{"id":"W1637181560","doi":"10.1063/1.2937611","title":"Optimal inspection period and replacement policy for CBM with imperfect information using PHM","year":2008,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Condition-based maintenance; Reliability engineering; Computer science; Hidden Markov model; Optimal maintenance; Degradation (telecommunications); State (computer science); Maintenance engineering; Markov process; Engineering; Statistics; Algorithm; Mathematics; Artificial intelligence","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":[0.00241219,0.0009205907,0.002207538,0.0009699085,0.000411781,0.001212509,0.001694332,0.001473325,0.002862254],"category_scores_gemma":[0.006179109,0.000878586,0.0008093744,0.0007582078,0.001049874,0.001200893,0.0009753667,0.001212243,0.0002703562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002099997,"about_ca_system_score_gemma":0.001972877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008098321,"about_ca_topic_score_gemma":0.004359894,"domain_scores_codex":[0.9990735,0.0002918742,0.00003151754,0.000238052,0.0001843218,0.0001806755],"domain_scores_gemma":[0.9978637,0.001469557,0.000347109,0.00009461251,0.0001425127,0.00008255674],"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":[0.00006994604,0.00002994014,0.0005167835,0.00005407672,0.00001885044,0.00005700234,0.00003148635,0.9820892,0.0007339083,0.01080586,0.0003158374,0.005277149],"study_design_scores_gemma":[0.00001219518,0.00002766353,0.0002769107,0.000007063459,0.000009248862,0.00001418048,0.00000800239,0.9945968,0.0001332041,0.004771076,0.0001378903,0.000005778921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07955958,0.0006532914,0.9143943,0.0005808084,0.00004046786,0.0001033294,0.0002498848,0.0002643382,0.004154019],"genre_scores_gemma":[0.9362372,0.0004600951,0.05672654,0.00006451043,0.00003876176,0.0002323023,0.0001814131,0.00006440599,0.005994774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008098321,"threshold_uncertainty_score":0.01610237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01274902046193664,"score_gpt":0.2188310785960851,"score_spread":0.2060820581341485,"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."}}