The Importance of Dosimetry Standardization in Radiobiology
Bibliographic record
Abstract
Radiation dose is central to much of radiobiological research. Precision and accuracy of dose measurements and reporting of the measurement details should be sufficient to allow the work to be interpreted and repeated and to allow valid comparisons to be made, both in the same laboratory and by other laboratories. Despite this, a careful reading of published manuscripts suggests that measurement and reporting of radiation dosimetry and setup for radiobiology research is frequently inadequate, thus undermining the reliability and reproducibility of the findings. To address these problems and propose a course of action, the National Cancer Institute (NCI), the National Institute of Allergy and Infectious Diseases (NIAID), and the National Institute of Standards and Technology (NIST) brought together representatives of the radiobiology and radiation physics communities in a workshop in September, 2011. The workshop participants arrived at a number of specific recommendations as enumerated in this paper and they expressed the desirability of creating dosimetry standard operating procedures (SOPs) for cell culture and for small and large animal experiments. It was also felt that these SOPs would be most useful if they are made widely available through mechanism(s) such as the web, where they can provide guidance to both radiobiologists and radiation physicists, be cited in publications, and be updated as the field and needs evolve. Other broad areas covered were the need for continuing education through tutorials at national conferences, and for journals to establish standards for reporting dosimetry. This workshop did not address issues of dosimetry for studies involving radiation focused at the sub-cellular level, internally-administered radionuclides, biodosimetry based on biological markers of radiation exposure, or dose reconstruction for epidemiological studies.
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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 | 0.354 | 0.350 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.006 | 0.023 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.009 | 0.020 |
| 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".