Detecting Vegetation Change in Neka River Basin of IRAN Based on
Bibliographic record
Abstract
Land use change has transformed a vast part of the natural landscapes of the developing world for the last 50 years. Land is a fundamental factor of production and through much of the course of human history; it has been tightly coupled with economic growth. Bare soil has recently increased and it is one of the most important land degradation processes in the Mediterranean basins. The land use has changed rapidly within and near Neka River which is a fast growing agricultural river Basin. The land use changes in this region were analyzed based on Landsat data from 1977 to 2001. Supervised/unsupervised classi?cation approach coupled with GIS analyses was employed to generate the change over land use/cover maps. In order to analyze landscape fragmentation, land-use change has been calculated using NDVI. Based on the results of the analysis, the range of NDVI has changed from 0.9597/-0.2876 in 1977 to 0.6420/-0.187 in 2001 which shows that bare land has increased, while woodland areas decreased.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".