{"id":"W2048299710","doi":"10.1007/s10845-009-0349-8","title":"LAD-CBM; new data processing tool for diagnosis and prognosis in condition-based maintenance","year":2009,"lang":"en","type":"article","venue":"Journal of Intelligent Manufacturing","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Data mining; Condition-based maintenance; Missing data; State (computer science); Reliability engineering; Machine learning; Engineering; Algorithm","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":[0.001004427,0.0008066726,0.001043882,0.002401033,0.0004512403,0.001306256,0.001254694,0.0008536823,0.009314873],"category_scores_gemma":[0.003287703,0.0003997815,0.0003844911,0.00132983,0.000315249,0.001173212,0.0009223542,0.0007874104,0.002448507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004684457,"about_ca_system_score_gemma":0.0008166856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002152584,"about_ca_topic_score_gemma":0.002136178,"domain_scores_codex":[0.9995267,0.00007083664,0.00005451783,0.00008409219,0.0002289015,0.00003483755],"domain_scores_gemma":[0.9988014,0.0005130389,0.0001598352,0.0001807168,0.0002832103,0.00006184085],"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":[0.001257138,0.0001578075,0.002972309,0.0004905736,0.0001053123,0.0002735438,0.0001831245,0.02307011,0.05292038,0.006707573,0.03092883,0.8809333],"study_design_scores_gemma":[0.0001415364,0.0002049056,0.002374718,0.00006230523,0.00007884003,0.0003459199,0.00005270839,0.8967353,0.06797718,0.005851266,0.02610206,0.00007323673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006409555,0.0003151524,0.957041,0.0001194344,0.00008086345,0.00006971928,0.001201677,0.03411303,0.0006495848],"genre_scores_gemma":[0.1756457,0.0003031001,0.8173129,0.000299675,0.0001074967,0.0003391481,0.00202924,0.000775495,0.003187228],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009314873,"threshold_uncertainty_score":0.03116131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02521179383352313,"score_gpt":0.2715152138788777,"score_spread":0.2463034200453545,"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."}}