{"id":"W4229040203","doi":"10.1063/5.0091699","title":"A three-dimensional numerical model for the motion of liquid drops by the particle finite element method","year":2022,"lang":"en","type":"article","venue":"Physics of Fluids","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Energy; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Royal Commission for Jubail and Yanbu","keywords":"Physics; Mechanics; Finite element method; Deformation (meteorology); Drop (telecommunication); Dissipation; Boundary value problem; Numerical analysis; Particle (ecology); Classical mechanics; Particle-laden flows; Statistical physics; Two-phase flow; Mathematical analysis; Mechanical engineering; Thermodynamics; Flow (mathematics); Meteorology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008358724,0.00007333735,0.0001323288,0.000004785811,0.00024187,0.000008012454,0.000281475,0.00001194958,0.0001508772],"category_scores_gemma":[0.00003372034,0.00004649972,0.00009223189,0.0001302974,0.00008072008,0.00005365098,0.0001256261,0.00006264224,0.000003971064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002543575,"about_ca_system_score_gemma":0.00004402065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001012703,"about_ca_topic_score_gemma":0.000001474965,"domain_scores_codex":[0.9989859,0.000107334,0.00023827,0.0001581597,0.0003717947,0.0001384739],"domain_scores_gemma":[0.999063,0.0004266229,0.00008292915,0.0003124303,0.00009163354,0.00002336985],"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":[0.0001059342,0.0001613907,0.00001831436,0.000004635454,0.000008654442,1.975432e-8,0.0004710403,0.2684753,0.723049,0.006501187,0.0005220767,0.0006823969],"study_design_scores_gemma":[0.00015156,0.00008066009,0.00002207117,7.818946e-7,0.00001484172,1.749763e-7,0.00005039635,0.6232603,0.373274,0.003013723,0.00009685374,0.00003458319],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.440355,0.00008336785,0.5584336,0.0007615737,0.0000539739,0.0001844363,0.0001136764,0.00000853364,0.000005871509],"genre_scores_gemma":[0.9927331,0.000002119206,0.006824438,0.0002186233,0.00001912256,0.0001500227,0.00001082388,0.0000089501,0.00003280499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5523781,"threshold_uncertainty_score":0.1896204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04601425760328234,"score_gpt":0.2953649177186102,"score_spread":0.2493506601153279,"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."}}