{"id":"W2105720696","doi":"10.1504/ijmic.2012.045693","title":"Machine vibration prediction using ANFIS and wavelet packet decomposition","year":2012,"lang":"en","type":"article","venue":"International Journal of Modelling Identification and Control","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Syncrude","keywords":"Adaptive neuro fuzzy inference system; Wavelet packet decomposition; Wavelet; SIGNAL (programming language); Computer science; Vibration; Series (stratigraphy); Decomposition; Fuzzy logic; Artificial intelligence; Wavelet transform; Fuzzy control system; Acoustics; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0004151495,0.00007181893,0.00009211691,0.0001308225,0.0001034423,0.0002454538,0.0001827742,0.00003534068,0.000003167567],"category_scores_gemma":[0.000009353546,0.00006603085,0.00003696193,0.00006863296,0.00002177849,0.00122506,0.00002513881,0.00009400129,0.000001382257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003268311,"about_ca_system_score_gemma":0.00001418342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008366059,"about_ca_topic_score_gemma":5.406291e-7,"domain_scores_codex":[0.9991304,0.00003838308,0.0003771231,0.000110457,0.000251365,0.00009230406],"domain_scores_gemma":[0.9991432,0.00005447178,0.0003434426,0.00008922407,0.0002839609,0.00008573532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002941548,0.0007789872,0.01524503,0.00003522059,0.0005689469,0.00001110772,0.002408809,0.1971363,0.2857146,0.2470948,0.0006274802,0.2500846],"study_design_scores_gemma":[0.0004825671,0.00001692192,0.003472717,0.00001993266,0.00002409579,0.0001695067,0.00001166407,0.9908503,0.001205391,0.003168635,0.0005185594,0.00005972181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1133346,0.0005235526,0.8838743,0.00169306,0.0004616077,0.00007169647,0.00001066228,0.00001413321,0.00001636454],"genre_scores_gemma":[0.9883774,0.000337882,0.01070124,0.0002034224,0.0003491837,0.000003163974,0.00000854333,0.000004703048,0.00001447554],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8750428,"threshold_uncertainty_score":0.269266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100117685958766,"score_gpt":0.2741690787959654,"score_spread":0.2531679019363777,"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."}}