Bibliographic record
Abstract
Animals’ protection is crucial for environmental stability and sustainability. Animals are the sign of magnificence and benevolence of Allah Almighty. The divine teachings of Islam provide a complete code for the welfare and protection of animals. Today the world has recognized the need for animals’ protection to maintain ecological balance. The ecological scientist has laid stress on animal rights and there is a great debate over the basic rights and liberties of animals. In the last few decades, humans have made great tremendous achievements in providing legal rights and protection to animals such as the “Universal Declaration on Animal Welfare”. The roots of recent animals protection and welfare paradigms can be traced back to Islamic injunctions provided 1400 years ago. Though man has subjugated animals still he is not authorized to do anything to animals. Environmental equilibrium will be damaged if animals are extinct as they are a part of the genesis pyramid. Islamic sacred scripture provides privileges and protection to animals. According to Islam, animals’ manipulation by man must be lawful as he will be accountable for that. In the contemporary world, there exist diverse legislation, practices, and concerns regarding animals’ protection and rights. Highlighting some of these legislations, practices, and concerns, this article will provide an overview of Islamic teachings regarding animal protection and welfare that is much needed for biosafety today.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.981 | 0.984 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".