Bibliographic record
Abstract
Many forces affect the final decision The introduction of a new vaccine is highly complex, particularly a new category of vaccine with no biological precedent. The new group B meningococcus vaccine Bexsero (4CMenB),1 developed using a genomic based reverse vaccinology approach,2 is a case in point. When a vaccine is targeted against a relatively common disease, the company usually sponsors a large randomised controlled trial to show that the vaccine works. Group B meningococcal infection is sufficiently rare, however, that such a trial is not feasible. In most countries, advice on vaccines and immunisation programmes is given to governments by independent committees. This advice includes data on vaccine effectiveness, the likelihood that the vaccine will confer herd immunity (protect some unimmunised people by reducing carriage or spread of disease), safety, and cost effectiveness. In the United Kingdom, the Joint Committee on Vaccination and Immunisation (JCVI) has such a role. In the UK,3 and in Australia, Canada, the United States, and many European countries, the government is not permitted in law to fund an immunisation programme unless the immunisation advisory committee says it is cost effective. Different countries allow different assumptions in the modelling, so they do not always reach the same decision. The process usefully distances …
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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 | 0.008 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.014 | 0.022 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".