemble approach for interpretable state of health estimation of lithium-ion batteries based on generalized additive models","year":2025,"lang":"en","type":"article","venue":"Journal of Energy Storage","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Western University","keywords":"Additive model; State (computer science); Estimation; Generalized additive model; State of health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009102777,0.001256429,0.001018402,0.0007343374,0.0003331088,0.0008244158,0.001149993,0.000749164,0.0009831828],"category_scores_gemma":[0.002588011,0.0004583219,0.001277952,0.0006371254,0.000360385,0.001095916,0.0008966373,0.001300168,0.0003029486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003710245,"about_ca_system_score_gemma":0.0004926031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005438525,"about_ca_topic_score_gemma":0.006433904,"domain_scores_codex":[0.9995839,0.0001225696,0.00002910342,0.0001144497,0.0001050702,0.00004487248],"domain_scores_gemma":[0.9994093,0.000287147,0.00006682192,0.00005296748,0.0001624929,0.00002126587],"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":[0.00007102061,0.00004287674,0.001592617,0.00007069341,0.0001471625,0.00008671903,0.0001050498,0.8604075,0.004074052,0.005501867,0.0008752897,0.1270252],"study_design_scores_gemma":[0.000001127559,0.0000125933,0.0001280807,0.000003856903,0.00001273095,0.000009168757,0.000004054717,0.9976746,0.0003215545,0.001644751,0.0001827392,0.000004755613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01075408,0.000240128,0.9880968,0.00006984604,0.00002450441,0.00001279128,0.00004351552,0.0002113826,0.000547004],"genre_scores_gemma":[0.7796084,0.00088682,0.2148476,0.0002038673,0.0001361474,0.0001976683,0.0005312858,0.0001319721,0.003456144],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005438525,"threshold_uncertainty_score":0.01081377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01752788930955886,"score_gpt":0.2748193799735409,"score_spread":0.257291490663982,"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."}}