Five-Column Chromatography Separation for Simultaneous Determination of Hard-to-Detect Radionuclides in Water and Swipe Samples
Bibliographic record
Abstract
There is a growing demand for the rapid determination of hard-to-detect radionuclides in environmental and biological samples for environmental monitoring, radiological protection, and nuclear forensic reasons. A new method using five-column chromatography separation has been developed for the simultaneous determination of Pu, Np, Th, U, Am, Cm, Pm, Y, and Sr isotopes, as well as iron-55, by inductively coupled mass spectrometry (ICPMS), α spectrometry, Čerenkov and liquid scintillation (LS) counting. Spiked swipe and water samples as well as proficient testing water standards were analyzed to validate the separation procedure, and the results are in good agreement with the expected values. The method provides quick sample turnaround time and high analysis throughput with low analysis cost. The flexibility of the method also allows for its easy adaptation to various emergency and routine radioassays.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".