{"id":"W2144966277","doi":"10.1002/er.1951","title":"Performance assessment of thermal management systems for electric and hybrid electric vehicles","year":2012,"lang":"en","type":"article","venue":"International Journal of Energy Research","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Refrigerant; Coolant; Automotive engineering; Electric vehicle; Battery (electricity); Nuclear engineering; Exergy; Electric-vehicle battery; Operating temperature; Environmental science; Engineering; Electrical engineering; Mechanical engineering; Gas compressor; Process engineering; Thermodynamics; Physics","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":[0.001054809,0.00008413229,0.0001529233,0.0009373841,0.00004113537,0.00003709078,0.0005288381,0.00003895794,0.000007497034],"category_scores_gemma":[0.00005250133,0.00007203042,0.00004333325,0.0002609665,0.0000422681,0.0003052264,0.0001142715,0.0003017768,7.410232e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002749928,"about_ca_system_score_gemma":0.00003359679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004195329,"about_ca_topic_score_gemma":1.832819e-7,"domain_scores_codex":[0.9982508,0.00005023388,0.0003279392,0.0000767917,0.0009016276,0.0003925958],"domain_scores_gemma":[0.9988808,0.0002549439,0.00007827076,0.000110667,0.0006072067,0.00006812569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003400556,0.0003589302,0.03877757,0.0005002427,0.001509084,0.00006591994,0.0000532204,0.08314292,0.4144949,0.02274476,0.002958788,0.4350536],"study_design_scores_gemma":[0.002115455,0.001138726,0.07917936,0.0003337578,0.00003047701,0.0004445181,0.0002132753,0.5806851,0.310716,0.0007993392,0.02397692,0.0003670085],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9837489,0.00303989,0.01044219,0.00008240479,0.0002699126,0.0001058544,0.000003545334,0.00002058609,0.002286694],"genre_scores_gemma":[0.9932896,0.005333919,0.000963426,0.00000391786,0.0002191037,0.00003566474,0.000001781132,0.00002010769,0.0001324103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4975422,"threshold_uncertainty_score":0.2937315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03233051497317986,"score_gpt":0.3508488248519506,"score_spread":0.3185183098787707,"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."}}