{"id":"W2783079751","doi":"10.2514/6.2018-0321","title":"Maturation of Direct Contactless Microfabrication for Application of Drag Reducing Riblets","year":2018,"lang":"en","type":"article","venue":"2018  AIAA Aerospace Sciences Meeting","topic":"Tribology and Lubrication Engineering","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Microsemi (Canada)","funders":"U.S. Department of Defense","keywords":"Microfabrication; Drag; Materials science; Computer science; Aerospace engineering; Engineering; Fabrication","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":[0.0006351722,0.00009890546,0.0001727452,0.0001251081,0.0001497315,0.00001447832,0.0001924952,0.00007321054,0.000004217462],"category_scores_gemma":[0.0001326304,0.0000997739,0.00003948945,0.0004943095,0.000207092,0.0002044383,0.0000165705,0.0000475016,0.000005509004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003583548,"about_ca_system_score_gemma":0.00002155829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004596201,"about_ca_topic_score_gemma":0.00001425438,"domain_scores_codex":[0.9991615,0.00001825272,0.0002997579,0.0001986127,0.0001300749,0.0001917364],"domain_scores_gemma":[0.9992965,0.0001492136,0.0001900614,0.0001754234,0.000159121,0.00002964815],"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":[0.000009465221,0.00001118152,0.001140045,0.000104354,0.00001134645,1.382439e-8,0.0006699635,0.01992375,0.9737011,0.001118171,0.0003763128,0.002934335],"study_design_scores_gemma":[0.0001675674,0.0000789131,0.005405192,0.00008945153,0.00001650685,0.000001512747,0.0001826398,0.1846014,0.808069,0.00008828254,0.001163752,0.0001357689],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6493921,0.0004070728,0.3437121,0.0001584725,0.0005496184,0.000425168,0.00001387091,0.0001789577,0.005162677],"genre_scores_gemma":[0.9805651,0.00001991318,0.01919754,0.000007971,0.0001208164,0.000036634,0.000008252101,0.0000128069,0.00003101226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.331173,"threshold_uncertainty_score":0.4068662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01090977478248845,"score_gpt":0.2474174188758354,"score_spread":0.236507644093347,"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."}}