Nuclear Regulatory Commission: Oversight of Underground Piping Systems Commensurate with Risk, but Proactive Measures Could Help Address Future Leaks
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "All U.S. nuclear power plant sites have had some groundwater contamination from radioactive leaks, and some of these leaks came from underground piping systems. The Nuclear Regulatory Commission (NRC) regulates nuclear power plants to protect public health and the environment from radiation hazards. GAO was asked to (1) determine experts' opinions on the impacts, if any, of underground piping system leaks on public health and the environment; (2) assess NRC requirements of licensees for inspecting these systems and monitoring and reporting on leaks; (3) identify actions the nuclear power industry, licensees, and NRC have taken in response to leaks; and (4) identify additional NRC requirements, if any, that key stakeholders think could help prevent, detect, and disclose leaks. GAO convened expert discussion groups through the National Academy of Sciences and asked experts to review three case studies, analyzed documents, visited seven plant sites and two NRC regional offices, and interviewed stakeholders."
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".