{"id":"W4313377423","doi":"10.1109/jestie.2022.3214060","title":"Model-Based Approach to Long Term Prediction of Battery Surface Temperature","year":2022,"lang":"en","type":"article","venue":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Office of Naval Research; U.S. Naval Research Laboratory; Natural Sciences and Engineering Research Council of Canada","keywords":"Battery (electricity); Reliability (semiconductor); Range (aeronautics); Heat generation; Lithium-ion battery; Computer science; Materials science; Automotive engineering; Engineering; Thermodynamics; Physics; Aerospace engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003939643,0.0001437379,0.0002952091,0.0004042386,0.00009301672,0.0000189228,0.0002882061,0.0001674656,0.000005080717],"category_scores_gemma":[0.000105646,0.0001504121,0.00004328475,0.001028507,0.00002566706,0.0001024012,0.00004166118,0.002060522,5.345407e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004445971,"about_ca_system_score_gemma":0.0002474084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001860014,"about_ca_topic_score_gemma":0.000003530731,"domain_scores_codex":[0.9985525,0.00007847673,0.0004880442,0.0001442155,0.000364257,0.000372524],"domain_scores_gemma":[0.9994972,0.00005585059,0.0001076867,0.0001534458,0.000126074,0.0000597971],"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":[0.00008763043,0.0000573268,0.004062371,0.00002676415,0.00003950197,0.000005725546,0.000111482,0.9457561,0.04499763,0.00002215936,0.0006884209,0.004144904],"study_design_scores_gemma":[0.003956196,0.001637126,0.001330688,0.0001517163,0.00005844836,0.0001200809,0.0002222296,0.883578,0.1064955,0.0003413644,0.001607182,0.0005014819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856656,0.0005931045,0.012886,0.0002194585,0.0003323882,0.0001744178,0.00001510638,0.00005156229,0.00006241545],"genre_scores_gemma":[0.998391,0.0001656141,0.001191859,0.00001885381,0.0001505106,0.000008080633,0.000006750943,0.00002559687,0.00004169845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0621781,"threshold_uncertainty_score":0.8952059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03199226876630425,"score_gpt":0.2604577521275779,"score_spread":0.2284654833612737,"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."}}