Field deployable technique for 90Sr emergency bioassay
Bibliographic record
Abstract
Rapid bioassay is very important for immediate and near-term consequence management, which includes identifying contaminated individuals and providing necessary medical intervention during a radiological or nuclear emergency. This paper reports the application of a newly developed bioassay technique for (90)Sr in urine on a field deployable instrument, the Triathler. Performance of this field technique for sensitivity, accuracy and repeatability is evaluated against bioassay criteria (ANSI N13.30). This field technique offers the following analytical merits: (1) minimum detectable activity of 121 Bq l(-1) when 20 ml of urine is used; (2) relative bias of 11.1 % and relative precision of 3.2 % at the level of 45 Bq per 20 ml of urine and (3) sample turnaround time of less than 1 h. The technique meets the requirements for emergency bioassay when a committed effective dose of 0.5 Sv is used as the action dose threshold for medical intervention. Sample throughput can be significantly improved if this technique is automated.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".