Assessing stand species and structural diversity at neighbourhood scale
Why this work is in the frame
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Bibliographic record
Abstract
Forest diversity assessments are typically conducted at stand scale. This traditional diversity assessment may provide substantial insight into overall stand structure but is limited with respect to describing within-stand variation, an important aspect of stand diversity. This article describes a method for assessing species and structural diversity at within-stand, neighbourhood scale. •Nearest neighbours are determined from mapped tree locations in field survey plots.•R codes (provided in appendices) are used to assist with determining species and structural diversity indices at a neighbourhood of 4 trees (a subject tree and the 3 nearest neighbours).•Neighbourhood structural diversity indices are compared against structural complexity index (SCI) in capturing within-stand variation.•Neighbourhood diversity indices, especially in managed stands, are useful for capturing spatial variation in species and structural diversity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it