Determining the effectiveness of using acoustic velocity as an indirect measurement of branchiness in standing longleaf pine
Bibliographic record
Abstract
Branches reduce stem quality, and the level of the effect is determined by the geometry, size, and number, of associated knots. Quantifying branchiness is difficult, as visual estimates are subjective, and mechanical measurements are impractical. Acoustic velocity (AV) is a relatively novel measurement capturing the speed stress travels through wood. AV is correlated with wood stiffness and is affected by internal characteristics like knots. This project tested AV as an indirect branchiness metric by measuring AV, height, diameter, and counting branches classified by diameter on 255 standing 8 year old longleaf pine ( Pinus palustris). AV was highly correlated with height (r = 0.76, p < 0.0001) and slenderness (r = 0.52, p < 0.0001). AV was moderately correlated with large living branches (diameter > 2.54 cm) (r = −0.27, p < 0.0001), but not correlated with total branches. Height, slenderness, and the count of large living branches (diameter > 2.54 cm) were included in the selected model for AV. Inclusion of dead or small (diameter < 2.54 cm) branches reduced model power. The best model captured 11% of the variation in AV, of which branches explained 5%. We conclude that AV does not appropriately quantify individual tree branchiness, but may be suitable for comparing populations such as families or provenances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".