Regional Substrates of the Brazilian Northeast on Acclimatization and Development Morphological of Minirose
Bibliographic record
Abstract
The transition from heterotrophism to autotrophism in acclimatization is a delicate process for most species. The objective of this work was to evaluate combinations of regional substrates of the Brazilian Northeast in the acclimatization and morphological development of minirose (Rosa chinensis ‘Minima’) seedlings. The experiment was carried out in a greenhouse using seedlings with 30 days of in vitro culture. The treatments were constituted by: 1) dry coconut powder; 2) 75% dry coconut powder + 25% rice husk; 3) 50% dry coconut powder + 50% rice husk; 4) 75% dry coconut powder + 25% charcoal rice husk; 5) 50% dry coconut powder + 50% carbonized rice husk; 6) 100% vermiculite; 7) 50% vermiculite + 50% dry coconut powder; 8) commercial substrate; 9) 75% sand + 25% dry coconut powder and 10) 50% sand + 50% dry coconut powder. After 21 days, the following characteristics were evaluated: survival percentage, leaf number, shoot height, dry matter of shoot and root and total dry matter. The regional materials tested showed a good choice of substrates to be used in the acclimatization of minirose seedlings. The vermiculite presented the worst results in the characteristics evaluated. Dry coconut powder as substrate should be used in mixtures with other materials to provide better acclimatization conditions. The use of 50% dry coconut powder + 50% rice husk provided a best development and growth of minirose seedlings (Rosa chinensis ‘Minima’) than other tested substrates
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".