An extended model of heartwood secondary metabolism informed by functional genomics
Bibliographic record
Abstract
The development of heartwood (HW) and the associated accumulation of secondary metabolites, which are also known as 'specialized metabolites' or 'extractives', is an important feature of tree biology. Heartwood development can affect tree health with broader implications for forest health. Heartwood development also defines a variety of wood quality traits that are important in the forest industry such as durability and colour of wood products. In the bioproducts industry, HW provides a source of high-value small molecules such as fragrances and antimicrobials. The HW properties of decay resistance in living trees, durability and colour of wood products, and small molecule bioproducts are largely defined by secondary metabolites, the biosynthesis of which appears to be activated during the onset of HW formation. Traditionally, it is thought that HW formation involves a spike in the activity of secondary metabolism in parenchyma cells in a transition zone between sapwood and HW, followed by programmed cell-death. The resulting HW tissue is thought to consist entirely of dead cells. Here, we discuss a variation of existing models of HW formation, based on the recent discovery of HW-specific transcriptome signatures of terpenoid biosynthesis in sandalwood (Santalum album L.) that invokes the activity of living cells in HW.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".