The spatial heterogeneity of soil water in the Populus euphratica forest in Guazhou Oasis
Bibliographic record
Abstract
The spatial variations of soil water content in the populus euphratica forest in Guazhou Oasis were analyzed by using methods of Statistics and Kriging interpolation.The mainly results showed:In vertical direction,the soil water contents of QZ、SG and BL increase with the depth of sample,and the soil water content of TG increases with the depth of sample in 0-80cm,but it reduces with the depth of sample in 100-120cm.The soil water content of the Populus euphratica reduces as the age of the Populus euphratica.The extent of soil water content in QZ is less than others,it is showed that human activities impact more on soil water content and the influence of irrigation is primary in Guazhou Oasis.In space,the soil water content of the Populus euphratica in Guazhou Oasis increases from southeast to northwest.
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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".