Bibliographic record
Abstract
We read with interest the results of the study by Dr Mills and colleagues regarding the use of a modified intradermal (ID) preexposure rabies vaccination schedule [two ID doses on each of days 0 and 7 and a single ID dose with serology on days 21 to 28 (TRID2 schedule)].1 Their results suggest that this approach “works” in seroconverting to an acceptable antibody level almost all participants using the TRID2 schedule. We acknowledge that the TRID2 schedule could afford some advantage where time is short and the typical approach (single ID doses on days 0, 7, and 28 followed by serology 2 to 3 weeks after the last ID dose) is not feasible. However, we suggest that the utility of the study could have been substantially enhanced if additional schedules had been evaluated, in particular, a parallel schedule wherein only single ID doses are provided on days 0 and 7. There is evidence that even a single ID dose on day 0 will seroconvert to an acceptable antibody level, at 1 month post‐vaccination, most [97/101 (96%)] vaccinees, 2 similar to the TRID2 schedule; it is suspected that giving a single ID dose at 0 and at 7 days would enhance the seroconversion rate and antibody level even further. Also, in a small study, single ID doses at 0, 3, and 7 days were associated with an acceptable antibody level at 1 year post‐vaccination in 15/16 (94%) of vaccinees.3 Using single ID doses vice the TRID2 dosing may well achieve similar seroconversion rates but reduce the cost (the TRID2 dosing entails five doses of vaccine while the usual ID dosing schedule only uses three doses of vaccine, ie, 60% of the vaccine cost) and avoids having to use an “off‐label” approach as in the TRID2 schedule. The views expressed in this letter are those of the authors and not necessarily those of the Department of National Defence of Canada.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".