{"id":"W3150561630","doi":"10.1016/j.psep.2021.03.045","title":"A programmable logic controller based remote pipeline monitoring system","year":2021,"lang":"en","type":"article","venue":"Process Safety and Environmental Protection","topic":"Water Systems and Optimization","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Higher Education Commission, Pakistan","keywords":"SCADA; Programmable logic controller; Pipeline transport; Pipeline (software); Reliability (semiconductor); Sensitivity (control systems); Leak; Real-time computing; Reliability engineering; Computer science; Controller (irrigation); ALARM; Embedded system; False alarm; Engineering; Automotive engineering; Electronic engineering; Artificial intelligence; Electrical 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":[0.0001047951,0.0001302045,0.0001457173,0.00002869279,0.0001419401,0.00004362526,0.0000284026,0.00008549471,0.00001011469],"category_scores_gemma":[0.000004228865,0.0001246777,0.0000283746,0.00008507466,0.00001590268,0.0001508833,0.00001208157,0.0001082949,0.000009714517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00012456,"about_ca_system_score_gemma":0.000004622439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001476323,"about_ca_topic_score_gemma":0.000003950483,"domain_scores_codex":[0.9992964,0.00002564883,0.0002042793,0.0001929652,0.000119555,0.0001611928],"domain_scores_gemma":[0.9998211,0.000004092615,0.00003561519,0.00007904825,0.000009538933,0.00005058064],"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":[0.00009319183,0.00002945582,0.0002659946,0.0009193976,0.00002374648,0.00000933525,0.0001181167,0.9695795,0.004269743,0.000009054102,0.000003449147,0.02467906],"study_design_scores_gemma":[0.0007589708,0.00002988719,0.0002446898,0.0001373633,0.00001715607,0.00003994972,0.0003006303,0.9844001,0.01305724,0.00002649853,0.0008363117,0.0001511851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007114166,0.0009678639,0.9896432,0.00005134418,0.0002470713,0.000546431,0.000008041538,0.0003228431,0.001099073],"genre_scores_gemma":[0.9986475,0.00008637248,0.0007581005,0.000005744884,0.0001211266,0.00005408749,0.00002400146,0.00002379557,0.000279332],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9915333,"threshold_uncertainty_score":0.5084207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008134617152855947,"score_gpt":0.1758637888389146,"score_spread":0.1677291716860587,"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."}}