A Rapid and Efficient Autoclave Pre-Treatment to Extract Iodine-129 from Urine Samples for AMS Analysis
Bibliographic record
Abstract
A new method was developed to extract 129I from urine samples and then measure it by AMS. The samples were pre-treated in an autoclave with hydrogen peroxide to remove unwanted compounds from the urine samples and were acidified with nitric acid, followed by precipitation of iodine as silver iodide (AgI) for measurement by AMS. This new procedure is substantially faster than previous methods for the extraction of iodine from urine and results in less chemical waste. The efficiency and reproducibility of this method were evaluated by using 125I as a yield tracer, eventually giving a recovery above 99%. To achieve this, several iterations of the method were required. The method was then successfully applied to measure 129I/127I isotopic ratios and 129I concentrations in 25 human urine samples. The AMS results for 129I in urine ranged 3.3 x 106 atoms/L to 884 x 106 atoms/L and the isotope ratio (129I/127I) in human urine ranged from 7.38 x 10-12 to 3.97 x 10-10 with a median of 1.29 x 10-10. This new method will be useful for investigations into the sources of iodine in the human diet and their relative importance for iodine sufficiency.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".