{"id":"W4407458121","doi":"10.1109/tim.2025.3541804","title":"A Hybrid Data-Driven Granular Model for Battery Remaining Useful Life Prediction","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Battery (electricity); Data modeling; Computer science; Reliability engineering; Engineering; Physics; Power (physics)","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":[0.0009922449,0.0008618458,0.0009604,0.001400052,0.0003383895,0.002089373,0.00160007,0.0007857008,0.001192102],"category_scores_gemma":[0.003544497,0.0003416242,0.001050167,0.001530612,0.0005637323,0.002340076,0.001100835,0.000942303,0.0002583909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061393,"about_ca_system_score_gemma":0.0006973812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009061055,"about_ca_topic_score_gemma":0.006375449,"domain_scores_codex":[0.9993721,0.0001011627,0.0000653617,0.0001616525,0.0002246278,0.0000751671],"domain_scores_gemma":[0.9989624,0.0004896563,0.0001535248,0.0001363253,0.0002066279,0.00005146131],"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":[0.0001404279,0.00006242196,0.003137732,0.0001065018,0.00005705976,0.000181848,0.00009314293,0.9382855,0.001677345,0.01236312,0.001508552,0.04238636],"study_design_scores_gemma":[0.000004215273,0.00001064466,0.0003039436,0.000008011612,0.00001113447,0.00001550857,0.00001087041,0.9941698,0.0002270957,0.004969713,0.0002615858,0.000007498502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05937155,0.0008441323,0.93366,0.000506192,0.00008200292,0.00008357045,0.001163206,0.00105873,0.003230739],"genre_scores_gemma":[0.9290046,0.0006057552,0.06761525,0.0001338426,0.00005486712,0.0001633392,0.001028056,0.00006415429,0.001330048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009061055,"threshold_uncertainty_score":0.01801664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08428870576422998,"score_gpt":0.295402769904385,"score_spread":0.211114064140155,"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."}}