{"id":"W4401595674","doi":"10.3390/electronics13163235","title":"Smart IoT SCADA System for Hybrid Power Monitoring in Remote Natural Gas Pipeline Control Stations","year":2024,"lang":"en","type":"article","venue":"Electronics","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"SCADA; Pipeline (software); Internet of Things; Natural gas; Monitoring and control; Computer science; Remote control; Embedded system; Engineering; Control (management); Power (physics); Smart power; Real-time computing; Environmental science; Control engineering; Electrical engineering; Operating system; Waste management; Artificial intelligence","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":[0.0002510776,0.0005255134,0.0004214132,0.0007310978,0.0004412977,0.0005547482,0.0009711906,0.0003826489,0.004416879],"category_scores_gemma":[0.0003978098,0.0001792252,0.0002145105,0.0004056418,0.0002016042,0.0006809011,0.0004437992,0.0002980786,0.001244416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00040486,"about_ca_system_score_gemma":0.0003895708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001321835,"about_ca_topic_score_gemma":0.001613904,"domain_scores_codex":[0.9995736,0.00005928425,0.00003737057,0.0001345224,0.0001563003,0.00003884317],"domain_scores_gemma":[0.9996765,0.0000309388,0.00005361281,0.00006320381,0.0001432282,0.00003248304],"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":[0.001474656,0.0008405753,0.03431552,0.0006946081,0.0001972304,0.00287228,0.00145232,0.0308673,0.3046049,0.007981091,0.04993125,0.5647683],"study_design_scores_gemma":[0.0004617535,0.001935441,0.05708687,0.0001695297,0.0002987187,0.00226816,0.0004299884,0.6758397,0.1529285,0.003196588,0.1051661,0.0002186156],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3396025,0.0005043143,0.5904791,0.0004673059,0.0004114265,0.0009446222,0.001032288,0.03221172,0.03434677],"genre_scores_gemma":[0.9733435,0.00008350526,0.01820515,0.0001064272,0.00005365479,0.0002841477,0.0004206504,0.00007853366,0.007424428],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004416879,"threshold_uncertainty_score":0.01477593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004559062874762572,"score_gpt":0.2201916026001574,"score_spread":0.2156325397253949,"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."}}