Study of Plant Abundance, Diversity, and Coverage in a Grassland Ecosystem
Bibliographic record
Abstract
On September 21 2015, the research group studied the biodiversity of plants seen in the grassland around Stong Pond on the York University Campus. The experiment occurred between 3:00pm and 4:00pm when temperatures were at 18 degrees Celsius and conditions were partly cloudy. During the study, plant abundance, species count, vegetation coverage and grass coverage were determined within a quadrat, for 25 randomly chosen locations throughout the grassland. Although locations were randomly chosen, the data obtained portrays the contrasting conditions throughout the ecosystem. Species that were commonly seen during the observations include Solidago canadensis (Canadian Goldenrod), Lotus corniculatus (Birdfoot Trefoil), Cirsium vulgare (Common Thistle), Aster ericoides (Heath Aster), Aster prenathoides (Late Purple Aster), and Xanthium strumarium (Common Cocklebur). All the data obtained during the study was based on visual observations of the quadrat; other than the quadrat no external measurement tools were used. Michael Chu, Diana Pik and Aisha Choudhry helped with obtaining the field 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".