Residue of Phosphorus Sources Broadcast and Applied on Rows in Forages during Off-Season Crops
Bibliographic record
Abstract
This study aimed to evaluate the residual effect of phosphorus sources and application techniques in the intercropping of forages during off-season crops. The experimental design was randomized blocks in a 4 × 2 + 1 factorial, being four sources of phosphorus [Bayóvar Reactive Phosphate (BRP), Monoammonium Phosphate (MAP), Simple Superphosphate (SS) and Triple Superphosphate (TS)], two application techniques (broadcasting and on rows) and an additional without phosphorus. The experiment was conducted during the off-season crop. The residual effect of phosphorus fertilization increased the growth and the production of biomass of forage sorghum regarding broadcast SS and TS sources. The lowest P contents in the tissue of plants fertilized with SS and TS may be attributed to the diluting effect, as it achieved the highest production of biomass. The application of TS favored a greater dry matter production in Brachiaria brizantha cv. Piatã. At the depth 0.00-0.05 m, there was a higher P content with the application of BRP. However, the production of biomass was low, a factor that may be related to an overestimation of P bound to Ca by the Mehlich-1 extractor. Under cultivation conditions, broadcast SS and TS had a higher residual effect.
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 | 0.001 |
| 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".