{"id":"W2781769144","doi":"10.2514/6.2018-0132","title":"Analysis of Unstructured Meshes from GMGW-1 / HiLiftPW-3","year":2018,"lang":"en","type":"article","venue":"2018  AIAA Aerospace Sciences Meeting","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Polygon mesh; Computer science; Computer graphics (images)","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":[],"consensus_categories":[],"category_scores_codex":[0.001225112,0.0002260757,0.0004338145,0.0004742446,0.0004598701,0.0003436538,0.002645376,0.0001165236,0.0000613152],"category_scores_gemma":[0.0004606412,0.0001771823,0.0001588004,0.004636848,0.001077036,0.0009030604,0.0006463242,0.000147965,0.00001572933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004803797,"about_ca_system_score_gemma":0.0001220562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001079179,"about_ca_topic_score_gemma":0.0004692814,"domain_scores_codex":[0.9973272,0.0001186847,0.0003967157,0.000839795,0.0008288714,0.0004887311],"domain_scores_gemma":[0.9981269,0.0002433279,0.0004761188,0.0007700826,0.0002727832,0.0001108453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004774838,0.00018023,0.1543629,0.00007770336,0.001179575,0.0000250822,0.02514827,0.000685464,0.6382439,0.07707388,0.007434635,0.09554057],"study_design_scores_gemma":[0.0003149371,0.0004077567,0.009571576,0.000268741,0.0003758052,0.00000587431,0.0006291472,0.2024466,0.747696,0.03648376,0.0008450104,0.0009547705],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7554253,0.002735547,0.2322664,0.001734913,0.001087219,0.0002355364,0.00002669431,0.001003234,0.005485176],"genre_scores_gemma":[0.5943538,0.000007285456,0.4053141,0.000156769,0.0000925724,0.000002513022,0.000001968437,0.000005436104,0.00006560144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2017612,"threshold_uncertainty_score":0.7225286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01449860256580975,"score_gpt":0.2803708158811365,"score_spread":0.2658722133153267,"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."}}