Malpighia emaginata D.C. Growth in Several Substrates and Salt Waters
Bibliographic record
Abstract
The acerola tree is one of the most promising fruit trees of the Brazilian fruit sector, demanding the development of studies that indicate the proper conditions to improve its production under adverse conditions. Consequently, our purpose was to evaluate the growth of Malpighia emaginata D.C in several substrates and under ascending levels of irrigation water salinity. The experiment was conducted in a 4 × 5 factorial scheme randomized block design, which comprised four substrates (S1 = soil; S2 = soil with a 10% addition of cattle manure; S3 = soil with a 10% addition of organic compounds; and S4 - soil with a 5% addition of cattle manure and a 5% addition of organic compounds) and five CEa salt levels (0.3, 1.0, 1.7, 2.7, and 3.5 dS m-1). The plant height and stem diameter variables were not affected by the studied factors. The interaction between salinity and the substrates affected the root growth and the build-up of the plants’ fresh and dry biomass, resulting in the increase of the values obtained by the substrates containing manure and organic compounds. The seedlings’ quality, represented by the height/stem diameter and aerial part/root dry mass ratios, and by the Dickson quality index, indicated that the plants produced in the substrates 2 and 3 were more vigorous.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".