The Relationship Between Tree Sapling Density and Competing Adult Density Between North American Deciduous Trees
Bibliographic record
Abstract
York University’s Danby Woodlot is a small deciduous forest on the outskirts of Toronto. The woodlot is home to many common North American trees such as maple, elm, and oak. This study was designed to find out if there is a correlation between the density of saplings surrounding its parent tree, and the density of competing adult trees that surround it. The two main factors of this experiment include the density of daughter saplings in a six-metre radius surrounding its parent, and the density of competing adults in the same six-metre radius. A third factor was measured, and that is the amount of light penetrating the forest canopy. It is expected that as the density of competing adult trees increases, the density of saplings surrounding its parent should decrease. This competition could arise from many factors, including, but not limited to, the availability of light and soil nutrients. The data was obtained by measuring 6m from a target tree in three directions, using three transects, and doing a physical count of specimens inside the circumference generated by the transects. All of the daughter saplings in the area were counted, as were all competing adults (of any species). Saplings were defined as any tree less than six feet tall. Daughter saplings were defined as any sapling of the same species as the parent (target) tree, regardless of proximity to other trees of the same species. Light availability under the canopy was estimated using thumb-and-forefinger rectangles aimed skyward at four points under the target tree. The four estimates were then averaged to generate the approximate amount of light reaching the forest floor under that tree. Thirty target trees were selected randomly.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".