Revivification of a method for identifying longleaf pine timber and its application to southern pine relicts in southeastern Virginia
Bibliographic record
Abstract
Longleaf pine ( Pinus palustris Mill.) cannot be distinguished from the other southern pines based on wood anatomy alone. A method that involves measuring pith and second annual ring diameters, reported by Arthur Koehler in 1932 (The Southern Lumberman, 145: 36–37), was revisited as an option for identifying longleaf pine timbers and stumps. Cross-section disks of longleaf, loblolly ( Pinus taeda L.), and shortleaf ( Pinus echinata Mill.) pines were measured and the diameters of their piths and second annual rings plotted against each other. From this plot, longleaf pine could be differentiated from the other two southern pine species, demonstrating that a method established with trees harvested more than 70 years ago is still applicable to standing timber of today. No evidence was found to suggest that different growth rates impact method applicability. In those situations where the second annual ring is intact, but not the pith, very large second annual ring diameters (>40 mm) may identify timbers with a lower probability of being longleaf pine. In addition to the identification of very old lightwood stumps as part of a longleaf pine restoration effort, both methods may be applied to timber identification in historic structures and the niche forest products industry involving the recovery and processing of highly prized longleaf pine logs from river bottoms. Measurements from relicts sampled in this study were consistent with the purported range for longleaf pine in Virginia.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".