Laboratory Intercomparison of the Cytokinesis-Block Micronucleus Assay
Bibliographic record
Abstract
The focus of the study is an intercomparison of laboratories' dose-assessment performances using the cytokinesis-block micronucleus (CBMN) assay as a diagnostic triage tool for individual radiation dose assessment. Homogenously X-irradiated (240 kVp, 1 Gy/min) blood samples for establishing calibration data (0.25-5 Gy) as well as blind samples (0.1-6.4 Gy) were sent to the participants. The CBMN assay was performed according to protocols individually established and varying among participating laboratories. The time taken to report dose estimates was documented for each laboratory. Additional information concerning laboratory organization/characteristics as well as assay performance was collected. The mean absolute difference (MAD) was calculated and radiation doses were merged into four triage categories reflecting clinical aspects to calculate accuracy, sensitivity and specificity. The earliest report time was 4 days after sample arrival. The CBMN dose estimates were reported with high accuracy (MAD values of 0.20-0.50 Gy at doses below 6.4 Gy for both manual and automated scoring procedures), but showed a limitation of the assay at the dose point of 6.4 Gy, which resulted in a clear dose underestimation in all cases. The MAD values (without 6.4 Gy) differed significantly (P = 0.03) between manual (0.25 Gy, SEM = 0.06, n = 4) or automated scoring procedures (0.37 Gy, SEM = 0.08, n = 5), but lowest MAD were equal (0.2 Gy) for both scoring procedures. Likewise, both scoring procedures led to the same allocation of dose estimates to triage categories of clinical significance (about 83% accuracy and up to 100% specificity).
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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 | 0.036 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".