Detection of <sup>135</sup> Cs by accelerator mass spectrometry
Bibliographic record
Abstract
RATIONALE: The ability to measure both (135) Cs and (137) Cs can provide an estimate of the age and source of Cs isotopes in an environmental sample. Accelerator mass spectrometry (AMS) consistently reports lower abundance sensitivities than other techniques and, with the addition of an on-line reaction cell, simpler isobaric suppression. Therefore, an AMS methodology was developed to measure Cs isotopes using CsF2- as the initial anion. METHODS: The ion beam is passed through the Isobar Separator for Anions (ISA) where it is captured by radiofrequency quadrupoles in a gas cell before injection into the tandem accelerator. In the ISA, the beam reacts with O2 gas, selectively removing the BaF2- and leaving the Cs analyte to be reaccelerated and sent through the remainder of the AMS system. RESULTS: The BaF2- signal was attenuated by a factor of 10(5) in the ISA while 25% of the original CsF2- current was transmitted into the accelerator. (135) Cs was measured without any interference from (133) Cs to an abundance sensitivity of 1.3 × 10(-10) . The abundances of four stable Ba isotopes (masses 133, 134, 135 and 137) were measured and no isotope-dependent bias was detected using the ISA in vacuum. CONCLUSIONS: The results demonstrate the feasibility of measuring long-lived Cs isotopes without Ba interference by AMS with on-line isobar separation and the ability to use shorter lived Cs isotopes for yield tracing.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".