Species comparison of the physical properties of loblolly and slash pine wood and bark
Bibliographic record
Abstract
Composition of the southern pine forest is now predominated by two species, loblolly pine (Pinus taeda L.) and slash pine (Pinus elliottii Engelm.), owing to fire suppression activities, natural regeneration on abandoned agricultural lands, and extensive planting. Comparison of the wood and bark physical properties of these pines is of interest in terms of the yields of usable biomass and, for the bark, its ecological functionality on a living tree. Trees from a species comparison study were used to generate wood and bark property data, on a whole-tree basis, and for stem disks collected at breast height. Models were constructed to explain the effect of relative height on wood and bark properties. When comparing the whole-tree data, slash pine wood (0.523 versus 0.498) and bark (0.368 versus 0.311) specific gravity values were higher, both offset by lower moisture contents; slash pine also produced a higher percentage of bark on a dry-mass basis (17% versus 12.5%). Unlike wood properties, bark properties showed significant between-species differences when determined at breast height alone, the exception being moisture content. In terms of yield, harvests of a green tonne of loblolly pine and slash pine would give approximately the same dry mass of wood, but slash pine provides more bark.
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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) | 0.000 | 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".