Development of a medical resource database for radiological emergency preparedness
Bibliographic record
Abstract
In order for Canada to be better prepared to respond quickly to a radiological or nuclear emergency detailed knowledge regarding the locations and capacities of hospitals, relevant medical supplies and radiological or nuclear professionals is needed. These key points of information were identified at a CRTI workshop in 2009, and it was proposed that a medical resource database (MRD) was required. This database is in addition to the development of a radiation accident registry which was also proposed at the CRTI Workshop in 2009. The MRD has been designed, built and populated where possible; it is now ready for field testing and deployment. The creation of the database is one more step towards a better and more effective response in a radiological or nuclear emergency. In order to maintain this database and keep it up to date, contributions from all levels of radiation protection professionals will be needed. In this paper, the database structure and the data collected will be presented and discussed.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".