Modeling of present and future potential distribution areas of Thymus praecox opiz. in Turkey according to the Maxent algorithm
Bibliographic record
Abstract
Thymus L. genus of the Lamiaceae family, which has a cosmopolitan distribution that includes annual or perennial herbs, rarely shrubs or trees, known for their pleasant smell, has medicinal and aromatic species. Although the ethnobotanical use of individuals of the genus Thymus is quite common, its consumption is often preferred as spice and medicinal tea. In this study, Thymus praecox Opiz. forms the material of the study. In this article, potential present and future distribution areas were modeled in MaxEnt 4.1 to determine the effects of climate change on the distribution areas of T. praecox in Türkiye. In the model, 2041-2060 (~2050) and 2081-2100 (~2090) periods of SSP2 4.5 and SSP5 8.5 scenarios in CanESM5.0.3 (The Canadian Earth System Model version 5) climate change model were used, together with sample points and bioclimatic variables. According to the study outputs, it is estimated that the estimated potential suitable and very suitable distribution areas of T. praecox today are 108411.705 km2 and according to the CanESM5.0.3 model, it will experience losses in very suitable and suitable distribution areas in the future, and very suitable distribution areas cannot be found in the SSP5 8.5 scenario 2081-2100 periods.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".