HF Verification and Validation Activities: Simulator Based Operational Trials
Bibliographic record
Abstract
Changes to shutdown system (SDS) software were made at the Darlington Nuclear Generating Station. This is a four unit CANDU (Canadian Deuterium Uranium) nuclear power station located on the north shore of Lake Ontario (each unit is approximately 900 MW). These changes were initiated through an agreement with the Canadian nuclear regulator to improve the maintainability of the safety critical software. In addition, a number of functional changes were made, based on operational experience, to improve the operability and maintainability of the shutdown systems as a whole. The integration of Human Factors Engineering (HFE) into the systems design process was achieved using a Human Factors Engineering Program Plan (see Beattie and Malcolm, 1991 for a discussion of this type of planning document). The HFE program steps were taken from NUREG 0711 - Human Factors Engineering Program Review Model (U.S. NRC, 1994). The program plan included formal HFE Verification and Validation, culminating with operational trials in the full-scale control room training simulator. Results indicated that all functional changes passed on all performance criteria, and that the measures showed a high degree of convergent validity.
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.
How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".