{"id":"W1992520396","doi":"10.3182/20060829-4-cn-2909.00026","title":"MODELLING OF VERTICAL GYROSCOPES WITH CONSIDERATION OF FAULTS","year":2006,"lang":"en","type":"article","venue":"IFAC Proceedings Volumes","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Gyroscope; Flexibility (engineering); Parametric statistics; Fault (geology); Control theory (sociology); Lag; Engineering; Fault tolerance; Control engineering; Computer science; Control (management); Reliability engineering; Artificial intelligence; Aerospace engineering; Mathematics; Geology; Statistics; Seismology","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":[0.0002836899,0.0009810994,0.0008234449,0.0005029066,0.0003083766,0.001257404,0.0008199188,0.001376861,0.001706527],"category_scores_gemma":[0.001559263,0.0005915296,0.0006878829,0.0005524689,0.0005415502,0.000871025,0.0007140702,0.0004758563,0.0004140626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005106009,"about_ca_system_score_gemma":0.000611354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01532761,"about_ca_topic_score_gemma":0.006664685,"domain_scores_codex":[0.9997332,0.00006147909,0.00001922713,0.00005768825,0.00008315613,0.00004534541],"domain_scores_gemma":[0.9995708,0.0001731209,0.0001036203,0.00003904018,0.00009264674,0.00002068925],"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":[0.00002563763,0.000003529306,0.0003424296,0.00002895007,0.000009390183,0.00005749886,0.00003300991,0.992339,0.001455008,0.002619933,0.0001045407,0.002981069],"study_design_scores_gemma":[0.000002606805,0.00001043705,0.0001893971,0.000003719951,0.000004044196,0.00001345625,0.000004351727,0.9981083,0.0004531789,0.0008873836,0.0003193498,0.000003815852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1070182,0.001020947,0.8798596,0.0002814307,0.000162475,0.00004282833,0.0004474345,0.000835839,0.01033119],"genre_scores_gemma":[0.9769489,0.0005798443,0.01544925,0.00002292567,0.0000313102,0.00004751126,0.0002641125,0.00007204351,0.006584196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01532761,"threshold_uncertainty_score":0.03047675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008390012659412426,"score_gpt":0.1857814251726825,"score_spread":0.1773914125132701,"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."}}