Material control and accountability (MC&A) recovery from the Cerro Grande fire at Los Alamos National Laboratory
Bibliographic record
Abstract
During the week of May 10-14, 2000, the Cerro Grande Fire scorched over 40,000 acres of prime forestland and destroyed over 400 homes in the Los Alamos community and several structures at the Los Alamos National Laboratory (LANL). Of the land affected by the fire, nearly one quarter of it was Laboratory property. All of LANL's 64 material balance areas (MBAs) were affected to some degree, but one Category I technical area and several Category I11 and IV areas sustained heavy damage. When the MC&A personnel were allowed to return to work on May 23, they addressed the following problems: How do we assure both ourselves and the Department of Energy (DOE) that no nuclear materials had been compromised? How do we assist the nuclear material (NM) custodians and their operating groups so that they can resume normal MC&A operations? Immediately after the return to work, the Laboratory issued emergency MC&A assurance actions for Category I through Category IV facilities. We conducted special inventories, area walkthroughs, and other forms of evaluation so that within a month after the fire, we were able to release the last MBA to resume work and assure that all nuclear material had been accounted for. This paper discusses the measures LANL adopted to ensure that none of its nuclear material had been compromised.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".