{"id":"W3003181969","doi":"10.1615/jpormedia.2020026859","title":"HEAT ENHANCEMENT USING ALUMINUM METAL FOAM: EXPERIMENTAL AND NUMERICAL APPROACH","year":2020,"lang":"en","type":"article","venue":"Journal of Porous Media","topic":"Heat and Mass Transfer in Porous Media","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Metal foam; Heat sink; Materials science; Pressure drop; Liquid metal; Heat transfer; Computer cooling; Thermal; Aluminium; Heat transfer enhancement; Electronics; Composite material; Performance enhancement; Mechanics; Mechanical engineering; Heat transfer coefficient; Thermodynamics; Thermal management of electronic devices and systems","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0005393843,0.0002868295,0.0003557023,0.0004906726,0.0003374784,0.0002574057,0.0004039819,0.0004772061,0.00160202],"category_scores_gemma":[0.0006543735,0.0001380754,0.0002372181,0.0006350538,0.0005485822,0.0002889291,0.0002413759,0.0003273321,0.0001608486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002169152,"about_ca_system_score_gemma":0.0001326164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007979038,"about_ca_topic_score_gemma":0.0004934825,"domain_scores_codex":[0.9996927,0.00005025063,0.0000176041,0.00004730543,0.0001316181,0.00006058962],"domain_scores_gemma":[0.9995989,0.0001868823,0.0000613107,0.00004909489,0.00009067912,0.00001308959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002496786,0.0002388169,0.0007798384,0.0002629578,0.00000693844,0.00009060681,0.0002201375,0.00669519,0.9842334,0.0006178621,0.0001156607,0.006488788],"study_design_scores_gemma":[0.00002533629,0.0007163812,0.001726215,0.00001371101,0.0000132304,0.00006731224,0.00009060564,0.02624082,0.9700695,0.0001215093,0.0008968342,0.00001864961],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906688,0.0003949632,0.005933803,0.00003334586,0.00001692519,0.00006065789,0.0001860905,0.0001052616,0.002600165],"genre_scores_gemma":[0.9933447,0.0002207232,0.005913773,0.000005574354,0.000006545771,0.00004470332,0.00004303641,0.000006893316,0.0004141164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00160202,"threshold_uncertainty_score":0.005359292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03037453432264479,"score_gpt":0.2468572029210515,"score_spread":0.2164826685984068,"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."}}