{"id":"W2756414053","doi":"10.1016/j.isatra.2017.09.004","title":"A hybrid clustering approach for multivariate time series – A case study applied to failure analysis in a gas turbine","year":2017,"lang":"en","type":"article","venue":"ISA Transactions","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Division of Graduate Education; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Cluster analysis; Multivariate statistics; Data mining; Euclidean distance; Metric (unit); Series (stratigraphy); Computer science; Similarity (geometry); Artificial intelligence; Pattern recognition (psychology); Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001731799,0.0007031159,0.0007018627,0.001828885,0.0007655953,0.0009577232,0.001096487,0.0012562,0.001042926],"category_scores_gemma":[0.002750807,0.0002382842,0.001006725,0.001822284,0.0003721164,0.0006196813,0.0006585543,0.0005145307,0.0002229912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006839729,"about_ca_system_score_gemma":0.0005822298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008211984,"about_ca_topic_score_gemma":0.0115869,"domain_scores_codex":[0.9991062,0.0003484733,0.0000574059,0.0001460923,0.0002694712,0.00007229584],"domain_scores_gemma":[0.9983512,0.0009094109,0.0001062654,0.0001651991,0.000409311,0.00005862927],"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":[0.000480548,0.0003607773,0.01224439,0.0003192436,0.0003634552,0.0009939284,0.0006355405,0.6562857,0.01550178,0.007591814,0.002216844,0.303006],"study_design_scores_gemma":[0.000009213579,0.00009011222,0.004190726,0.000009101636,0.00004416145,0.0001963299,0.0001441384,0.990782,0.0019889,0.001723729,0.0007916173,0.00003006364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3461127,0.0004576989,0.6487622,0.0003630194,0.00006844704,0.0001583084,0.0002767501,0.0005182111,0.003282813],"genre_scores_gemma":[0.8306516,0.0001625214,0.1667351,0.00003581962,0.00003870905,0.00006110417,0.0002106598,0.00009116433,0.002013267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008211984,"threshold_uncertainty_score":0.01632833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01263515608843998,"score_gpt":0.2422126375456122,"score_spread":0.2295774814571722,"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."}}