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Record W1497287745 · doi:10.7205/milmed.169.10.833

Health Effects of Anthrax Vaccination in the Canadian Forces

2004· article· en· W1497287745 on OpenAlexaffabout
Duncan Hunter, Dick Zoutman, Jeff Whitehead, Joan Hutchings, Ken MacDonald

Bibliographic record

VenueMilitary Medicine · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsDepartment of National DefenceQueen's University
Fundersnot available
KeywordsVaccinationAnthrax vaccinesMedicineChartMedical diagnosisPediatricsDemographyImmunologyImmunizationStatisticsPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to determine whether anthrax vaccine resulted in adverse health effects in Canadian Forces members 8 months after vaccination. METHODS: A quasi-experimental, retrospective chart review was undertaken for two groups within the Canadian Forces, one group that received anthrax vaccination and another that did not. Information on symptoms, diagnoses, and injuries for 848 persons for which there were approximately 35,000 chart entries was abstracted from charts over a 4.5-year period and was coded using the International Statistical Classification of Diseases and Related Health Problems, 10th edition. RESULTS: The chart retrieval rate was 84%. The mean number of chart entries per person was higher in the comparison group (43.4) than in the vaccine group (38.2). No statistically significant differences were seen in the percent change before and after vaccination in the number of chart entries for specific diagnoses and symptoms for the vaccine group compared with the comparison group. Visual inspection of the time trend in rates showed no unexplained increases in the rate of diagnosis and symptoms in the vaccine group after vaccination. CONCLUSION: This study found no evidence that the anthrax vaccination resulted in an increase in adverse health effects in the 8-month period after vaccination.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.287
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2004
Admission routes2
Has abstractyes

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