Size of Containers in the Production of Flamboyant Seedlings
Bibliographic record
Abstract
The size of the container can affect the quality of the seedlings and, there is no recommendation of containers for the formation of flamboyant seedlings [Delonix regia (Bojerex Hook.) Raf]. Thus, the objective of this study was to evaluate the production of flamboyant seedlings in different container sizes, besides performing trail analysis to identify the growth variables that characterize the quality of these seedlings. The experimental design was a randomized block design with seven container sizes (13 × 13 cm, 15 × 15 cm, 13 × 20 cm, 15 × 25 cm, 17 × 22 cm, 17 × 30 cm or 30 × 40 cm), with four replicates. Each experimental unit was composed of five containers, totaling 20 containers per treatment. The plant height, stem base diameter, number of leaves and the sturdiness quotient were measured at 20, 40, 60, 80 and 100 days after emergence (DAE), and at 100 DAE were also measured the root volume, root dry matter, shoot dry matter, total dry matter, shoot/root dry matter ratio and Dickson quality index (DQI). The flamboyant seedlings have better grow when cultivated in polyethylene bags with size of 30 × 40 cm. The collar diameter, root volume, root dry matter, shoot dry matter and total dry matter are the most adequate variables to indicate the quality of flamboyant seedlings. However, because it is a rapid, simple and non-destructive measurement variable, the root collar diameter is more adequate to identify high-quality flamboyant 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".