Why the global south is integral to the development of next-generation COVID-19 vaccines and antibody therapeutics
Bibliographic record
Abstract
The threshold level of immunization coverage needed to confer population immunity for COVID-19 is not yet known, although some settings may require up to 85% of the population to be vaccinated for vaccine-induced population immunity to apply. Achieving such a goal may prompt some countries to contemplate mandating COVID-vaccination. However, attaining a threshold level of population immunity, even via vaccination mandates, is not necessarily a panacea. The emergence of variants that escape immune responses could also render a setting’s previous attainment of population immunity meaningless. The extent to which immune responses protect against emerging variants is of increasing importance and speaks to the need for countries to urgently step up genomic surveillance for SARS-CoV-2 variants and openly share that data timeously. Emerging variants also underscore why COVID-19 candidate vaccines and antibody therapeutics should be trialled in diverse geographical settings. Such approaches will catalyse the development of effective next-generation COVID-19 vaccines and antibody therapeutics. © 2021, University of Toronto. All rights reserved.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".