Bibliographic record
Abstract
A transect was laid out at the woodlot at York university, Toronto Canada. The transect was laid from the outside edge of the woodlot to the center of the woodlot. Next a measurement of approximately 6 feet was assigned to find an innitial tree. From here the distance between it and the nearest adult tree (adult tree being discribed as one being at least 12 feet in height) of any species was measured with a second transect and recorded. Next the diameter at breast height (approximately 3' 5" from the ground) was taken of both trees and recorded. condition was also defined for both trees as a number variable between 0 and 2. The condition was estimated relative to the surrounding trees, 0 meaning dead and 2 meaning a full canopy of leaves. The purpose of this experiment was to find if the density of the woodlot would increase, in other words if the distance between 2 adult trees would decrease, as one walked farther into the woodlot. Further experimentation to be done in this area could be comparing the density (in the same way it was done here) at the edge of the woodlot closest to the nearby road and measuring tree density farther away from said road and comparing the data.
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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.108 | 0.100 |
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".