Children as vulnerable populations in radiological/nuclear events: discussion scenarios
Bibliographic record
Abstract
A workshop to discuss Canada's preparedness to properly manage and treat children during radiological/nuclear (R/N) events was held in Ottawa, Canada, on 1-2 June 2010. This workshop provided a platform for participants of varied backgrounds including medicine, radiological and nuclear physics as well as child care, to discuss the strength and shortcoming of the currently implemented practices and procedures in Canada for the treatment and management of contaminated and/or exposed children during R/N events. To aid this discussion, scenarios (vignettes) involving the malicious use of radiological material were presented and discussed from the perspective of the emergency response focusing specifically on children. From these discussions, it was concluded that the management of children during R/N events is vastly different from the management of adults, and requires a specific set of protocols and procedures, not yet outlined in Canadian documentation. This paper is not meant to discuss existing response protocols during R/N events, but rather to discuss the deficiencies in planning and suggested improvements/revisions raised through discussion at the workshop on how to better manage children during an R/N event.
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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 | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.043 | 0.014 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".