Bibliographic record
Abstract
Electropolishing is a rapid and effective technique for removing plutonium and other radionuclide contamination from a variety of metal surfaces. The major objective of this continuing research is to develop electropolishing into a large-scale decontamination technique that can completely and economically remove transuranic and other surface contamination from large volumes of metallic waste. These research studies have demonstrated the ability of electropolishing to reduce the radiation levels of steel tools and stainless steel vacuum system components, which were heavily contaminated with plutonium oxide. Other examples of objects that have been decontaminated within minutes using electropolishing include hot cell manipulator assemblies, analytical instrument components, laboratory transfer containers, offsite shipping containers, fission product storage capsules, laboratory animal cages, and nuclear reactor process tube components. One of the major activities of this research has been the establishment and intensive operation of a 400-gal immersion electropolishing system designed specifically to develop and demonstrate decontamination techniques for representative plutonium- and beta/gamma-contaminated components. Substantial progress has also been made in developing in situ electropolishing techniques that can be used to decontaminate metallic surfaces that cannot readily be transported to or immersed in a conventional electropolishing tank. Sectioning/pretreatment studies are underway to develop and demonstrate optimum disassembly, sectioning, surface preparation, and gross contamination removal procedures. Other supporting studies are also in progress to provide a sound technical basis for scale-up and widespread application of this new decontamination process.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.973 | 0.981 |
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; the direct Gemma label and the distilled Codex classifier 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".