Anion Exchange and Mehlich‐III Phosphorus in Humaquepts Varying in Clay Content
Bibliographic record
Abstract
Soil‐test P is not only used for fertilizer recommendations but also as a component to predict risk of P transfer from soils to surface waters. The changes in soil‐test P following P application are often related to soil texture. This study assessed the changes in anion‐exchange membrane P (AEM‐P) and Mehlich‐III extractable P (M3P) in Humaquepts varying in clay content. Five soils from loamy sand to “heavy” clay received 0 (P0), 10 (P10), 20 (P20), or 40 (P40) mg P kg −1 per each simulated growth season were successively cropped with barley ( Hordeum vulgare L.) and soybean ( Glycine max L. Merr.) in a growth chamber experiment. There were clay content mineral fertilizer P (MFP) interactive effects on soil AEM‐P, M3P contents and plant P uptake. The AEM‐P paralleled clay content and MFP rate. The average increase in M3P at P10 and P20 over P0 was smaller on clayey than on coarse‐textured soils. The converse trend was true at P40 over P10 and P20. The increase in M3P per unit MFP addition in excess of plant uptake decreased linearly with the increase in clay at P10 and P20 but not at P40. There was a quadratic plateau relationship between AEM‐P and M3P contents with a turning point at 4.2 μg AEM‐P cm −2 or 93.0 mg M3P kg −1 Plant P uptake was more closely related to AEM‐P than M3P in all soils, suggesting AEM‐P is a more reliable indicator of labile P than M3P in Humaquepts for the tested crops, particularly in fine‐textured soils. Clay content has a large influence on changes in AEM‐P and M3P following MFP additions to Humaquepts.
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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 | 0.000 | 0.000 |
| 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".