QUICKSCAN DICENTRIC CHROMOSOME ANALYSIS FOR RADIATION BIODOSIMETRY
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The dicentric chromosome assay (DCA) is the gold-standard assay for accurately estimating unknown radiological doses to individuals following radiological or nuclear accidents. However in a mass-casualty scenario, this assay is not well suited for providing timely dose estimates due to its time- and expertise-intensive nature. In Canada, two approaches are being developed in an attempt to increase triage-quality biological dosimetry throughput. These are 1) increasing the number of trained personnel capable of conducting the DCA, and 2) evaluating alternative biodosimetry approaches or DCA variations. In a recent exercise, a new scoring technique (termed DCA QuickScan) was evaluated as an alternative rapid-scoring approach. Triage-quality conventional DCA and DCA QuickScan analysis were based upon scoring a minimum of 50 metaphase cells or 30 dicentrics by 9-15 scorers across four laboratories. Dose estimates for the conventional DCA were found to be within 0.5 Gy of the actual dose for 83% of the unknown samples, while DCA QuickScan dose estimates were within 0.5 Gy for 80% of the samples. Of the dose estimates falling 0.5 Gy or more outside the actual dose, the majority were dose over-estimates. It was concluded that the DCA QuickScan approach can provide critical dose information at a much faster rate than the conventional DCA without sacrificing accuracy. Future studies will further evaluate the accuracy of the DCA QuickScan method.
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.
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 | 0.000 | 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 it