{"id":"W3007592021","doi":"10.1002/eng2.12128","title":"A Markovian reliability approach for offshore wind energy system analysis in harsh environments","year":2020,"lang":"en","type":"article","venue":"Engineering Reports","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Downtime; Reliability engineering; Reliability (semiconductor); Fault tree analysis; Markov process; Computer science; Remedial action; Process (computing); System dynamics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002115215,0.000193151,0.0006739525,0.0003901745,0.00005690931,0.00008598457,0.0003058488,0.0001104099,0.00004019972],"category_scores_gemma":[0.001353025,0.0001629023,0.0004830633,0.002141385,0.0000226388,0.0001655654,0.00008833957,0.0001148148,0.000003957825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001186214,"about_ca_system_score_gemma":0.00002502163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007397878,"about_ca_topic_score_gemma":0.000009815592,"domain_scores_codex":[0.9967264,0.0000525737,0.00116256,0.0008918399,0.0008773021,0.000289326],"domain_scores_gemma":[0.9983749,0.0002605971,0.0002779668,0.0008311158,0.00003854114,0.0002169194],"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":[0.00001764258,0.00003573873,0.08094214,0.00002192347,0.000168239,0.0001033629,0.0002434655,0.9163524,0.0001361789,0.00006141012,0.0002453306,0.001672209],"study_design_scores_gemma":[0.0001219613,0.00002147095,0.06985437,0.000006345223,0.0002092237,0.00001140653,0.0002594547,0.9163133,0.0001835833,0.00008827259,0.0127168,0.0002137861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2517897,0.0002022292,0.7464269,0.000419292,0.0001433366,0.0002514424,0.00001814727,0.00008442843,0.0006645173],"genre_scores_gemma":[0.992215,0.000009370884,0.007239471,0.00003322208,0.00007362989,0.00003312243,0.00004053209,0.00001633112,0.0003392713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7404253,"threshold_uncertainty_score":0.6642964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02527568556706488,"score_gpt":0.2540384503880399,"score_spread":0.228762764820975,"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."}}