Emergency Radiobioassay Method for Determination of <sup>90</sup>Sr and <sup>226</sup>Ra in a Spot Urine Sample
Bibliographic record
Abstract
A new radiobioassay method has been developed for simultaneous determination of (90)Sr and (226)Ra in a spot urine sample. The method is based on a matrix removal procedure to purify the target radionuclides from a urine sample followed by an automated high performance ion chromatographic (HPIC) separation of (90)Sr and (226)Ra and offline radiometric detection by liquid scintillation counting (LSC). A Sr-resin extraction chromatographic cartridge was used for matrix removal and purification of (90)Sr and (226)Ra from a urine sample prior to its introduction to the HPIC system. The HPIC separation was carried out through cation exchange chromatography using methanesulfonic acid (75 mM) as the mobile phase at 0.25 mL/min flow rate. The performance criteria of the method was evaluated against the American National Standard Institute ANSI/HPS N13.30-2011 standard for the root mean squared error (RMSE) of relative bias (Br) and relative precision (SB) at two different spiked activity levels. The RMSE of Br and SB for (90)Sr and (226)Ra were found to be satisfactory (≤0.25). The minimum detectable activity (MDA) of the method for (90)Sr and (226)Ra are 2 Bq/L and 0.2 Bq/L, respectively. The MDA values are at least 1/10th of the concentrations of (90)Sr (190 Bq/L) and (226)Ra (2 Bq/L) excreted in urine on the third day following an acute exposure (inhalation) that would lead to an effective dose of 0.1 Sv in the first year. The sample turnaround time is less than 8 h for simultaneous determination of (90)Sr and (226)Ra.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".