{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006456769,0.0004729067,0.0003404913,0.000603657,0.0002945373,0.0005833966,0.0003995188,0.0002933863,0.001530059],"category_scores_gemma":[0.001066933,0.0001419739,0.0003216729,0.0003335766,0.0001850898,0.0006654473,0.0003769558,0.0002005497,0.0003144125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006015584,"about_ca_system_score_gemma":0.0002487696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001143008,"about_ca_topic_score_gemma":0.000986035,"domain_scores_codex":[0.9996581,0.00006467573,0.00002149163,0.00005386119,0.0001656662,0.00003621481],"domain_scores_gemma":[0.9996296,0.0001050865,0.0000419174,0.00002906852,0.0001775537,0.00001669612],"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":[0.002468962,0.0004494997,0.02370886,0.001155242,0.0001937504,0.000258027,0.0004408373,0.4426827,0.2826047,0.003432037,0.002198953,0.2404065],"study_design_scores_gemma":[0.00005564808,0.005708402,0.04824578,0.00006344359,0.0002069568,0.0002076226,0.0006532549,0.7032647,0.2314956,0.00120399,0.008820847,0.00007378729],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9590709,0.00127881,0.03077758,0.00009877894,0.0000553789,0.0001122177,0.0002284512,0.0002189806,0.008159054],"genre_scores_gemma":[0.9973983,0.0001509671,0.001421597,0.000005023938,0.000005480633,0.00002611698,0.000100642,0.00001079722,0.0008812006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001530059,"threshold_uncertainty_score":0.005118549,"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."}}