{"id":"W4293205431","doi":"10.2139/ssrn.4047634","title":"An Interface-Driven Adaptive Variational Procedure for Fully Eulerian Fluid-Structure Interaction Via Phase-Field Modeling","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Solidification and crystal growth phenomena","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Eulerian path; Fluid–structure interaction; Interface (matter); Phase (matter); Mechanics; Computer science; Field (mathematics); Classical mechanics; Statistical physics; Physics; Mathematics; Finite element method; Thermodynamics; Theoretical physics; Lagrangian; Bubble","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007455617,0.0001717287,0.0001693962,0.0001308228,0.0007602418,0.0001257594,0.0004325741,0.00005670367,0.001092071],"category_scores_gemma":[0.0000459004,0.0001683329,0.00008399286,0.0001545437,0.00001610419,0.000533093,0.00005284671,0.0009606228,0.000007902167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001062463,"about_ca_system_score_gemma":0.001162046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002005978,"about_ca_topic_score_gemma":0.00008681935,"domain_scores_codex":[0.9977863,0.0001494782,0.0003738375,0.0003332375,0.0003423458,0.001014803],"domain_scores_gemma":[0.9992583,0.00004221205,0.0002535838,0.0001630578,0.0001813532,0.0001014497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001359866,0.0002178893,0.00001069207,0.000008466482,0.00006101426,6.130573e-7,0.001390702,0.09375161,0.8608609,0.03884543,0.00009600753,0.003396762],"study_design_scores_gemma":[0.002384884,0.003739092,0.000008431592,0.00001318582,0.00006288549,0.0006124364,0.01199617,0.7691438,0.01700963,0.1937884,0.0008315363,0.0004095511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4482884,0.000130979,0.5500706,0.0005491203,0.0005173117,0.0002760184,0.00004609931,0.00004964175,0.00007181825],"genre_scores_gemma":[0.9977611,0.00001715134,0.001179969,0.0002576009,0.0005111198,0.00008548277,0.00004452073,0.00003159833,0.0001114575],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8438513,"threshold_uncertainty_score":0.9998211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01646759462211012,"score_gpt":0.2887099860884878,"score_spread":0.2722423914663777,"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."}}