Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
SCADA systems are widely used in power systems for monitoring, operation and control purposes. Failure of the SCADA system can result in severe consequences such as customer load losses and equipment damages, etc. Evaluating these consequences at planning stage can help select the appropriate level of reliability of the SCADA systems. This paper presents a practical method for quantifying the risk associated with the failure of the SCADA systems utilized in power systems. The method first identifies the various components of risk and then evaluates each by considering overlap of the two events, failure of control by SCADA and failure of automatic operation of the power system network. The SCADA risk is calculated and expressed in terms of dollars on a station by station basis. The calculated risk can be used to rank a group of stations, to identify the importance of stations and to establish the reliability requirements for the SCADA system that has the lowest capital cost. The proposed method is applied to the Hydro One Transmission Networks System with its historical operating performance data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it