Combating Nuclear Smuggling: DHS has Developed Plans for Its Global Nuclear Detection Architecture, but Challenges Remain in Deploying Equipment
Bibliographic record
Abstract
Testimony issued by the Government Accountability Office with an abstract that begins "Over the past 10 years, DHS has made significant progress in deploying radiation detection equipment to scan for nuclear or radiological materials in nearly all trucks and containerized cargo coming into the United Stated through seaports and border crossings. However, challenges remain for the agency in developing a similar scanning capability for railcars entering this country from Canada and Mexico, as well as for international air cargo and international commercial aviation. As portal monitors approach the end of their expected service lives, observations from our past work may help DHS as it considers options to refurbish or replace such monitors. Among other things, we have previously reported that DHS should (1) test new equipment rigorously prior to acquisition and deployment, (2) obtain the full concurrence of the end user to ensure that new equipment meets operational needs, and (3) conduct a cost-benefit analysis to inform any acquisition decisions. In our past work on the GNDA, we recommended that DHS develop an overarching strategic plan to guide the development of the GDNA, as well as a strategic plan for the domestic part of the global nuclear detection strategy. DHS took action on these recommendations and, in December 2010, it issued the interagency GNDA strategic plan. We reported, in July 2011, that the GNDA strategic plan addressed several of the aspects of our prior recommendations but did not (1) identify funding necessary to achieve plan objectives or (2) employ monitoring mechanisms to determine progress and identify needed improvements. In April 2012, DHS issued its GNDA implementation plan, which addresses the remaining aspects of our recommendations by identifying funding dedicated to plan objectives and employing monitoring mechanisms to assess progress in meeting those objectives. However, in both the GNDA strategic plan and the implementation plan, it remains difficult to identify priorities from among various components of the domestic part of the GNDA."
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.032 | 0.010 |
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".