An overview of new data on the relative effectiveness of flu vaccines in vulnerable populations
Bibliographic record
Abstract
As healthcare professionals prepare for flu season in a pandemic year, the results of three large, population-based U.S. studies now provide comparisons of the relative effectiveness (rVE) of the available flu vaccine formulations in high-risk patients. In a study published in August 2020, a vast retrospective cohort analysis of almost 2 million U.S. patients over 65 years old compared adjuvanted to non-adjuvanted flu vaccine. In September, 2020, a prospective study in 823 U.S. nursing homes provided a similar comparison in more than 50,000 patients. Also last month, a retrospective cohort analysis of over 3 million U.S. patients yielded rVE data for egg-based versus cell-based vaccines in high-risk patients aged 4–64. The goal of this literature alert is to provide an overview of these new studies to Canadian healthcare professionals preparing for this year’s flu season.
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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 | 0.013 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".