{"id":"W4408139017","doi":"10.1016/j.ress.2025.110980","title":"Early prediction of battery life using an interpretable health indicator with evolutionary computing","year":2025,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Battery (electricity); Evolutionary algorithm; Computer science; Artificial intelligence; Machine learning","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":[0.0003980641,0.0006227998,0.0005103399,0.0007766119,0.0002021479,0.0005865056,0.0004647045,0.0005595344,0.0008520546],"category_scores_gemma":[0.002050369,0.0001492804,0.000325362,0.0004139338,0.0002009455,0.0005640034,0.0004217325,0.0005390887,0.000226315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003127637,"about_ca_system_score_gemma":0.0002780439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001878241,"about_ca_topic_score_gemma":0.001971618,"domain_scores_codex":[0.9998146,0.00003396135,0.0000114203,0.00005435959,0.00005834224,0.00002729402],"domain_scores_gemma":[0.9992998,0.0003467129,0.00008443886,0.00004728575,0.0001890042,0.00003265728],"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":[0.0006053247,0.0004241861,0.0547964,0.0001682234,0.0001110459,0.000476068,0.0001560014,0.5443646,0.04431741,0.003743633,0.001704645,0.3491324],"study_design_scores_gemma":[0.000004565777,0.00007058324,0.004427686,0.000008620327,0.00001334235,0.00003804152,0.00001073195,0.9907183,0.003493249,0.001046641,0.0001600449,0.000008167907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3653411,0.0004427774,0.6299042,0.000226863,0.00009607785,0.00006384735,0.0002528717,0.0009349109,0.002737327],"genre_scores_gemma":[0.9638767,0.00006435195,0.03512804,0.00003392811,0.00001465629,0.00002396196,0.0001300158,0.00001882093,0.0007094753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001878241,"threshold_uncertainty_score":0.003734648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008640588198193013,"score_gpt":0.2352036416954667,"score_spread":0.2265630534972737,"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."}}