{"id":"W2327123071","doi":"10.2514/6.2014-1238","title":"Deployment of Particle Image Velocimetry into the Lockheed Martin High Speed Wind Tunnel","year":2014,"lang":"en","type":"article","venue":"52nd Aerospace Sciences Meeting","topic":"Particle Dynamics in Fluid Flows","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Particle image velocimetry; Software deployment; Wind tunnel; Aerospace engineering; Marine engineering; Aerodynamics; Particle tracking velocimetry; Computer science; Acoustics; Geology; Physics; Aeronautics; Engineering; Mechanics; Turbulence","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":[0.002053496,0.0004247172,0.0005125825,0.0005172596,0.0007936474,0.0008250299,0.0006837004,0.0007628066,0.003007377],"category_scores_gemma":[0.001674885,0.0004745095,0.0002597435,0.0002914023,0.0006400296,0.0009916098,0.0008725546,0.0009633453,0.0005933781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006016974,"about_ca_system_score_gemma":0.00268986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0123657,"about_ca_topic_score_gemma":0.01491342,"domain_scores_codex":[0.9993574,0.0001472945,0.00001870887,0.0001014281,0.0002263841,0.0001488338],"domain_scores_gemma":[0.9987741,0.0002253001,0.00005500525,0.0001402017,0.0003963386,0.0004089649],"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":[0.01014787,0.003689051,0.1392607,0.0002328792,0.0002436078,0.001625429,0.001714341,0.1134179,0.4748445,0.007497572,0.01886231,0.2284638],"study_design_scores_gemma":[0.001050984,0.006942479,0.1116669,0.0001006692,0.00009595342,0.0003249286,0.0005779983,0.7674671,0.0892067,0.0009202207,0.02139681,0.0002491763],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9596618,0.00007005717,0.02963881,0.0003922292,0.0002139344,0.0003032174,0.0008572586,0.002720483,0.006142218],"genre_scores_gemma":[0.958121,0.00003880865,0.03703707,0.00006234159,0.00001270042,0.00007172914,0.0008577804,0.0001199896,0.003678528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0123657,"threshold_uncertainty_score":0.02458745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008675182000000739,"score_gpt":0.2268547460914559,"score_spread":0.2181795640914551,"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."}}