{"id":"W3099805203","doi":"10.36001/phmconf.2020.v12i1.1261","title":"Life prediction for aircraft structure based on Bayesian inference: towards a digital twin ecosystem","year":2020,"lang":"en","type":"article","venue":"Annual Conference of the PHM Society","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of National Defence; National Research Council Canada; Government of Canada; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Computer science; Inference; Data mining; Software; Bayesian probability; Bayesian inference; Machine learning; 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":[0.001583006,0.0005496062,0.0006704048,0.001794838,0.0003933848,0.00128448,0.001197681,0.0007422886,0.001185056],"category_scores_gemma":[0.004041422,0.0003715267,0.0005921684,0.001108371,0.0006351849,0.002777975,0.001716716,0.0009261359,0.0003143181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006750437,"about_ca_system_score_gemma":0.0009291038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005404429,"about_ca_topic_score_gemma":0.0047916,"domain_scores_codex":[0.9992168,0.0001608222,0.00004276212,0.0002243731,0.0003048797,0.00005027742],"domain_scores_gemma":[0.9987983,0.0004724215,0.0001507423,0.0001957974,0.0003114264,0.00007129753],"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":[0.0002071343,0.0001684005,0.0187396,0.0001390476,0.0001366082,0.0002629651,0.0003817719,0.484041,0.009248643,0.03707521,0.002015673,0.4475841],"study_design_scores_gemma":[0.000003776429,0.0000156093,0.0007464871,0.000007457666,0.00001087936,0.00004016103,0.00002039091,0.9897048,0.0009063722,0.007824245,0.0007123706,0.000007563356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02050865,0.0001405545,0.9777288,0.0001251426,0.00001524902,0.00001910487,0.00006046166,0.0002968298,0.001105184],"genre_scores_gemma":[0.5551277,0.000391991,0.4415648,0.0001135377,0.0000700341,0.00006242158,0.0004162536,0.00009539945,0.002157836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005404429,"threshold_uncertainty_score":0.01074594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02153486751451185,"score_gpt":0.2388464766988626,"score_spread":0.2173116091843507,"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."}}