SOCIAL ISOLATION MEASURES CAUSE REDUCTION IN THE CONTAMINATION AND DEATHS BY COVID-19? THE CASE OF THE MUNICIPALITY OF ARARAQUARA, SP, BRAZIL
Bibliographic record
Abstract
A pandemia SARS-Cov-2 estabeleceu a necessidade de adoção de medidas restritivas para conter a disseminação do vírus. Em 2021, devido ao elevado número de casos de COVID-19 no município de Araraquara, Brasil, e após o esgotamento das vagas hospitalares em 2021, foi anunciado um bloqueio. Analisamos o efeito do distanciamento social dessa cidade, utilizando dados fornecidos pela prefeitura municipal ao longo de um período total de 90 dias. Usamos esses dados em uma tabela de vida, uma importante ferramenta que avalia o impacto de doenças na dinâmica populacional de uma espécie. Os resultados indicaram uma taxa básica de mortalidade de 0,0138 no período analisado e uma redução considerável no número de casos infectados e óbitos por COVID-19 após 24 dias de isolamento. Nossos resultados mostraram a eficácia do distanciamento social em conter a propagação da doença, com redução de 80% no número de óbitos, bem como a utilidade da tábua de vida como ferramenta útil para análise de dados.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".