Właściwości i zastosowanie lecznicze żywicy jodły syryjskiej w historii medycyny i farmacji
Bibliographic record
Abstract
The Syrian fir [Abies cilicica (Antoine & Kotschy) Carrière] is a slender tree found in the mountainous areas of Lebanon, Syria and Turkey. Its name recalls an ancient land called Cilicia, located in modern-day Turkey; the capital city of this land was Tarsus, where an important trade route called the Gates of Cilicia ran. The rich medicinal properties of the resin naturally flowing from this tree were appreciated by the ancient Egyptians as early as in the Old Kingdom period. It was used as an antiseptic, anti–inflammatory and diuretic agent, but also in cosmetics: an important ingredient of preparations strengthening weakened hair, skin firming and wrinkle reducing. Respiratory ailments, mainly persistent coughs, were widely treated with preparations containing the Syrian fir resin, which was also noted by the Roman historian Pliny the Elder in his famous Naturalis Historia. The purpose of this paper is to discuss the medicinal properties of the Syrian fir, primarily of its resin, and the time period in which it was used for therapeutic purposes. A thorough analysis of the botanical, medical and pharmaceutical literature brings to a conclusion that Syrian fir was often used in the abovementioned applications in ancient times. Since the Middle Ages and continuing into the 19th century, native, neighboring, more popular varieties of fir trees, like the balsam fir, or the Canadian fir, were more often used for medicinal purposes. Many other common species of coniferous trees were used as well, especially the Pinus sylvestris, thanks to which the pine tar (Pix liquida Pini) can still be used 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".