Scripting Real-Time Application Platform (RTAP) Panels: An Overview of the Terminal Swing Panel Project
Bibliographic record
Abstract
Enbridge Pipelines remotely controls the flow of approximately two-thirds of Canada’s crude oil and refined products produced from the Western Canadian Sedimentary basin through the Enbridge mainline pipeline system. These various products divided into batches run though multiple terminal systems. Each terminal site is unique and requires a multitude of specialized control systems to maintain its various flow patterns. To efficiently control these terminals Enbridge operators use the custom built PROCYS SCADA system. This system contains a graphical user interface containing schematics and panels that allow operator view and control. As part of this system a subset of control panels were developed and labeled swing panels. Swing panels allow operators to safely and efficiency run product through the various systems within a terminal. Swing panels have been in successful operation for over 10 years, however their development and maintenance cycles were less than optimal for operators and SCADA support staff. For this reason the Enbridge Terminal swing panel system was redesigned. These second generation swing panels were designed to use XML input files and Perl scripting to allow for automated construction. By encapsulating terminal swings in XML the swing panels are easier to maintain and build. This re-design resulted in a system of more functional, usable, and maintainable swing panels. The following paper will discuss this project in more detail.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".