Baseline assessment of a potassium iodide distribution for nuclear power plant emergencies in the Canadian-United States border region
Bibliographic record
Abstract
OBJECTIVE: This study sought to evaluate resident demographics and resident understanding of the proper use of potassium iodide (KI) pills as a countermeasure in the event of a nuclear power plant emergency. We also described expected behaviors of community members in the event of a nuclear accident. DESIGN: The study design utilized a cross-sectional survey with a validated written questionnaire. Subjects, Participants: The study subjects were Canadian residents living within the primary emergency planning zone of the Fermi 2 nuclear power reactor. There was a 77 percent participation rate (n = 180) in Amherst Point and 61 percent for Bois Blanc Island (commonly referred to as Bob-Lo Island) (n = 57). MAIN OUTCOME MEASURE(S): The primary study outcome measures were the number of knowledge-based questions survey respondents correctly answered about proper KI use (Ksum) and various behavior-based survey questions in the context of the extended parallel process model (EPPM). RESULTS: Overall, we found that residents in general had a very low overall comprehension of proper KI use. We found that most resident demographics (eg, age, gender) did not significantly impact their knowledge of proper KI use but did find that households with children under 13 years of age tended to have higher comprehension scores than households without young children. Most residents reported that if they thought they were exposed to radiation they would go to the hospital or call 911 and few residents knew their evacuation routes, few were aware of the emergency siren, none knew where the reception center was located, and most did not have an emergency kit in their home. The majority of the survey respondents did indicate that they would evacuate if told to do so by their government. CONCLUSIONS: Public health outreach is crucial for KI distribution programs because of the overall low pre-existing comprehension in communities. Also, hospitals and 911 must be prepared to deal with higher volume of residents seeking help should an accident occur.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".