{"id":"W2998112846","doi":"10.2514/6.2020-1799","title":"Development of an Anti-Icing Computational Fluid Dynamics Code","year":2020,"lang":"en","type":"article","venue":"AIAA Scitech 2020 Forum","topic":"Icing and De-icing Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Icing; Computational fluid dynamics; Aerospace engineering; MATLAB; Accretion (finance); Stall (fluid mechanics); Source code; Icing conditions; Computer science; Software; Environmental science; Mechanics; Marine engineering; Engineering; Meteorology; Physics; Operating system; Astrophysics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005737722,0.0005075843,0.0005135867,0.000375014,0.0004780694,0.0007972448,0.001630122,0.0008943241,0.00722659],"category_scores_gemma":[0.002407774,0.0003076533,0.0005742,0.0003097529,0.0004423325,0.0006667563,0.001155331,0.001356083,0.001971301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005431304,"about_ca_system_score_gemma":0.002255037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005421767,"about_ca_topic_score_gemma":0.003598504,"domain_scores_codex":[0.9996759,0.00003887037,0.00002440767,0.00004154102,0.0001772813,0.00004194725],"domain_scores_gemma":[0.9991239,0.0002824213,0.00004339504,0.00006979892,0.0003957239,0.0000848917],"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":[0.0002880704,0.0002228047,0.004735384,0.0003633476,0.00009063631,0.0004517865,0.0002652516,0.7691707,0.02774522,0.03520881,0.02433577,0.1371222],"study_design_scores_gemma":[0.00006895115,0.00002877381,0.0003229813,0.00002363059,0.000006829094,0.00004264962,0.00001494946,0.9693378,0.007753466,0.002060537,0.02032254,0.0000168158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06968492,0.0002681665,0.8642957,0.001054851,0.0006445136,0.0007425377,0.002717317,0.01907608,0.04151588],"genre_scores_gemma":[0.2375831,0.0003286497,0.7382362,0.0003983159,0.0000934069,0.001580096,0.004498854,0.002108685,0.01517271],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00722659,"threshold_uncertainty_score":0.02417535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123672117144053,"score_gpt":0.2213342803009851,"score_spread":0.2089670685865798,"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."}}