{"id":"W2321522561","doi":"10.1504/ijesms.2016.075544","title":"Development of a three-dimensional icing simulation code in the NSMB flow solver","year":2016,"lang":"en","type":"article","venue":"International Journal of Engineering Systems Modelling and Simulation","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Compute Canada","keywords":"Icing; Airfoil; Solver; Aerodynamics; Computer science; Block (permutation group theory); Computational science; Simulation; Aerospace engineering; Mechanics; Engineering; Mathematics; Physics; Geometry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003186815,0.0005505602,0.0006213866,0.000387242,0.0003903513,0.0004794119,0.001326458,0.0005290348,0.004553943],"category_scores_gemma":[0.000686314,0.0002959227,0.0004137699,0.0003949574,0.0002727198,0.000329697,0.0006987153,0.0008651101,0.001260186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004169384,"about_ca_system_score_gemma":0.001343996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007394455,"about_ca_topic_score_gemma":0.00327489,"domain_scores_codex":[0.9997849,0.00002535919,0.00001102918,0.00001711765,0.0001240373,0.00003748034],"domain_scores_gemma":[0.9997316,0.00004594698,0.00002169478,0.00004298106,0.0001219721,0.00003589527],"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":[0.0001595498,0.0002212917,0.003928999,0.0002734566,0.00005425324,0.0002760612,0.0001852933,0.8684325,0.04946567,0.01542524,0.006742344,0.05483532],"study_design_scores_gemma":[0.00003428978,0.00002373188,0.0005387609,0.00001340285,0.000004869547,0.00003161882,0.00001212999,0.9834288,0.006099897,0.0005119331,0.009289341,0.00001118996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1579916,0.0003325751,0.7825645,0.0003239111,0.0002246188,0.0008931538,0.003398854,0.01240568,0.04186503],"genre_scores_gemma":[0.47548,0.0003864633,0.5028993,0.0001379063,0.00005657091,0.001555667,0.005113354,0.001793289,0.01257745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007394455,"threshold_uncertainty_score":0.01523447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02871680359495505,"score_gpt":0.2424671127304132,"score_spread":0.2137503091354581,"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."}}