Wood density variability in successive breeding populations of maritime pine
Bibliographic record
Abstract
Growth and form are the two main traits used for genetic improvement of maritime pine ( Pinus pinaster Ait.) in the southwest of France. In this paper, wood density is studied to answer two main questions: Is there a general trend for density variability throughout tree development and has selection indirectly reduced wood density variability over breeding populations, owing to genetic unfavourable correlation with growth? Wood density and its components were studied in three polycross tests, each representative of one of the successive breeding populations. Wood density was measured with an X-ray densitometer in approximately 50 families per test with >1900 trees. A preliminary study showed that bark-to-pith ring indexing allows for a better estimation of genetic effects than does pith-to-bark indexing. Genetic variability of wood density appears to be highly dependent on the year considered and no general pattern can be detected over time. Whereas the variability of selected traits is known to have decreased over breeding populations, no significant change was found for variability of wood density.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".