Genetic variation in wood shrinkage and its correlations with tree growth and wood density of <i>Calycophyllum spruceanum</i> at an early age in the Peruvian Amazon
Bibliographic record
Abstract
Calycophyllum spruceanum (Benth.) Hook. f. ex Shum. is an important timber tree species in the Peruvian Amazon Basin. Farmers and industry use wood from young trees of this species, so tree breeders should investigate genetic variation in juvenile wood properties to verify whether they can be improved. A previous study using the same provenance/progeny test showed that there was significant genetic variation in tree growth and wood density, that heritability was higher for density than for growth, and that density and growth were positively correlated at 39 months. This paper presents results for wood shrinkage at 39 months and their correlations with tree growth and wood density. Data were collected on thinned trees. Shrinkage values were relatively low when considering wood density of this species. There was significant genetic variation in wood shrinkage due to families within provenances and, in some cases, due to provenances. Heritability estimates were moderately high for linear and volumetric shrinkage (0.37–0.50) and lower for the tangential/radial shrinkage ratio (0.21–0.29) across zones. The genetic correlations that were considered significant ranged from 0.30 to 0.80. In general, genetic correlations suggest that selection of faster-growing trees with higher wood density would result in wood with greater shrinkage and a larger tangential/radial shrinkage ratio.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".