Bibliographic record
Abstract
Vaccination is one of the most successful public health achievements of human history. However, like any drug, no vaccine is absolutely safe. As the incidence of vaccine-preventable diseases has been effectively controlled by vaccines, the safety of vaccines inoculated in healthy people has attracted more and more attention. The United States is the earliest country to start vaccine safety management. After some major vaccine safety incidents, vaccine safety management has gradually developed and improved. Vaccine safety regulator in the United States mainly consists of 4 federal agencies: the Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), the National Institutes of Health (NIH), and the Health Resources & Services Administration (HRSA). FDA is mainly responsible for pre-market registration and approval of vaccines, and supervision and inspection of vaccine manufacturers. CDC is mainly responsible for making immunization planning, monitoring of vaccine adverse reactions, and management of free vaccine projects of government. NIH is mainly responsible for vaccine research and development. HRSA is mainly responsible for vaccine accident compensation. In addition, the experience of European Medicines Agency in limitation of validity period of vaccine license and vaccine quality management and the experiences in safety management of vaccines in Canada, Britain, Australia and New Zealand, including cold chain management, surveillance of vaccine adverse events, etc. are worthy of learning. Key words: Vaccines; Safety; Public health administration; Adverse Drug Reaction Reporting Systems; United States
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".