Fighting Pandemics: Inspiration from Islam
Bibliographic record
Abstract
Infectious disease has killed more people than any other cause throughout history. The current pandemic of coronavirus disease (COVID-19) has again revealed how vulnerable we remain. Muslims constitute the world's second-largest religious group, making up about a quarter of the world population. They have distinctive faith and culture, pertaining to their religious beliefs and practices that need special attention, in situations such as current COVID-19 pandemic. Congregational prayers are an indispensable part of Islamic culture. Performance of obligatory prayers in congregation is compulsory and mandatory for every Muslim adult male who has no excuse for not doing so. But, doing so during a pandemic can help in the spread of the COVID-19. Muslims look up to the Holy Qur'an and teachings of Prophet (PBUH) (Hadiths) for guidance under all the circumstances. In this review we will cover how Islamic teaching can guide us to manage pandemics like COVID-19.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".