{"id":"W4381613794","doi":"10.11159/ffhmt23.132","title":"Multiphase Flow Modelling Using Surrogate Model","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Surrogate model; Multiphase flow; Flow (mathematics); Machine learning; Mechanics","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":[0.0009931306,0.0006019558,0.001030548,0.0008006876,0.0003632578,0.001605351,0.0007955229,0.001729299,0.002161832],"category_scores_gemma":[0.002806732,0.0005205639,0.001101899,0.0008117437,0.0005201207,0.00143298,0.001105824,0.001101092,0.0005065063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004192856,"about_ca_system_score_gemma":0.0008054774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001594901,"about_ca_topic_score_gemma":0.0009623858,"domain_scores_codex":[0.999572,0.000181826,0.00002846775,0.000046297,0.0001417933,0.00002961765],"domain_scores_gemma":[0.9990706,0.0005240781,0.00009664096,0.0001084058,0.0001623802,0.00003807785],"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":[0.00003040073,0.00001742736,0.0001291779,0.00002920965,0.000009572048,0.00002595538,0.00001012462,0.9869342,0.0008844854,0.006196742,0.0001334432,0.005599203],"study_design_scores_gemma":[0.00000179751,0.000005065568,0.00001423909,0.000002536259,7.246709e-7,0.000004002954,9.051738e-7,0.9986071,0.0001475145,0.001047579,0.0001671869,0.000001442928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01549569,0.000249789,0.9797996,0.0001299086,0.00005701237,0.00004249137,0.0001301822,0.0002617786,0.003833453],"genre_scores_gemma":[0.7759458,0.0008019591,0.2144839,0.0000765291,0.00005072108,0.0003471629,0.0006914813,0.0001693714,0.007433118],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002161832,"threshold_uncertainty_score":0.00723207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2163490309616363,"score_gpt":0.3782014723938651,"score_spread":0.1618524414322288,"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."}}