{"id":"W7132928632","doi":"","title":"Modeling, estimation, and control of partially observable failing systems using phase method","year":2016,"lang":"","type":"dissertation","venue":"TSpace","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto","keywords":"Reliability (semiconductor); Bayesian probability; Process (computing); Posterior probability; Observable; Condition-based maintenance; Autoregressive model; State (computer science); Control theory (sociology); Partially observable Markov decision process","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009994979,0.0005054961,0.001001239,0.0001855471,0.0001930535,0.0001276882,0.0001641944,0.0005244367,0.00005593789],"category_scores_gemma":[0.0005871448,0.0004862142,0.0001383676,0.0002228795,0.000046452,0.0004777088,0.00001922832,0.0002533086,0.000005059642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001707763,"about_ca_system_score_gemma":0.0002063778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001205795,"about_ca_topic_score_gemma":0.00003154009,"domain_scores_codex":[0.9973424,0.0001920138,0.001126408,0.0005445128,0.0003253672,0.0004693071],"domain_scores_gemma":[0.9979373,0.0002774499,0.0004705716,0.0004574549,0.000699763,0.0001575109],"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":[0.0002080131,0.00005262177,0.00001747857,0.002685172,0.000162493,0.000001170996,0.002996889,0.9429269,0.04783085,0.0008894744,0.000003392632,0.002225485],"study_design_scores_gemma":[0.002567127,0.00009952822,0.000001789566,0.002518148,0.0004938345,0.000005759608,0.001566531,0.9873987,0.004502369,0.0003527336,0.00002536124,0.0004681167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09476909,0.003236074,0.8996972,0.00006493407,0.0008483197,0.001015121,0.00003215596,0.00007149274,0.0002656195],"genre_scores_gemma":[0.9126375,0.0008433717,0.08532225,0.000005305546,0.0001193658,0.00005499106,0.0001035696,0.000105668,0.000807954],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8178684,"threshold_uncertainty_score":0.999759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02870722736088143,"score_gpt":0.347145103264047,"score_spread":0.3184378759031656,"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."}}