{"id":"W2331994911","doi":"10.2514/6.2014-0913","title":"NSMB contribution to the 2nd High Lift Prediction Workshop","year":2014,"lang":"en","type":"article","venue":"52nd Aerospace Sciences Meeting","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"Lift (data mining); Computer science; Machine learning","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":[0.002073001,0.0007913241,0.0006469283,0.0005741305,0.0009293256,0.001405509,0.0008395291,0.0007147719,0.0234465],"category_scores_gemma":[0.001835144,0.0002263878,0.0006899346,0.0003045329,0.0003104113,0.0006397768,0.002324468,0.001224893,0.00982457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001171072,"about_ca_system_score_gemma":0.002759925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004920301,"about_ca_topic_score_gemma":0.007477091,"domain_scores_codex":[0.9986044,0.0001716444,0.00002566095,0.00009169196,0.0009147419,0.0001919326],"domain_scores_gemma":[0.9983228,0.0001093068,0.00003169355,0.0001629759,0.00096601,0.0004072746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001923411,0.0006344648,0.004339803,0.000295355,0.0000471507,0.001150704,0.0004143787,0.06547031,0.03586652,0.01178094,0.525121,0.3529558],"study_design_scores_gemma":[0.0002176571,0.0008523442,0.007035422,0.0001658756,0.00003226372,0.0004696765,0.0002871027,0.2267082,0.03741793,0.006431498,0.720284,0.00009802766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2790228,0.003401186,0.1757224,0.02819002,0.04621172,0.0009367468,0.007844534,0.007460139,0.4512105],"genre_scores_gemma":[0.4552255,0.001103065,0.04714444,0.0007588629,0.004001172,0.0002915824,0.01108078,0.001640727,0.4787539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0234465,"threshold_uncertainty_score":0.07843637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006150070529987212,"score_gpt":0.2017736075493892,"score_spread":0.195623537019402,"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."}}