Determining spontaneous fission properties by direct mass measurements with the FRS Ion Catcher
Bibliographic record
Abstract
We present a direct method to measure fission product yield distributions (FPY) and isomeric yield ratios (IYR) for spontaneous fission (SF) fragments. These physical properties are of utmost importance to the understanding of basic nuclear physics, the astrophysical rapid neutron capture process ('r process') of nucleosynthesis, neutron star composition, and nuclear reactor safety. With this method, fission fragments are produced by spontaneous fission from a source that is mounted in a cryogenic stopping cell (CSC), thermalized and stopped within it, and then extracted and transported to a multiple-reflection time-of-flight mass-spectrometer (MR-TOF-MS). We will implement the method at the FRS Ion Catcher (FRS-IC) at GSI (Germany), whose MR-TOF-MS relative mass accuracy (~ 10-7) and resolving power (~ 600,000 FWHM) are sufficient to separate all isobars and numerous isomers in the fission fragment realm. The system's essential element independence and its fast simultaneous mass measurement provide a new direct way to measure isotopic FPY distributions, which is complementary to existing methods. It will enable nuclide FPY measurements in the high fission peak, which is hardly accessible by current techniques. The extraction time of the CSC, tens of milliseconds, enables a direct measurement of independent fission yields, and a first study of the temporal dependence of FPY distributions in this duration range. The ability to resolve isomers will further enable direct extraction of numerous IYRs while performing the FPY measurements. The method has been recently demonstrated at the FRS-ICr for SF with a 37 kBq 252Cf fission source, where about 70 different fission fragments have been identified and counted. In the near future, it will be used for systematic studies of SF with a higher-activity 252Cf source and a 248Cm source. The method can be implemented also for neutron induced fission at appropriate facilities.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".