{"id":"W2010064657","doi":"10.4028/www.scientific.net/amm.16-19.1310","title":"Fault Diagnosis of Engine Based on Improved Dempster-Shafer Information Fusion Method","year":2009,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Credibility; Dempster–Shafer theory; Information fusion; Fault (geology); Function (biology); Fusion; Data mining; Sensor fusion; Artificial intelligence; Degree (music); Computer science; Engineering; Machine learning; Mathematics","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":[0.002282921,0.0008839757,0.001574781,0.004594304,0.0006223826,0.001369063,0.001033886,0.00120368,0.001297454],"category_scores_gemma":[0.007069206,0.0005166412,0.001169989,0.00220604,0.0006531062,0.002556667,0.001064138,0.0007560415,0.0003138803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169779,"about_ca_system_score_gemma":0.001012487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002583268,"about_ca_topic_score_gemma":0.001939252,"domain_scores_codex":[0.997476,0.0004632087,0.0002781926,0.0002906717,0.00138646,0.0001053332],"domain_scores_gemma":[0.9981169,0.0008134284,0.0001756247,0.0001353331,0.0007142315,0.00004450375],"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":[0.0004319735,0.00009045694,0.002367561,0.0007585027,0.0003261384,0.0005307685,0.0003652242,0.2849941,0.01953674,0.038914,0.002743892,0.6489406],"study_design_scores_gemma":[0.00005916715,0.0001133692,0.00122071,0.00003739709,0.0001003177,0.0003520481,0.00004479232,0.9713742,0.007692656,0.01678304,0.002161109,0.00006127658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01339537,0.0009701069,0.9834031,0.0001483774,0.00005939472,0.00006176792,0.0000525523,0.0001764945,0.00173281],"genre_scores_gemma":[0.5813732,0.001571321,0.4144148,0.00008841594,0.000116096,0.0001715458,0.0001634374,0.00002307343,0.00207826],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004594304,"threshold_uncertainty_score":0.01207334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004803987022868599,"score_gpt":0.206171703419581,"score_spread":0.2013677163967124,"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."}}