{"id":"W2744967713","doi":"10.1061/9780784480885.024","title":"Precision Tracking of Pressure Events: “What’s Going on in My Transmission Pipeline Loop?”","year":2017,"lang":"en","type":"article","venue":"Pipelines 2017","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Loop (graph theory); Pipeline (software); Tracking (education); Transmission (telecommunications); Transient (computer programming); Transmission network; Sample (material); Pipeline transport; Jurisdiction; Computer science; Engineering; Real-time computing; Environmental science; Telecommunications; Mechanical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001746333,0.0003003989,0.0001620355,0.0007521767,0.001618564,0.002369087,0.0007146486,0.001565414,0.002936994],"category_scores_gemma":[0.009826283,0.0002510587,0.0001867836,0.001077511,0.001520341,0.003796403,0.001111861,0.001669039,0.0008994542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001926005,"about_ca_system_score_gemma":0.001587286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02136166,"about_ca_topic_score_gemma":0.04403649,"domain_scores_codex":[0.9989135,0.0003672353,0.00004565684,0.0001795748,0.0003265467,0.0001675571],"domain_scores_gemma":[0.9975222,0.000741335,0.000553292,0.000117094,0.0008618195,0.0002043096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000402722,0.0002689731,0.2294509,0.001059272,0.00008526364,0.00376388,0.120732,0.003140854,0.01391886,0.01318903,0.1617055,0.4522829],"study_design_scores_gemma":[0.00003065431,0.0006163151,0.3568127,0.002041482,0.00009461625,0.004067038,0.2518071,0.00921074,0.01165205,0.01388763,0.3494127,0.0003668747],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7272877,0.004830651,0.05008238,0.1161871,0.001032975,0.000344299,0.002377159,0.001186727,0.09667113],"genre_scores_gemma":[0.9667888,0.002050323,0.01417335,0.004710714,0.0002028534,0.00008922737,0.0004652554,0.00009177811,0.01142759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02136166,"threshold_uncertainty_score":0.04247463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01846203288419948,"score_gpt":0.2641490498799673,"score_spread":0.2456870169957678,"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."}}