Vertical distribution character of soil inorganic phosphorus in mountain meadow system of WuGong Mountain
Bibliographic record
Abstract
The spatial distribution of soil inorganic phosphorus and the correlation between soil inorganic phosphorus and soil available phosphorus along the different altitudes(the altitude range from 1 600~1 900m)and different soil depths were analyzed in mountain meadow system of Wugong Mountain.The soil inorganic phosphorus(P)content ranged in 175.48~524.06mg·kg-1,significantly increased(P0.05)with the increase of altitude and decreased gradually with the increase of soil depth.There was a vertical distribution law and surface gathering character.The range of variation in water-soluble P,Al-P,Fe-P,O-P,Ca-P was 0.423~4.781,16.27~90.72,54.13~344.34,19.66~90.32,15.12~76.21mg·kg-1,respectively.There were also vertical distribution and surface gathering character in each proportions of inorganic phosphorus.The percentage of Fe-P was the highest which followed by Al-P,O-P,Ca-P and water soluble P.There was a significantly positive correlations between soil available P and Al-P which suggest that Al-P was the potential resource for available P in this area.This research revealed the spatial distribution of soil inorganic P and the correlation between available P and soil inorganic P,determinate the resource of soil P which provided a guidance for vegetation restoration in mountain meadow ecosystem.
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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".