Age estimation of <i>Quercus marilandica</i> and <i>Quercus stellata</i>: applications for interpreting stand dynamics
Bibliographic record
Abstract
We compared methods to correct age of cores that failed to intercept the tree's pith for two oak species, blackjack oak (Quercus marilandica Muenchh.) and post oak (Quercus stellata Wangenh.), and determined the difference in age at tree base (010 cm from ground level) versus breast height (1.4 m from ground level). Methods to correct age of off-center cores were relatively similar in error for both species (2.98.1 years). Ocular estimation of number of rings to pith required the least amount of data collection and manipulation to apply. A regression technique using tree diameter provided the lowest absolute error (913 years) for age estimation of rotten cores, compared with methods that used mean ring widths to extrapolate tree age. Age difference due to coring height averaged 9 years for both species and was highly variable, indicating that trees should be cored as close to ground level as possible. Age structure of this forest could be accurately reconstructed to within 5-year age-classes using recommended methods, with the exclusion of large, rotten, and putatively old trees.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".