Biodiversity of species on the grassland of Stong Pond, York University.
Bibliographic record
Abstract
On September 21, 2015 in between 2:30pm to 5:30pm with a temperature of about 19 degrees Celsius, our group members conducted an experiment on the biodiversity of species. In this experiment, a dataset was collected for 25 quadrats on the grasslands of Stong Pond, York University- Keele Campus. During the study, the quadrat was placed randomly on the grassland twenty five times as replicates and was continuous. Plant species were identified in the quadrat with the help of a plant guide and features such as color, leave shape/size were also observed in the identification process. Various species of grasses were present and all were counted as one species. Common species found were: Common Milkweed, Birdfoot Trefoil, Grass, Heath Aster, Late Purple Aster, Common Thistle, Queen Anne’s Lace, Canadian Goldenrod, and Cow Vetch. The species type, total number of species observed and the total plant abundance was recorded. The data obtained was based on our visual observations, and no other tools besides the quadrat were used. Ron Kleiman helped with obtaining this raw 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 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) | 0.015 | 0.011 |
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".