{"id":"W3013086854","doi":"10.1109/tte.2020.2983846","title":"A Practical and Comprehensive Evaluation Method for Series-Connected Battery Pack Models","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Transportation Electrification","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China; Chongqing Postdoctoral Science Foundation","keywords":"Battery (electricity); Battery pack; Adaptability; Computer science; Series (stratigraphy); Identification (biology); Selection (genetic algorithm); Reliability engineering; Engineering; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001660386,0.0002055209,0.0002082788,0.0001732073,0.0001443209,0.00003309081,0.00008521411,0.0001831493,0.00003444264],"category_scores_gemma":[0.00002350543,0.000233504,0.00006523476,0.0005173347,0.00004755978,0.0006491337,2.921805e-8,0.00038234,0.000008669154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000108505,"about_ca_system_score_gemma":0.00006243888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003051906,"about_ca_topic_score_gemma":0.00002072552,"domain_scores_codex":[0.9985978,0.00007494741,0.000353149,0.0003992991,0.0003103907,0.0002644167],"domain_scores_gemma":[0.9990158,0.0003132908,0.00005911243,0.000196254,0.0003182895,0.00009724854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002722536,0.00004440307,0.000001323936,0.0001223814,0.00007820834,9.751354e-7,0.0004599842,0.4656775,0.4765143,0.0008969321,0.0001907051,0.05574109],"study_design_scores_gemma":[0.0006362738,0.0001985015,0.0001303283,0.000008303278,0.00007707965,0.000003637581,0.000170282,0.5486619,0.4481751,0.001587937,0.0001783426,0.0001722694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01407734,0.00005398935,0.9799601,0.003608046,0.00007970606,0.001380143,0.0001258675,0.0006851483,0.00002961112],"genre_scores_gemma":[0.9226825,0.0002561211,0.07577497,0.0001994983,0.00002293927,0.0008491918,0.0001511292,0.00005306405,0.00001061949],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9086051,"threshold_uncertainty_score":0.9522017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09675267167208572,"score_gpt":0.3486988671016519,"score_spread":0.2519461954295662,"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."}}