{"id":"W2317888906","doi":"10.11159/ijmem.2012.011","title":"Thermal Management Analysis of a Lithium-Ion Battery Pack using Flow Network Approach","year":2012,"lang":"en","type":"article","venue":"International Journal of Mechanical Engineering and Mechatronics","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Battery pack; Battery (electricity); Nuclear engineering; Coolant; Materials science; Heat transfer; Lithium-ion battery; Automotive engineering; Thermal; Power (physics); Electrical engineering; Mechanical engineering; Engineering; Mechanics; Thermodynamics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001088387,0.0002625313,0.0002169642,0.0003406711,0.0002419503,0.0002820615,0.0002719388,0.0002649449,0.001369752],"category_scores_gemma":[0.0002197381,0.0001553185,0.0002440768,0.0001864633,0.0002194289,0.0006678543,0.0001444013,0.000136678,0.0001123528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000472987,"about_ca_system_score_gemma":0.0002946328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003596759,"about_ca_topic_score_gemma":0.002836094,"domain_scores_codex":[0.9999729,0.000006939194,0.000001085672,0.000005441288,0.000009498294,0.00000410831],"domain_scores_gemma":[0.9999417,0.00002694603,0.000009129563,0.000002758245,0.00001640309,0.000003000678],"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":[0.00005796979,0.00003474373,0.0009885333,0.00004702235,0.000008755052,0.00004678144,0.00003485777,0.970197,0.0194219,0.001487907,0.0001314949,0.007543063],"study_design_scores_gemma":[0.000001085142,0.00001206889,0.0001547563,0.000001148247,0.000001625432,0.000003231155,0.000004523063,0.9982439,0.001351216,0.0001384005,0.00008673884,0.000001255818],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6824107,0.0003807684,0.3052967,0.0001215008,0.00003072488,0.0001007764,0.0001534251,0.0003562494,0.01114911],"genre_scores_gemma":[0.9912935,0.0001399099,0.005936073,0.000008421589,0.000003501135,0.00004169783,0.00005682809,0.00001328489,0.002506661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003596759,"threshold_uncertainty_score":0.007151663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01594958859771767,"score_gpt":0.2540009147189035,"score_spread":0.2380513261211858,"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."}}