{"id":"W6981714966","doi":"","title":"Expanded fatigue damage and load time signal estimation for dynamic helicopter components using computational intelligence techniques","year":2014,"lang":"en","type":"article","venue":"NPARC","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"SIGNAL (programming language); Transient (computer programming); Range (aeronautics); Computational intelligence; Computational model; Signal processing; State (computer science); Ranging; Estimation theory","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005056122,0.0004363825,0.0003777868,0.001316089,0.0001970129,0.0003672957,0.0004498381,0.0003722956,0.0007808246],"category_scores_gemma":[0.003050415,0.0002255354,0.000311206,0.0006802949,0.0002310828,0.0006859141,0.0003281256,0.000368489,0.000117698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004642471,"about_ca_system_score_gemma":0.0004220168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01140274,"about_ca_topic_score_gemma":0.01114644,"domain_scores_codex":[0.999827,0.00004367187,0.0000128781,0.00003732703,0.00005808775,0.00002114623],"domain_scores_gemma":[0.9988181,0.0007266752,0.0001689188,0.00009274002,0.0001703294,0.00002316239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003300433,0.00003952829,0.004960052,0.00001658454,0.00001297902,0.00002916071,0.00002173075,0.9585049,0.0010444,0.0007310884,0.0001279105,0.03447866],"study_design_scores_gemma":[4.658221e-7,0.00000479983,0.0008617567,5.914409e-7,6.775824e-7,0.000002551259,0.000001814237,0.9987954,0.0001717585,0.0001404448,0.00001864674,0.000001119595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5775051,0.0001434569,0.419283,0.0001330548,0.000008091879,0.00004520491,0.0001734712,0.0004172591,0.002291347],"genre_scores_gemma":[0.9632593,0.00005084701,0.0359948,0.000008143757,0.000005731488,0.00002373358,0.0001633825,0.00001194474,0.0004822217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01140274,"threshold_uncertainty_score":0.02267271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0578563176236309,"score_gpt":0.2629141667200774,"score_spread":0.2050578490964465,"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."}}