{"id":"W2783381751","doi":"10.2514/6.2018-0324","title":"Design and Testing of Conventional and 3-D Riblets","year":2018,"lang":"en","type":"article","venue":"2018  AIAA Aerospace Sciences Meeting","topic":"Mechanical Engineering and Vibrations Research","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"Air Force Research Laboratory; Langley Research Center","keywords":"Computer science; Reliability engineering; Engineering","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":[0.001068749,0.0004800041,0.0004330459,0.0004530933,0.0003096227,0.000866622,0.001860883,0.001199569,0.003605369],"category_scores_gemma":[0.001591671,0.0005005174,0.0004435593,0.0002779849,0.0006728484,0.0007254817,0.0007120567,0.0004552206,0.001661687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005833575,"about_ca_system_score_gemma":0.0006456809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002907637,"about_ca_topic_score_gemma":0.0004661053,"domain_scores_codex":[0.9988189,0.0001473292,0.00006028553,0.0002113366,0.0006456191,0.000116541],"domain_scores_gemma":[0.9981191,0.0003407178,0.0003344879,0.0005151139,0.0004920266,0.0001986606],"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":[0.001021235,0.0004258637,0.005874565,0.0005407275,0.0000675747,0.0006143656,0.0003405774,0.1444028,0.7530342,0.009307238,0.002123838,0.082247],"study_design_scores_gemma":[0.0002217874,0.006646174,0.01401697,0.00008569532,0.0000813072,0.0007856248,0.0001783863,0.3577041,0.591324,0.002109706,0.02670069,0.0001455776],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4726377,0.0004238144,0.5045645,0.0003543284,0.0002869225,0.0004327302,0.000479608,0.003245071,0.01757536],"genre_scores_gemma":[0.8342916,0.0001472287,0.1572281,0.0001355035,0.00002503182,0.0001992585,0.0003002045,0.000206692,0.007466219],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003605369,"threshold_uncertainty_score":0.01206118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05298089222760273,"score_gpt":0.2780915628924299,"score_spread":0.2251106706648272,"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."}}