CANDU FIRE PROBABILISTIC RISK ASSESSMENT (PRA) MODEL
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
Fire Probabilistic Risk Assessment (PRA) is being introduced to the fire protection engineering practice both locally and worldwide. The commercial nuclear power industry has also experiencing the impact of this new approach. This paper examines the work performed to assess the relative accuracy of fire models for CANDU nuclear power plant (NPP) applications. The Canadian NPP uses some portions of NUREG/CR-6850 in performing fire PRA. Canadian fire ignition frequencies have been provided by International Fire Data Exchange Project. The CANDU Fire PRA Model can quantitatively evaluate plant damage states and core damage frequencies. This model will assist fire engineers in performing CANDU Fire PRA analysis, by recognizing vulnerabilities related to fire events and will contribute to further improvement of the Canadian NPPs’ safety.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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