Measuring <sup>210</sup> Pb by accelerator mass spectrometry: a study of isobaric interferences of <sup>204,205,208</sup> Pb and <sup>210</sup> Pb
Bibliographic record
Abstract
RATIONALE: The measurement of (210) Pb provides an assessment of the risk an individual faces of developing lung cancer as a result of their exposure to radon and radon decay products. Existing radiometric techniques are not sensitive enough to detect (210) Pb in many exposures. This report describes the further development of a method of measuring (210) Pb using Accelerator Mass Spectrometry (AMS). METHODS: (204,205,208,) (210) Pb measurements were performed by AMS. Samples were prepared from stock solutions of (204) Pb, (205) Pb, (208) Pb and (210) Pb and measured by making PbF3 (-) ions at the IsoTrace AMS facility using a SIMS-type Cs(+) sputter source. Potential interferences in Pb(3) (+) isotope measurement and the overall efficiency of Pb beam production were determined experimentally. RESULTS: (204) Pb and (205) Pb suffer from molecular and atomic isobaric interferences that cannot be removed without sacrificing the efficiency of (210) Pb measurements whereas (208) Pb suffers from no interferences. The abundance sensitivity of (210) Pb/(208) Pb was 1.3 × 10(-12) . Keeping the (210) Pb/(208) Pb spike below this level resulted in a detection limit of 4.4 mBq of (210) Pb using the IsoTrace AMS facility. CONCLUSIONS: This study identified key interferences in the measurement of PbF3 (-) → Pb(3) (+) ions and demonstrated a new AMS method to measure (210) Pb. This new AMS technique is about five times more sensitive than gamma and beta spectroscopy measurements of (210) Pb and the measurement time is much shorter. Copyright © 2016 John Wiley & Sons, Ltd.
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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) | 0.000 | 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 | 0.001 | 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 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".