{"id":"W1907818491","doi":"10.1016/j.apenergy.2015.09.092","title":"Particle-filtering-based estimation of maximum available power state in Lithium-Ion batteries","year":2015,"lang":"en","type":"article","venue":"Applied Energy","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":119,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"State of charge; Battery (electricity); State of health; Particle filter; Lithium-ion battery; Energy storage; Power (physics); Lithium (medication); Computer science; Gaussian; Engineering; Control theory (sociology); Electrical engineering; Filter (signal processing); Chemistry","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":[0.0001192395,0.000130986,0.000171976,0.000134981,0.00001276637,0.00001624752,0.0001737261,0.00007156296,0.00007238749],"category_scores_gemma":[0.00002692562,0.0001366356,0.00001608415,0.0003185943,0.00007509226,0.0001217027,0.00007020379,0.0001099764,0.00006198009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001158327,"about_ca_system_score_gemma":0.00002335337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005874305,"about_ca_topic_score_gemma":0.00003853879,"domain_scores_codex":[0.999061,0.00001091711,0.0002463145,0.0001655228,0.0001987148,0.0003175483],"domain_scores_gemma":[0.999516,0.00003969402,0.00003072416,0.0003280055,0.00002933636,0.00005626672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000539679,0.00003359868,0.0001443805,0.00003888981,0.000007504336,0.000006552027,0.0000963606,0.9206958,0.06036318,0.0009047099,0.0006481878,0.01700683],"study_design_scores_gemma":[0.0006188917,0.00007639398,0.0001340274,0.00002108153,0.000001684319,9.540761e-7,0.00006969667,0.1360417,0.8506056,0.007124532,0.005120168,0.0001852908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7690212,0.0001251837,0.2230951,0.00007568961,0.0001149897,0.0001189023,0.000007958921,0.0005557215,0.006885257],"genre_scores_gemma":[0.9948915,0.00001502375,0.004805159,0.00003170201,0.000005934137,0.00009144504,0.00001282038,0.00003454359,0.0001118869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7902424,"threshold_uncertainty_score":0.5571839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01967098890663679,"score_gpt":0.2396512458230902,"score_spread":0.2199802569164535,"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."}}