Annual and seasonal variation characteristics of NDVI and its relationship with meteorological factors in Jialing River Basin
Bibliographic record
Abstract
The variation of the normalized difference vegetation index(NDVI) and its relationship with precipitation,air temperature,and sunshine duration in the Jialing River Basin during the period from 1982 to 2006 were studied using statistical methods.The results show that the annual average NDVI had an increasing trend during the study period,especially in the spring,and it was highly correlated with temperature.In all seasons,there was a lag in the change of the seasonal average NDVI when the air temperature and precipitation changed in the basin,especially in the vegetation growth seasons: spring,summer,and autumn.In the spring,the relationships between the average NDVI and the sunshine duration in the present quarter and the air temperature in the previous quarter were more significant.During the summer,the average NDVI was significantly influenced by meteorological factors of both the present quarter and the previous quarter.During the autumn,the average NDVI was significantly correlated with sunshine duration and was greatly influenced by the air temperature in the previous quarter.
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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".