Reconstructing structural development of even-aged larch stands in Siberia
Bibliographic record
Abstract
A method was proposed for quantitatively reconstructing structural development over time of even-aged monospecific forests and was applied to a larch (Larix gmelinii (Rupr.) Rupr.) stand in Siberia. It relies on samples obtained at one-time observation and some simple assumptions considered general in even-aged stands. Tree-ring data taken from breast height of a group of the largest trees and those measured at various stem heights of several individuals representing the range of tree sizes in the plot are used for the estimation. Stand density and parameters of stem volume distribution at a given time in the past were calculated with the "stem slenderness index," and with an assumption of the -3/2 power distribution for the distribution function of stem size, respectively. By developing time-dependent allometric relationships for individual tree attributes, the whole-stand values of stem volume and its increment were reconstructed for several decades of stand development. Estimated history of the changes in stand density, total stem volume, and stem volume growth for the dense larch stand examined, mostly agreed with a separate estimation by the self-thinning assumption.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 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".