York University Tree Inventory: Health
Bibliographic record
Abstract
Trees are important parts of urban spaces, and their health is an important concern for urban planners. Urban trees are subject to higher levels of disturbance both directly from human activity or indirectly through pollution or climate effects caused by urbanization. One potential disturbance factor on tree health is ground vibration caused by underground subway lines. Ground vibration from subways has been known to cause structural damage on buildings and structures such as bridges and highways, and trees are analogous permanent natural structures rooted in the ground. To date, there has been little research specifically concerning the effects of ground vibrations on tree health. This study is a longitudinal study examining the effects of a recently built subway line underneath the York University campus on tree health. Using data from a tree census conducted prior to the Toronto Transit Commission subway extension running directly under the university becoming fully functional, and a new set of data collected over October 2020 to March 2021, this study examined the effects of subway disturbance on the growth and health of 745 trees on the York University campus. Trees from ten different species were measured at varying distances from the subway line with groups both within and outside of 200 meters from the subway. It was hypothesized that tree growth and health would decrease closer to the subway, and that species-specific patterns would be observed. However, this study found no significant relationship between distance from the subway and tree growth or health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.020 |
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; both teacher heads agree on what is shown here.
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".