Prototype neutron-capture counter for fast-coincidence assay of plutonium in residues
Bibliographic record
Abstract
A new neutron coincidence counter with improved capabilities is being built as a commercial prototype. This counter uses {sup 6}LiF/ZnS(Ag) based scintillation detectors to achieve a short neutron die-away time ({tau} < 5 {micro}s), which increases the sensitivity of the counter to measurements of {sup 240}Pu by neutron coincidence counting. Greater sensitivity is required for measurements of residues, whose large {alpha},n-neutron yields create a high accidental coincidence rate in a counter with a relatively long {tau} (for example, ones that use {sup 3}He detectors). Traditional problems of gamma-ray sensitivity in scintillation detectors have been overcome through pulse processing techniques. Intrinsic differences of the excitation processes associated with neutron and gamma-ray interactions in the {sup 6}LiF/ZnS(Ag) detector allow these particles to be separated via pulse shape analysis (PSA). Degree of neutron/gamma-ray separation, factors affecting separation, neutron detection efficiency, and the effects of pulse shape and energy thresholds in a small test detector using a combination of commercially available and custom electronics are discussed. Final custom pulse processing techniques and PSA results are also presented.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".