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Record W4293069813 · doi:10.32413/pjph.v11i4.848

Should Children in Pakistan be vaccinated? Is there any Evidence?

2022· article· en· W4293069813 on OpenAlexaboutno aff
Syed Jaffar Abbas Zaidi, Qaiser Ali Baig, Shahida Maqsood

Bibliographic record

VenuePakistan Journal of Public Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsVaccinationHerd immunityMedicinePandemicPopulationEnvironmental healthPrivilege (computing)PediatricsCoronavirus disease 2019 (COVID-19)ImmunologyPolitical scienceDiseaseLaw

Abstract

fetched live from OpenAlex

In Pakistan, where the vaccination rate is dismally low and where the huge population remains unvaccinated, vaccination in children might be considered a privilege and a luxury. But with several countries such as Canada, United States, China, Indonesia, and Israel forging ahead with vaccinating children and the United Kingdom slowly following their footsteps and with mounting evidence, it might not be prudent to keep children side-lined from vaccination in Pakistan. This paper presents some evidence for vaccination in children and highlights the need and urgency for vaccinating children in Pakistan. Clinical trials of Pfizer/NBiotech, Moderna and SinoVac’s CoronaVac has shown promising results and higher antibody titres in children as compared to adults. For herd immunity to be effective and to curb this pandemic, it is prudent to initiate vaccination in children in Pakistan at the earliest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.114
GPT teacher head0.420
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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