Potential of East African phosphate rock deposits in integrated nutrient management strategies
Bibliographic record
Abstract
Phosphorus deficiency affects around 80% of the acid soils of western Kenya, but fertilizer use is limited due to high prices. This paper explores the potential of local phosphate rocks (PR) as a remedy within the context on an integrated soil fertility management approach. A promising phosphate rock is Minjingu PR (MPR, Tanzania), a sedimentary/biogenic deposit which contains about 13% total P and 3% neutral ammonium citrate (NAC) soluble P. On-farm trials in P-deficient soils in western Kenya demonstrate MPR to be as effective as triple superphosphate (TSP, 20% P) at equal P rates. The benefits are most pronounced with the integration of agroforestry technologies that improve soil fertility. Besides Minjingu PR, Busumbu PR from Uganda (BPR) is potentially another source of P. It is typical of the abundant but unreactive igneous PRs in eastern, central and southern Africa. Agronomic performance of BPR is poorer, though its lower cost and location near to P-deficient areas in western Kenya make it attractive in some situations. The policy implications of these findings are discussed further in the paper.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".