Modeling corewood–outerwood transition in loblolly pine using wood specific gravity
Bibliographic record
Abstract
A modified logistic function was used for modeling specific-gravity profiles obtained from X-ray densitometry analysis in 675 loblolly pine ( Pinus taeda L.) trees in four regeneration trials. Trees were 21 or 22 years old at the time of the study. The function was used for demarcating corewood, transitional, and outerwood zones. Site and silvicultural effects were incorporated into the model. Heteroscedasticity and within-group correlation were accounted for by specifying the variance and serial-correlation structure, respectively. The estimated transition zone was located between rings 5 and 15, and the outerwood demarcation point varied from rings 12 to 15. No effects of treatments on the demarcation points were observed; however, site preparation and fertilization affected the lower asymptotes of the curves in all sites. A geographical trend for the demarcation point was observed, with the northern site requiring more time to reach a plateau in specific gravity compared with the southern sites. The diameter of the juvenile core was increased as a result of the treatments. However, the amount of corewood was not statistically affected, ranging from 55% in the north to 75% in the south, except at one site where fertilization decreased the percentage of corewood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".