The capacity, capabilities and needs of the WHO biodosenet member laboratories
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
Biodosimetry is an essential tool for providing timely assessments of radiation exposure, particularly when physical dosimetry is unavailable or unreliable. For mass-casualty events involving public exposure to ionising radiation, it is paramount to rapidly provide this dose information for medical management of casualties. The dicentric chromosome assay is currently the most reliable accepted method for biodosimetry; however, in a mass-casualty scenario, the throughput of this assay will be challenged by its time-consuming nature and the specific expertise required. To address this limitation, many countries have established expertise in cytogenetic biodosimetry and started developing surge capabilities through setting up regional networks to deal with emergency situations. To capitalise on this growing expertise and organise it into an internationally coordinated laboratory network, the World Health Organization has created and launched a global biodosimetry network (BioDoseNet). In order to determine the existing capacity of BioDoseNet member laboratories, including their expertise and in vivo experience, involvement in national and international activities, problems, needs and prospects, an in-depth survey was conducted. These survey results provide significant information on the current state of emergency cytogenetic biodosimetry capabilities around the world.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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