Biomass and carbon in <i>Schizolobium parahyba</i> var. <i>amazonicum</i> stands under different spacing
Bibliographic record
Abstract
Native species planted in areas previously occupied by degraded pasture can play an important role in biomass supply and atmospheric carbon sequestration. Evaluating the performance of native species in different planting spacings becomes important for forestry and the management of new species with economic potential. Schizolobium parahyba var. amazonicum is a non-traditional species in the southeastern region of Brazil and it was established in pasture areas to evaluate growth, biomass, and carbon stock. Five planting spacings (3 m x 2 m, 3 m x 3 m, 4 m x 3 m, 4 m x 4 m, and 5 m x 5 m, in monoculture) were tested in 9 experimental plots. The biomass of the shoot and root, as well as the carbon content, were obtained by the direct method. The biomass varied 31.4 and 52.9 kg tree-1 in the spacing 3 m x 2 m and 5 m x 5 m, respectively. The greater carbon stock was observed in the lower spacing (19.43 Mg ha-1), 50% higher than in the larger spacing. The spacing did not influence the biomass and carbon stock in the roots per unit area. The performance of the species should be monitored at advanced ages given the different responses to planting spacing and competition between plants.
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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 | 0.001 | 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".