Evaluation of Tea as a Matrix in a Dual (3H/14C) Performance Testing Program in Canada
Bibliographic record
Abstract
Urine is the most popular matrix used in performance testing programs (PTP) and inter-comparison programs (ICP) for bioassay. Because it comes from humans, there are concerns regarding its biosafety. For large programs, its collection can take several hours or days to complete. In addition, natural urine has an unpleasant smell, which tends to worsen with increasing storage time. In order to solve some of these problems, the Bioassay Section at the Radiation Protection Bureau in Health Canada has been investigating the use of tea in both PTP and ICP exercises. A method based on diluting tea steeps and scanning them in the UV-VIS range of the light spectrum to select appropriate concentrations as simulated urine for the programs has been published. So far, however, only single H and single C in tea have been studied. The results were found to be compatible and very successful under the S-106 standard of the Canadian Nuclear Safety Commission. This report is an extension of similar investigations and shows that tea samples spiked with both H and C (DUAL) are also compatible and produce excellent PTP results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".