{"id":"W2271370967","doi":"10.1115/1.4032488","title":"Probabilistic Performance Assessment of Fiber Optic Leak Detection Systems","year":2016,"lang":"en","type":"article","venue":"Journal of Offshore Mechanics and Arctic Engineering","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Memorial University of Newfoundland","funders":"","keywords":"Operability; Probabilistic logic; Leak detection; Reliability engineering; Leak; Computer science; Reliability (semiconductor); Pipeline transport; Detection theory; Risk analysis (engineering); Engineering; Real-time computing; Artificial intelligence; Detector; Telecommunications","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":[0.00378229,0.001036066,0.0006703156,0.001459202,0.0005054058,0.001395661,0.001044643,0.001161861,0.001156186],"category_scores_gemma":[0.01158478,0.0003784916,0.0008554526,0.0006594116,0.0008766171,0.001446769,0.001184392,0.0006976381,0.0002165707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001591997,"about_ca_system_score_gemma":0.0009367518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004827779,"about_ca_topic_score_gemma":0.001570304,"domain_scores_codex":[0.9976071,0.0007826212,0.000112127,0.0002991048,0.0009626872,0.0002363486],"domain_scores_gemma":[0.9927796,0.004714919,0.0009462201,0.0002955097,0.001160831,0.0001029574],"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":[0.00004164,0.00001073604,0.00137888,0.00002304365,0.00001206974,0.00003250122,0.00003654858,0.9889186,0.001413143,0.002964638,0.0000666004,0.005101565],"study_design_scores_gemma":[0.000001408232,0.0000290123,0.0004121132,0.000003724899,0.000005765557,0.00001620706,0.000006245962,0.9977875,0.0005777297,0.00107855,0.00007467518,0.000007063084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1472621,0.0003758864,0.8472438,0.0002022628,0.00001617675,0.0001218891,0.0001438266,0.0004338704,0.004200226],"genre_scores_gemma":[0.9841867,0.0001456178,0.01465387,0.00001608953,0.00000956314,0.00007883402,0.00008983949,0.00001869635,0.0008007521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004827779,"threshold_uncertainty_score":0.0200029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008416341123523154,"score_gpt":0.2068935988758547,"score_spread":0.1984772577523316,"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."}}