Rapid Preparation of Polonium Counting Sources for Alpha Spectrometry Using Copper Sulfide Microprecipitation
Bibliographic record
Abstract
Thin-layer polonium (Po) sources for alpha spectrometry counting can be rapidly prepared using copper sulfide (CuS) microprecipitation. Polonium was coprecipitated with CuS, filtered onto Eichrom Resolve filters, and counted. This simple procedure is faster, cheaper, and more convenient than traditional spontaneous plating on metallic discs, and similar yields were obtained (80-90%). The experimental conditions for the microprecipitation technique were optimized (0.05 mg of Cu(2+) in 10 mL of 1 M HCl); these compare advantageously with conventional preparation and purification procedures for polonium samples (0.1 to 1 M HCl). The results showed that the most likely potential radionuclide interferences (Ra, Th, U, Np, Pu, and Am) for long-lived polonium isotopes ((208)Po, (209)Po, (210)Po) are effectively removed during processing. The effects of several transition metals (Cu(2+), Ag(+), Fe(3+), Fe(2+), Pb(2+), and Ni(2+)) on the yield and the resolution of the alpha peaks obtained were also assessed. Little interference was found, demonstrating the versatility of the present microprecipitation technique for environmental and biological matrices. The procedure has been successfully applied to different amounts of (210)Po using (209)Po as a yield tracer.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".