Balancing Vaccine Science and National Policy Objectives: Lessons From the National Vaccine Injury Compensation Program Omnibus Autism Proceedings
Bibliographic record
Abstract
The US Court of Federal Claims, which adjudicates cases for the National Vaccine Injury Compensation Program, has been confronted with more than 5000 cases submitted on behalf of children with autism spectrum disorders, seeking to link the condition to vaccination. Through a test case process, the Omnibus Autism Proceedings have in every instance found no association between autism spectrum disorders and vaccines. However, vaccine advocates have criticized the courts for having an overly permissive evidentiary test for causation and for granting credence to insupportable accusations of vaccine harm. In fact, the courts have functioned as intended and have allowed for a fair hearing of vaccine concerns while maintaining confidence in vaccines and providing protection to vaccine manufacturers.
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 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 | 0.041 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.019 | 0.021 |
| Insufficient payload (model declined to judge) | 0.006 | 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".