{"id":"W837786555","doi":"10.1007/s10489-015-0674-x","title":"Data mining-based methods for fault isolation with validated FMEA model ranking","year":2015,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Reliability engineering; Failure mode and effects analysis; Data mining; Fault detection and isolation; Isolation (microbiology); Reliability (semiconductor); Fault tree analysis; Ranking (information retrieval); Fault (geology); Root cause; Component (thermodynamics); Machine learning; Power (physics); Artificial intelligence; 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":[0.002733495,0.001706554,0.001618879,0.005606527,0.0006608665,0.001500973,0.001731711,0.0008259825,0.003359857],"category_scores_gemma":[0.01084441,0.0003388439,0.00150238,0.002551541,0.0003429158,0.001197541,0.0009352237,0.001351887,0.0008713919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000821238,"about_ca_system_score_gemma":0.001847245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005047327,"about_ca_topic_score_gemma":0.007171247,"domain_scores_codex":[0.9986008,0.0003854263,0.0001418269,0.0002328426,0.0005197291,0.0001194733],"domain_scores_gemma":[0.9950213,0.002781784,0.000411423,0.0004578293,0.001243164,0.00008438258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003470268,0.0005211632,0.006439499,0.000451717,0.0003898923,0.0001207868,0.00007946649,0.3032114,0.006448973,0.007557686,0.004466882,0.6699656],"study_design_scores_gemma":[0.00002272592,0.00007713719,0.0009263377,0.00003081225,0.00005586432,0.00004993796,0.00002482033,0.9896342,0.002427344,0.005813033,0.000925257,0.00001260491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01828432,0.0004764149,0.9775363,0.0001336039,0.00004100968,0.0001324613,0.0004960495,0.001715069,0.001184868],"genre_scores_gemma":[0.4693968,0.0003222137,0.5256201,0.0001303501,0.00007361918,0.0003754576,0.00237156,0.0002009773,0.001508855],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005606527,"threshold_uncertainty_score":0.01445627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1283990250589309,"score_gpt":0.4053995618538704,"score_spread":0.2770005367949396,"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."}}