{"id":"W2050038522","doi":"10.4028/www.scientific.net/amm.16-19.193","title":"An Engine Dynamic Signal Testing System Based on Virtual Instrument Technology","year":2009,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Advanced Sensor and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Signal conditioning; Data acquisition; Virtual instrumentation; Computer hardware; Instrumentation (computer programming); Portable computer; Software; SIGNAL (programming language); Field (mathematics); Signal processing; Digital signal processing; Computer science; Instrument Driver; Sampling (signal processing); Virtual instrument; Personal computer; Data processing; Engineering; Embedded system; Power (physics); Electrical engineering; Operating system; Detector","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":[0.00100287,0.000659553,0.0008824517,0.001414305,0.000439846,0.0008394103,0.001664244,0.0006068878,0.003763842],"category_scores_gemma":[0.001050741,0.0003552032,0.0003168904,0.0006480461,0.0003484484,0.001167139,0.001026512,0.00049175,0.00125662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003745659,"about_ca_system_score_gemma":0.0008979496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007540743,"about_ca_topic_score_gemma":0.0004712981,"domain_scores_codex":[0.9985664,0.0002621765,0.0000960702,0.0002703771,0.0006864495,0.0001184938],"domain_scores_gemma":[0.9992004,0.0001520019,0.0000580751,0.0001227951,0.0003750671,0.0000916498],"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":[0.001559666,0.0005403893,0.01399871,0.0008152126,0.0001721694,0.0005301945,0.0006161748,0.01356184,0.6665258,0.009277395,0.007430139,0.2849724],"study_design_scores_gemma":[0.0008735241,0.007707691,0.02717235,0.0001338062,0.0005926952,0.003477896,0.0002455013,0.2950256,0.5962167,0.003253187,0.06490973,0.0003912909],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1682338,0.000448002,0.807266,0.000131899,0.0001814172,0.000849711,0.0005876006,0.01339088,0.008910685],"genre_scores_gemma":[0.8280172,0.0003054268,0.1608628,0.0002122375,0.0001031253,0.0008330049,0.001327982,0.0002077864,0.008130297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003763842,"threshold_uncertainty_score":0.01259136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004625397969363859,"score_gpt":0.1821650122423995,"score_spread":0.1775396142730356,"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."}}