Additional file 1 of Global impact and cost-effectiveness of one-dose versus two-dose human papillomavirus vaccination schedules: a comparative modelling analysis
Bibliographic record
Abstract
Additional file 1: Table 1. Transmission dynamic model description. Table 2. Vaccination strategies. Table 3. World Bank income group. Table 4. Inputs: HPV-FRAME reporting standard checklist. Table 5. Inputs: HPV-FRAME reporting standard checklist (Continued). Table 6. Outputs: HPV-FRAME reporting standard checklist. Table 7. Internal validation. Figure 1. Cumulative cervical cancers averted by routine one-dose HPV vaccination by income groups, no discounting. Figure 2. Cervical cancer deaths averted by routine one-dose HPV vaccination by income groups, no discounting. Figure 3. Cervical cancers averted by routine one-dose HPV vaccination by income groups, discounted. Figure 4. Cervical cancer deaths averted by routine one-dose HPV vaccination by income groups, discounted. Figure 5. Cumulative cervical cancers averted by routine one-dose HPV vaccination by income groups, discounted. Figure 6. Proportion of cervical cancers averted by 1-dose compared to a perfect vaccine, discounted. Figure 7. Proportion of cervical cancer deaths averted by 1-dose compared to a perfect vaccine. Figure 8. Cervical cancers averted by routine one-dose HPV vaccination by income groups with a 2-valent vaccine. Figure 9. Cervical cancers averted by routine one-dose HPV vaccination by income groups at lower coverage. Figure 10. Proportion of cervical cancer deaths averted by 1-dose compared to a perfect vaccine at lower coverage. Figure 11. Proportion of cervical cancer averted by 1-dose compared to a perfect vaccine when vaccination is delayed. Figure 12. Cervical cancers averted by routine one-dose HPV vaccination by income groups at when vaccination is delayed. Figure 13. Threshold cost to pay for the first and second dose of vaccine, discounting on health outcomes and costs. Figure 14. Threshold cost to pay for the first and second dose of vaccine, no discounting. Figure 15. Number of girls needed to be vaccinated to avert one additional case over the years 2021–2120.
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.814 | 0.064 |
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".