Preparation and application of steeps of tea as new simulations of urine for the performance testing programme of 14C
Bibliographic record
Abstract
(14)C is one of the radionuclides for which the Canadian Nuclear Safety Commission has developed performance testing programmes (PTPs). During the PTP exercises, clients receive samples of natural urine containing spiked radionuclides, for testing. In these programmes, urine has disadvantages. These include (1) slow collection times from donors, (2) unpleasant smell and (3) potential to transmit diseases. To assist in solving some of these problems, the Canadian National Calibration Reference Centre for Bioassay and In Vivo Monitoring has conducted research with tea solutions, to find simpler, safer and more readily available alternatives to urine. This paper provides a new technique by which steeps of black tea have been successfully prepared for the (14)C PTP. The results of tea solutions compared well with those of urine. It was concluded that tea steeps, of which the spectroscopic and colour quenching properties have been adjusted, do provide appropriate urine simulations, suitable for use in PTPs.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".