Bibliographic record
Abstract
In the Qur'an al-Hakim, the study of the phenomena of nature and the human welfare derived from them is mentioned with a considerable frequency. Human life on this planet depends on both non-living elements and living bodies. However, this article is intended to mention only animals, especially pets. From time immemorial man has been able to derive various benefits from animals. For example, it has been getting benefits from milk, meat, manure, manure and fuel, clothing from skins and houses (tents) etc. God, the Lord of Glory, created man and jinn for His worship. And besides, He has commissioned all creatures to serve man. From the Qur'anic teachings and the teachings of the Prophet (peace and blessings of ALLAH be upon him) we find that the rights of human beings and even animals have been defined in Islam. In the supernatural religions we still see these things clearly, while in the non-divine religions which are adorned with human invention, even though the loudest claimants of animal rights know that for the first time in Europe the animal rights legislature built in 1635.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.963 | 0.956 |
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".