{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004324119,0.000236858,0.0002964623,0.0001826481,0.000067785,0.0001043875,0.000152864,0.00007793637,0.00000370295],"category_scores_gemma":[0.00004587835,0.0002453668,0.0001144546,0.0003289245,0.00001148248,0.0001107261,0.000009824236,0.0004782506,0.00004981256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190798,"about_ca_system_score_gemma":0.0001214838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003185868,"about_ca_topic_score_gemma":0.0001462779,"domain_scores_codex":[0.9983436,0.00004147508,0.0004285735,0.000275022,0.0002113635,0.0006999545],"domain_scores_gemma":[0.9993706,0.0002142546,0.0000278094,0.0002510024,0.00006867897,0.00006768263],"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":[0.0007300382,0.0002023765,0.002445144,0.01484397,0.002236471,0.0009122104,0.004078294,0.4994295,0.2083416,0.02404931,0.05125564,0.1914754],"study_design_scores_gemma":[0.001075503,0.00008560249,0.0000725444,0.000524502,0.00004230474,0.00005933719,0.0001272265,0.8629903,0.02014319,0.00009568573,0.1143891,0.0003947299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7332216,0.1300434,0.1140168,0.0004012564,0.0155195,0.002269036,0.0001950444,0.002763021,0.001570363],"genre_scores_gemma":[0.9983684,0.00007276797,0.0005325171,0.000009088498,0.0005130768,0.00006008989,0.00003000884,0.00009573928,0.0003183393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3635608,"threshold_uncertainty_score":0.9999999,"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."}}