Hawaii Veterinarians' Bioterrorism Preparedness Needs Assessment Survey
Bibliographic record
Abstract
The purpose of this study was to assess the objective bioterrorism-related knowledge base and the perceived response readiness of veterinarians in Hawaii to a bioterrorism event, and also to identify variables associated with knowledge-based test performance. An anonymous survey instrument was mailed to all licensed veterinarians residing in Hawaii (N = 229) up to three times during June and July 2004, using numeric identifiers to track non-respondents. The response rate for deliverable surveys was 59% (125 of 212). Only 12% (15 of 123) of respondents reported having had prior training on bioterrorism. Forty-four percent (55 of 125) reported being able to identify a bioterrorism event in animal populations; however, only 17% (21 of 125) felt able to recognize a bioterrorism event in human populations. Only 16% (20 of 123) felt they were able to respond effectively to a bioterrorist attack. Over 90% (106 of 116) expressed their willingness to provide assistance to the state in its response to a bioterrorist event. Veterinarians scored a mean of 70% correct (5.6 out of 8 questions) on the objective knowledge-based questions. Additional bioterrorism preparedness training should be made available, both in the form of continuing educational offerings for practicing veterinarians and as a component of the curriculum in veterinary schools.
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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 | 0.000 | 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 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".