{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002358611,0.000510857,0.0006039548,0.000613179,0.0005121019,0.0006800772,0.001766006,0.0004949924,0.0107447],"category_scores_gemma":[0.0004035402,0.0002680452,0.0002273458,0.0003736162,0.0002108455,0.0005812138,0.0004386908,0.0005620302,0.001752367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004328709,"about_ca_system_score_gemma":0.0006689079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001952384,"about_ca_topic_score_gemma":0.002254889,"domain_scores_codex":[0.9994106,0.00004512194,0.00002313407,0.0001739749,0.0002992628,0.00004783567],"domain_scores_gemma":[0.9997016,0.00006040155,0.00004180599,0.00004919536,0.0001151601,0.0000318823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00142268,0.000567983,0.002966642,0.0005314859,0.00009876893,0.0005208543,0.0001772474,0.0142595,0.4743626,0.003714946,0.02470296,0.4766744],"study_design_scores_gemma":[0.0006975771,0.002776433,0.01018161,0.00007733268,0.0002965358,0.001515503,0.00008264233,0.4861134,0.4181962,0.002364051,0.07745285,0.0002458396],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1600025,0.0009044387,0.7280957,0.0005603501,0.0007345886,0.0007114992,0.001070388,0.05954194,0.04837869],"genre_scores_gemma":[0.8871065,0.0001785964,0.08617146,0.0006705704,0.0001450318,0.0002172544,0.0005271963,0.0003179152,0.02466554],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0107447,"threshold_uncertainty_score":0.03594458,"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."}}