Do Dose Numbers Matter?
Bibliographic record
Abstract
BACKGROUND: The diversity of Canadian infant meningococcal C conjugate (MenC) vaccine programs is unique among countries providing MenC vaccines and offers a valuable opportunity to determine the optimal vaccine program. This longitudinal study assessed differences in seroprotection by 3 different vaccine schedules in children two years after receiving either 1 toddler MenC vaccine dose (1 dose), 1 infant and 1 toddler dose (2 doses), or 2 infant and 1 toddler MenC vaccine dose (3 doses). METHODS: Three similar cohorts of healthy infants from 1, 2 and 3 dose program areas were enrolled before to their 12 month toddler dose and vaccinated with MenC-tetanus toxoid (MenC-TT) conjugate vaccine. Sera obtained 2 years later were assayed for serogroup C bactericidal activity using standardized procedures with rabbit as the exogenous complement source. Serum bactericidal activity titers ≥1:8 were considered protective. RESULTS: Results were available for 384 children. Rates of seroprotection at 36 months of age were significantly different between the 1 and 3 dose programs, but confidence intervals overlapped between the 1 and 2 dose programs and between the 2 and 3 dose programs: 1 dose 92% (95% confidence interval: 86%-96%) versus 99% (95%-100%) with 2 doses and 100% (97%-100%) with 3 doses. Geometric mean titers were significantly different at 12.1 (10.8-13.5), 32.4 (28.9-36.2) and 50.6 (45.7-55.9) in the 1, 2 and 3 dose programs, respectively. CONCLUSIONS: At 36 months of age, evidence of seroprotection remained for greater than 90% of participants. Our results indicate that 1 toddler dose or 1 infant plus 1 toddler dose with MenC-TT vaccine provides seroprotection against MenC disease in early childhood.
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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 | 0.012 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.157 | 0.028 |
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".