Spatial patterns of trees from different development stages in mixed temperate forest in the Hyrcanian region of Iran
Bibliographic record
Abstract
Mixed beech (Fagus orientalis Lipsky) forests are very important to the Hyrcanian region of Iran because of their high degree of naturalness and as a source of wood production. Determination of tree spatial patterns over development stages is a first step in understanding underlying processes driving regeneration and forest dynamics. Spatial patterns of trees from three development stages (initial, optimal and decay) of an untouched mixed beech forest were quantified within three 1-ha plots. To prepare the stem maps, we measured each tree with a DBH larger than 7.5 cm using the azimuth-distance method. Spatial patterns were then analysed using Ripley's K-function. Results indicated that the number of trees decreased from the initial stage to the decay stage, with tree spatial patterns being aggregated, slightly aggregated and highly randomized for initial, optimal and decay stages, respectively. Differences in spatial patterns among the development stages are not unexpected considering that such unmanaged forests are driven by gap dynamics which results in interactions between gap filling individuals.
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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 | 0.001 |
| 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".