大洗研究開発センター廃棄物管理施設における森林火災の及ぼす影響評価
Bibliographic record
Abstract
In response to new standards for regulating waste management facilities, it was carried out impact assessment of forest fires on the waste management facilities existed in Oarai Research and Development Center of Japan Atomic Energy Agency. At first, a fire spread scenario of forest fires was assumed. The intensity of forest fires was evaluated from field surveys, forest fire evaluation models and so on. As models of forest fire intensity evaluation, Rothermel Model and Canadian Forest Fire Behavior Prediction (FBP) System were used. Impact assessment of radiant heat to the facilities was carried out, and temperature change of outer walls for the assumed forest fires was estimated. The outer wall temperature of facilities was estimated around 160$^{\circ}$C at the maximum, it was revealed that it doesn't reach allowable temperature limit. Consequently, it doesn't influence the strength of concrete. In addition, a probability of fire breach was estimated to be about 20\%. This report illustrates an example of evaluation of forest fires for the new regulatory standards through impact assessment of the forest fires on the waste management facilities.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.051 |
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; both teacher heads agree on what is shown here.
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".