Genetics of physical wood properties and early growth in a tropical pine hybrid
Bibliographic record
Abstract
Quantitative trait locus (QTL) detection was carried out for physical wood properties and early growth traits in an interspecific hybrid between Pinus elliottii var. elliottii Engelm. and Pinus caribaea var. hondurensis (Sénécl) Barr. et Golf. A pseudo-testcross QTL detection strategy was used to identify genome regions that influenced wood density, secondary growth, and dry wood mass index on each genetic map for the parents of a single F1family (n = 133). Traits were measured for annual ring and earlywood and latewood components and were based on both individual and average ring values from 1996 to 1999. A total of 12 significant putative QTLs were identified that clustered into four genomic regions in the P. elliottii var. elliottii parent and a single region in the P. caribaea var. hondurensis parent. The P. elliottii var. elliottii parent largely contributed putative QTLs for diameter growth and wood density, whereas the P. caribaea var. hondurensis parent contributed a putative QTL for earlywood formed in 1997. Putative QTLs that influenced density and ring width did not colocate, suggesting independent inheritance of these characters. This was consistent with the lack of genetic correlation between wood density and diameter growth observed in quantitative studies in hybrid pines.
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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 | 0.001 | 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) | 0.001 | 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".