{"id":"W2606918641","doi":"10.1115/1.4036428","title":"Risk-Based Maintenance Planning for Deteriorating Pressure Vessels With Multiple Defects","year":2017,"lang":"en","type":"article","venue":"Journal of Pressure Vessel Technology","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Pressure vessel; Leak; Reliability engineering; Process (computing); Planned maintenance; Oil refinery; Computer science; Risk analysis (engineering); Engineering; Business; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004380575,0.0002156274,0.0004304846,0.0002213923,0.0003350947,0.0001189486,0.0006299583,0.0002987579,0.00000388637],"category_scores_gemma":[0.001461915,0.0001696567,0.00009375521,0.0001072255,0.000181259,0.0004551899,0.00004205439,0.0005214587,7.407884e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002390519,"about_ca_system_score_gemma":0.0000582996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003838376,"about_ca_topic_score_gemma":0.000007979284,"domain_scores_codex":[0.9988384,0.00002664504,0.000416927,0.0001963061,0.0001581311,0.0003635786],"domain_scores_gemma":[0.997987,0.0001641004,0.0007981989,0.0005525008,0.0004328932,0.00006530967],"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":[0.0002532992,0.00004410902,0.04004835,0.000449078,0.00025668,0.00002927854,0.0001238277,0.9432529,0.01096441,0.0001980933,0.001132373,0.003247601],"study_design_scores_gemma":[0.005908708,0.00124069,0.01327673,0.001664499,0.0007732775,0.0001552163,0.000308793,0.832581,0.06957576,0.002600512,0.07120471,0.0007101023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2718103,0.002172302,0.7238184,0.0005058052,0.0005926727,0.0005757835,0.00003986911,0.0002790978,0.0002058502],"genre_scores_gemma":[0.9438468,0.00007865999,0.05582796,0.00001457366,0.0001037528,0.00003910382,0.000001577084,0.00004763086,0.00004001139],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6720365,"threshold_uncertainty_score":0.6918398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008365015107557975,"score_gpt":0.2321294332912875,"score_spread":0.2237644181837296,"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."}}