{"id":"W2409004783","doi":"10.1109/icit.2016.7474923","title":"Development of PC-based SCADA training system","year":2016,"lang":"en","type":"article","venue":"","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"SCADA; Microcontroller; Interface (matter); Embedded system; Troubleshooting; Automation; Data acquisition; Computer science; Software; User interface; Serial port; Process (computing); Supervisory control; Computer hardware; Engineering; Operating system; Control (management); 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":[0.0002603318,0.0004443007,0.0003987987,0.0005896481,0.0003197604,0.0005581234,0.001033621,0.0003338878,0.01061444],"category_scores_gemma":[0.0006364856,0.0002107552,0.0001403422,0.0003456092,0.0001404999,0.0004810044,0.0003195784,0.0003758085,0.004661984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003223744,"about_ca_system_score_gemma":0.0007115043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00192852,"about_ca_topic_score_gemma":0.001034579,"domain_scores_codex":[0.9994544,0.00005301151,0.00003255983,0.0001237001,0.0002856806,0.00005063268],"domain_scores_gemma":[0.9995483,0.0000336894,0.0000260518,0.00005765256,0.0002957332,0.0000384956],"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":[0.0004645872,0.0003751865,0.007490688,0.0006832344,0.00006301844,0.000905356,0.0005383418,0.03104082,0.1633205,0.007159112,0.04849778,0.7394614],"study_design_scores_gemma":[0.0003183791,0.00184173,0.01891153,0.0001918724,0.0001485551,0.002693916,0.0002037603,0.3546126,0.2737215,0.001851619,0.3453572,0.0001474078],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07215963,0.0005156478,0.823148,0.0003288355,0.0003706273,0.001265053,0.000780008,0.04473417,0.05669804],"genre_scores_gemma":[0.6746895,0.0005056921,0.2615768,0.0002285908,0.0001675562,0.0007865852,0.001491985,0.0006325943,0.05992069],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01061444,"threshold_uncertainty_score":0.03550881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01437108832531236,"score_gpt":0.1929831252081435,"score_spread":0.1786120368828312,"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."}}