{"id":"W3189926550","doi":"10.1016/j.ijheatmasstransfer.2021.121757","title":"Charging optimization of multi-tube latent heat storage comprising composite aluminum foam/nano-enhanced coconut oil","year":2021,"lang":"en","type":"article","venue":"International Journal of Heat and Mass Transfer","topic":"Phase Change Materials Research","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"University of New South Wales","keywords":"Materials science; Thermal energy storage; Latent heat; Phase-change material; Taguchi methods; Composite material; Thermal; Metal foam; Thermal conductivity; Composite number; Tube (container); Porosity; Thermodynamics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001844292,0.0001278347,0.0002770181,0.0001827551,0.00003281791,0.00007977124,0.0001499586,0.00005895824,0.0001463431],"category_scores_gemma":[0.00001111848,0.0001240531,0.00008749648,0.00007248556,0.0000372128,0.0002534821,0.00002028055,0.0001540811,0.000001393633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009846935,"about_ca_system_score_gemma":0.00003382732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000107593,"about_ca_topic_score_gemma":0.000007013254,"domain_scores_codex":[0.9988818,0.00005147377,0.0003979842,0.0001045265,0.0004008931,0.0001633358],"domain_scores_gemma":[0.9993021,0.00005115074,0.00001821814,0.00006848614,0.0004695042,0.00009053935],"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":[0.0000769636,0.00005034879,0.0001304054,0.00008618437,0.000162487,0.00008696898,0.0004060305,0.189955,0.8080635,0.00001181783,0.00001567833,0.0009546521],"study_design_scores_gemma":[0.002071106,0.00004109761,0.000286018,0.0003930201,0.00002729553,0.0001353616,0.00007507668,0.1781296,0.8183907,0.000009461766,0.0003143006,0.000126911],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.738984,0.001352302,0.2581332,0.0003770223,0.0008946237,0.00004298883,0.00004451657,0.00001762368,0.0001536967],"genre_scores_gemma":[0.9949409,0.001895197,0.002857124,0.00003884544,0.0001706799,0.000002794687,0.00002913092,0.00002529627,0.00004007166],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2559569,"threshold_uncertainty_score":0.505874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02526715317958161,"score_gpt":0.2737886135637533,"score_spread":0.2485214603841717,"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."}}