Glauconitic Siltstone as a Source of Potassium, Silicon and Manganese for Flooded Rice
Bibliographic record
Abstract
The objective of this study was to evaluate the efficiency of glauconitic siltstone as a multi-nutrient source for flooded rice. Two experiments were carried out under greenhouse conditions, one using a Ferralsol and the another an Arenosol. Glauconitic siltstone was applied in different doses (0, 5, 20, 40, and 80 mg dm-3 K2O) and potassium chloride, wollastonite, and manganese sulfate were respectively used as standard sources, at doses of 80 mg dm-3 K2O, 270 mg dm-3 Si, and 2 mg dm-3 Mn. The sources were incubated for 90 days on the two soil types and, after the incubation period, rice plants were sown, and two consecutive rice growths were performed. The application of glauconitic siltstone in tropical soils promotes increases in the plant and grain dry matter of rice plants, as well as K, Si and Mn contents in soil samples and accumulated in plants. Greater effects following the application of glauconitic siltstone are obtained after the second rice growth due to its gradual release.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".