{"id":"W3205916839","doi":"10.23977/jeis.2021.060203","title":"Thermal Optimizations and CFD Analysis of Finned Heat Sinks for Natural Convection","year":2021,"lang":"en","type":"article","venue":"Journal of Electronics and Information Science","topic":"Heat Transfer and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Heat sink; Computational fluid dynamics; Mechanics; Heat transfer coefficient; Heat transfer; Fin; Natural convection; Sink (geography); Convection; Convective heat transfer; Airflow; Thermodynamics; Materials science; Mechanical engineering; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002897686,0.00004046756,0.0001113607,0.0002985132,0.00008113603,0.00007065426,0.00003962248,0.00002386208,0.000005554906],"category_scores_gemma":[0.00005410038,0.00003507976,0.00003602407,0.0008372838,0.00003904379,0.001948467,0.000004473217,0.00006848616,4.45508e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003241934,"about_ca_system_score_gemma":0.0001148827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.33013e-7,"about_ca_topic_score_gemma":0.000002858277,"domain_scores_codex":[0.9994695,0.000005048728,0.000271469,0.00003096573,0.0001292118,0.00009383146],"domain_scores_gemma":[0.9993901,0.00003085954,0.00003556476,0.00003716244,0.0004694918,0.00003679241],"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":[0.00001106089,0.000005739004,0.0001238578,0.00002288662,0.0000620516,6.707141e-8,0.0006571789,0.9753416,0.01726417,0.002987508,0.00001256955,0.003511279],"study_design_scores_gemma":[0.0002689976,0.00005887821,0.003225362,0.000006497561,0.00009065083,0.00000874046,0.00009090564,0.9801073,0.01565464,0.00002472842,0.0004216591,0.00004166051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5454026,0.0007947362,0.4530777,0.0001764491,0.0001200232,0.00005704838,0.000006539062,0.000007407379,0.000357424],"genre_scores_gemma":[0.9959074,0.001175172,0.00284406,0.00005219738,0.000008443301,7.01139e-7,0.000008134825,0.000001595901,0.000002331847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4505047,"threshold_uncertainty_score":0.1430511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00468665355612074,"score_gpt":0.2190855878296654,"score_spread":0.2143989342735446,"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."}}