NON-DESTRUCTIVE EXAMINATION USING NEUTRONS: A NUCLEAR WASTE AND ORPHANED SOURCE CHARACTERIZATION CASE STUDY APPLICABLE TO NUCLEAR FORENSICS
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
Found unknown radioactive material is often contained in a package so the chemical and physical form of the material itself is unknown, and the detail of the packaging is likewise unknown. Together, these present a significant risk on how to handle the package for destructive examination of its contents. Whether of nefarious origin or the result of less stringent practices of yesteryear the material needs to be properly identified and characterized for appropriate disposition. Results of neutron imaging, neutron diffraction, and delayed neutron analysis as applied to an examination of sealed capsules containing unknown radioactive materials are presented. The results demonstrate that neutron-based non-destructive examination techniques can be employed for inspecting encapsulated radioactive samples to identify the materials, to elucidate the internal physical structure of the radioactive material and encapsulation, and to estimate the mass of fissile and fissionable materials within. This characterization of orphaned radioactive special nuclear material illustrates the potential for these techniques in nuclear forensics investigations.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it