{"id":"W4295918947","doi":"10.4050/f-0078-2022-17636","title":"RACER Coumpound Helicopter: Operational Wireless FTI Data Transfer from ROTOR's up to Fuselage","year":2022,"lang":"en","type":"article","venue":"","topic":"Advanced Measurement and Detection Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Fuselage; Wireless; Data acquisition; Rotor (electric); Engineering; Computer science; Frame (networking); Instrumentation (computer programming); Systems engineering; Real-time computing; Marine engineering; Aeronautics; Telecommunications; Aerospace engineering; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003150933,0.0001327941,0.0001368635,0.00006442379,0.0001838689,0.00004887391,0.0003097129,0.00003039692,0.006071832],"category_scores_gemma":[0.00001099885,0.0001391852,0.0000289826,0.000171072,0.000008285161,0.000276093,0.0001006624,0.000189568,0.00008033033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009486378,"about_ca_system_score_gemma":0.00002058424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003279822,"about_ca_topic_score_gemma":0.0000709618,"domain_scores_codex":[0.9989185,0.00005934438,0.0001918356,0.0002829231,0.0003699337,0.0001774723],"domain_scores_gemma":[0.9993646,0.00005474317,0.000005079838,0.0004530501,0.00002901153,0.00009357302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000202595,0.00007496515,0.0004346946,0.00002794795,0.0001870475,0.00001300425,0.001409064,0.212907,0.6938363,0.0006374451,0.03456666,0.0557033],"study_design_scores_gemma":[0.001291713,0.00006261829,0.0003607566,0.00000730863,0.00003024141,0.000006508089,0.00056305,0.1067775,0.09685349,0.0001449466,0.7933515,0.0005503544],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1491893,0.0001523843,0.8455253,0.0001360489,0.001437133,0.0003501185,0.0002911118,0.0003481522,0.002570476],"genre_scores_gemma":[0.9684166,0.00002699175,0.02641707,0.000817628,0.0004006612,0.0002515696,0.0003705963,0.00006453361,0.003234407],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8192272,"threshold_uncertainty_score":0.9948367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07117678442561867,"score_gpt":0.2929615178400079,"score_spread":0.2217847334143892,"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."}}