Disturbance as a factor in influencing herbaceous plant colonization patterns in urban green spaces
Bibliographic record
Abstract
Data tables for project titled: Disturbance as a factor in influencing herbaceous plant colonization patterns in urban green spaces. Includes species name per pseudo-quadrat, species richness per pseudo-quadrat, species richness per pseudo-transect, for each pseudo-transect and sampling site. Data was acquired on 09/17/2020, and fully processed by 09/20/2020. Site A refers to the stretch of road along Webb Dr, Mississauga, Ontario near John Bud Cleary Park between Grand Park Dr. & Confederation Pkwy. Along this road are two sites sampled: a moderately disturbed sampling site, and a highly disturbed sampling site - due to both occurring on the same road, they are both denoted as Site A. Each sampling site consists of two transects: one towards the interior of the city block which is assumed to be the source of recolonizing plants due to its larger size, another runs on the patch of land directly adjacent to and between the asphalt road and concrete sidewalk panels. In lieu of perfectly square quadrat sampling and tape measurements, each sidewalk panel’s polygonal shape was used to denote a ‘pseudo’ quadrat and to define the spatial limits of sampling. In this context, site denotes the road at which sampling occurred; sampling site refers to a set of double pseudo-transects, one for the interior of the city block, and one running parallel to that transect as well as the asphalt road to which it is adjacent. Dataset is organized into Excel sheets per sampling site.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".