Analytical Study of Cold Waves in the Lattakia Region During the Period 1960-2020 and Assessment of Their Damages Using Geographic Information Systems and Remote Sensing
Bibliographic record
Abstract
This research aims to study negative thermal anomalies (cold waves) associated with extreme climatic conditions in Syria during the period (1960-2020). It includes the study and analysis of minimum temperatures in the Lattakia region and determines the extent of deviation of the daily minimum temperature average from the overall daily average at the Lattakia, Qastal Ma'afu, and Slunfah stations during the study period. The research also conducted a statistical analysis of cold waves and their general trend in the study area using the XLSTAT program. Furthermore, the level of damage caused by cold waves that led to frost occurrences in the Zghrin and Bloran plains was assessed using the Normalized Difference Vegetation Index (NDVI), relying on 12 cloud-free Landsat 8 satellite images (with a spatial resolution of 30m) taken before and after frost events in the following years: 2015, 2016, 2017, 2021, and 2022, within the ArcMap 10.8 program. The results showed several levels of damage, with significant and meaningful correlations recorded at a 95% confidence level between the decrease in the vegetation density index and frost events in the studied cases.
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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".