TEK SAĞLIK YAKLAŞIMININ KÖKENİ: DÜNYADAKİ VE TÜRKİYE'DEKİ MEVCUT DURUMU
Bibliographic record
Abstract
The One Health approach has a history of hundreds of years of thought and social development. In essence, it is a holistic understanding of health that deals with the problems that arise at the intersection of humans, animals and the environment. The emergence of One Health coincides with the start of scientific training in the first Veterinary School opened in Lyon, France in 1762 by Claude Bourgelat (1712-1779). When the veterinary school is opened, there is a prevailing opinion that veterinary medicine only deals with animals. Later, it is realized that besides animals, it also contributes to human medicine. In this, the role of the head of comparative medicine in Lyon, physician, anatomist, historian and social reformer, Prof.Dr. Félix Vicq D'Azyr (1748 – 1794) is great. Similarly, world-renowned German medical scientist Prof.Dr. Rudolf L.K Virchow (1821 - 1902), with his research on Trichinella spiralis in pork in 1855, realized that veterinary medicine and human medicine complement each other, which was an important development in terms of the medical science world. Virshow provided the birth of One Medicine with his historical explanation of the relationship between both professions as "There is not and should not be a dividing line between animal and human medicine. The purpose is different, but the experience gained forms the basis of all medicine". Afterthat Dr. William Osler (1849-1919), who became a Canadian student "One Medicine" and explained that "veterinary medicine and human medicine complement eachother and this concept should be perceived as a single medical concept" He supported Virchow with his statement. On its 70th anniversary, WHO called on world leaders to improve the health of all people and support the Sustainable Development Goals. The One Health approach has evolved into“ One Welfare “, the advanced stage of “One Health”, with the call of WHO in 2018.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".