{"id":"W3135327858","doi":"10.4271/2021-01-0759","title":"Comparative Study between Equivalent Circuit and Recurrent Neural Network Battery Voltage Models","year":2021,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Equivalent circuit; Battery (electricity); Computer science; Voltage; Artificial neural network; Electrical engineering; Engineering; Artificial intelligence; 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":[0.0005948535,0.0007588776,0.0005751761,0.0004113992,0.0001769969,0.0006891664,0.0008578153,0.0007633545,0.001332349],"category_scores_gemma":[0.002470202,0.0002680593,0.0005487007,0.000300197,0.0002009248,0.001226644,0.0002535557,0.0004941226,0.0003330774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007282298,"about_ca_system_score_gemma":0.0004341516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01342848,"about_ca_topic_score_gemma":0.009928067,"domain_scores_codex":[0.9998158,0.00006394555,0.00001363509,0.00004241948,0.00004322025,0.00002105921],"domain_scores_gemma":[0.99905,0.00063928,0.0000690055,0.00006616055,0.0001586514,0.00001696163],"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":[0.00009985408,0.0000412435,0.0008068996,0.00006014008,0.00004276491,0.00005228056,0.00003261578,0.9677064,0.001602082,0.001205965,0.0003059593,0.02804365],"study_design_scores_gemma":[0.000001079334,0.00001290091,0.0001006164,0.000001759447,0.000004393006,0.000004762127,0.000002135369,0.999472,0.0002062109,0.0001415249,0.00005058415,0.000002054784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5337134,0.002601949,0.4461564,0.0005132585,0.00009940675,0.00006792664,0.0003754381,0.002454321,0.01401798],"genre_scores_gemma":[0.9851916,0.0003693307,0.01198697,0.00004204417,0.00001376184,0.00004001115,0.000256671,0.00006052306,0.002039009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01342848,"threshold_uncertainty_score":0.02670062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05824944589493507,"score_gpt":0.3072210540431146,"score_spread":0.2489716081481795,"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."}}