Genotype and environment interaction on the wood quality of <i>Eucalyptus</i> spp. for energy purposes
Bibliographic record
Abstract
The objective of this study was to evaluate the wood chemical and energetic characteristics of Eucalyptus spp. clones planted in three sites in the Midwest of Brazil. Thus, five clones from Eucalyptus spp. were planted in different sites aiming to determine the qualitative characteristics of the wood resulting from the variation in the tree growth environment and the genetic material. The same clones were planted in the three sites to determine the genotype × environment interaction. The trees were then sampled at 5 years after planting for their physical–chemical and energetic characterization. The results showed that the wood characteristics vary in different proportions according to the clone, just as the growth environment of the trees alters the behavior of the clones for the same characteristics. The edaphic variables affected the wood characteristics, inferring that the water content in the soil has more effect on the wood properties than the water content in the air, mainly on wood basic density. The results of this study indicate that using the appropriate genotype related to the environment conditions determines the wood characteristics, since the wood properties are strongly influenced by the edaphoclimatic variables.
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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 | 0.000 |
| 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".