Initial Growth of Amburana cearensis in Decomposed Buriti Stem Substrate and Nitrogen Doses
Bibliographic record
Abstract
One of the difficulties of producing native species seedlings is slow growth. The objective of this study was to evaluate the initial development of Amburana cearensis (Allem.) A. C. Smith in relation to the concentration decomposed buriti stem substratum and nitrogen doses. A completely randomized design was used in a factorial arrangement of 3 × 5 (proportions of decomposed buriti stem × nitrogen doses), with six replicates. The treatments were formulated substrates comprised of decomposed buriti stem manually mixed with soil (Dystrophic Yellow Latosol) in three proportions (0, 25 and 50%) and five nitrogen doses (0, 100, 200, 300 and 400 mg dm-3) applied in treatments. There was no significant interaction between the DRM and ND factors. However, there was an isolated effect for the following variables: Plant height (PH), stem diameter (SD), leaf number (LN), leaf area (LA), dry mass of the aerial part (DMA) and root length (RL). The best concentrations of the substrate for the variables PH, LA and DMA were 25% and 50%, whereas for SD, LN and RL, the best result was 50%. ND and other variables had good responses under recommended doses ranging from a minimum of 264.82 mg dm-3, observed in DMA, and a maximum of 400 mg dm-3, observed in RL. Both factors positively the quality of umburana seedlings.
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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 | 0.000 | 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 | 0.001 |
| 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".