{"id":"W3023322586","doi":"10.2514/6.2019-2808","title":"Characterization of Laminar Separation Bubbles Using Infrared Thermography","year":2019,"lang":"en","type":"article","venue":"AIAA Aviation 2019 Forum","topic":"Heat Transfer Mechanisms","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Thermography; Characterization (materials science); Laminar flow; Separation (statistics); Infrared; Materials science; Optics; Computer science; Mechanics; Nanotechnology; Physics; Machine learning","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":[0.0004266941,0.000240375,0.0002209952,0.0003787736,0.0002882586,0.0003817751,0.0002949377,0.0003454527,0.001192005],"category_scores_gemma":[0.000568282,0.00008734634,0.0001273365,0.0001517628,0.0002962668,0.0004363523,0.000250038,0.000360494,0.0003215818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002287421,"about_ca_system_score_gemma":0.0002473385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008286554,"about_ca_topic_score_gemma":0.0007301606,"domain_scores_codex":[0.9997981,0.0000246137,0.00001028235,0.00004056005,0.00009169168,0.00003484953],"domain_scores_gemma":[0.9996886,0.0001005991,0.00007615724,0.00001611565,0.00009986087,0.00001860866],"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":[0.00005377492,0.00001408623,0.0002121087,0.00002551174,0.000001259261,0.0000307846,0.00003406011,0.0001931612,0.9963204,0.0001510964,0.00004329388,0.002920465],"study_design_scores_gemma":[0.000002950529,0.00009590839,0.0006590277,0.000002351463,0.000001798615,0.00002566937,0.00001713914,0.002632526,0.9960265,0.00003709589,0.0004944468,0.000004614433],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8633966,0.001275664,0.1302269,0.0001706019,0.0000501306,0.000195114,0.0003329527,0.0004459335,0.003906102],"genre_scores_gemma":[0.95582,0.0003590919,0.0389462,0.00006017373,0.00001419321,0.0001049528,0.0002293417,0.00004156307,0.004424491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001192005,"threshold_uncertainty_score":0.00398767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00639028887243784,"score_gpt":0.2127846680883662,"score_spread":0.2063943792159284,"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."}}