Effect of Shade on Abundance and Diversity of Plant Species in a Grassland
Bibliographic record
Abstract
Data was collected on October 17th, 2014 at 3:00 p.m. and October 24th, 2014 at 2:45 p.m. at the grassland located between Chimneystack Road, York Boulevard and Keele Street, at the East end of York University, Toronto, ON. On October 17th, 2014 it was raining and cloudy, and the temperature was 17°C; on October 24th, 2014 it was sunny, and the temperature was 16°C. The purpose to collect this data was to determine the effect of shade on the abundance and diversity of species in a grassland by comparing number of individuals, number of different species, percent plant coverage and percent grass coverage of the center of grassland (no shade) and the edge of the grassland/woodlot (shade). It is predicted that there will be greater diversity and abundance of plants in the center of the grassland compared to the edge because only shade tolerant species would be able to thrive on the edge in the shade. On each day, a 1m x 1m quadrat was placed at the edge of grassland/woodlot and another quadrat was placed in the center of the grassland, 15 meters away from the quadrat at the edge, measured by using a transect tape. In each quadrat, number of individual plants were counted and recorded as a number; number of different plant species were counted and recorded- without the use of a species guide; percent plant coverage was estimated by seeing what proportion of the quadrat the plants occupy; and percent grass coverage was estimated by seeing what proportion of the quadrat is occupied by grass. This data was counted as a pair, and the next pair data was obtained by repeating this method 1 m away from the first pair. This was repeated for a total number of 20 pairs on each day, and 40 pairs in total over the two days. This experiment was carried out by Rajbir Ghuman, Alexander Karakatsanis, Arlene Tran and Jenna Teixeira.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".