Relationships between Soil Properties and Rice Growth with Steel Slug Application in Indonesia
Bibliographic record
Abstract
<p>In the presence study representative rice producing sites in Lampung, Central Java and West Java Province was presented, the relationships between soil properties, rice growth and yield, and further evaluated the effect of Si application on rice growth and yield in different soil types were carried out using local steel slug, which was the most common material as the Si amendment. The soil samples were acidic to neutral with textural classes were clayey, loam and sandy clay loam. Mean nitrogen and available P content was below the value in tropical Asia. Silica availability has been decreasing in rice fields in Indonesia and Si deficiency in rice is now recognized as a possible limiting factor rice production. Steel slug, which has a high Si content and locally available, was selected as a potential source of Si in the present study. A greenhouse experiment was carried out to evaluate the effect of steel slug on rice growth in different soil types. Steel slug was applied at the rates of 0, 20, 50, 100, 200 and 300 kg Si/ha. Steel slug application increased plant height at 300 kg Si/ha. Grain yield of soils that contained low available Si was increased with steel slug application. In contrast, some soils with high available Si content did not respond to Si application and other soil properties affected rice growth.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".