Nutrient Assessment with Omission Pot Trials for Management of Rubber Growing Soil
Bibliographic record
Abstract
Rubber-growing soils in southern Thailand are usually deficient in both macro- and micronutrients. Omission pot trial is an excellent tool for nutrient assessment because it can indicate the most limiting nutrient and the order of limitation. Maize is generally used as a test plant, but the difference in nutrient response of maize and rubber is not clearly understood. An omission pot trial with 10 treatments (All, -N, -P, -K, -Mg, -S, -Zn, -Cu, -B, and -Lime) was conducted. The soil samples were limed with Ca(OH)2 to pH 6, except for that used for the -Lime treatment. Equivalent amounts of 400 kg ha-1 of N, 120 of P, 175 of K, 75 of Mg, 100 of S, 6 of Zn, 4 of Cu and 2 kg ha-1 of B, were added in the All treatment. Nutrient X was omitted in the -X treatment. Maize and rubber were grown as test plants. The plant growth indices were measured after 30 days for maize and after 9 months for rubber. The limiting nutrients of both plants were N, P, and Ca (lime). Rubber growth in the field, which received government-recommended and omission-based fertilization, were not different.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".