Ecology Lab 2 Grassland Dataset (Pond distance vs vegetation percentage)
Bibliographic record
Abstract
This ecological experiment which was done at York University grasslands, Monday, September 20/2016, at 2:30 P.M, Studies the relationship between the vegetation percentage (ratio of plant individuals to grass) and the distance from the pond. The study was done using a 1meterx1meter square quadrat which was randomly thrown 25 times. Methods A 1meterx1meter square quadrat was used for this experiment. The quadrat was randomly thrown 25 times (n=25 trials) in the grasslands beside the pond and the total number of plant individuals, number of plant species, vegetation percentage, and grass percentage in the quadrat box were counted, calculated and recorded on a piece of paper. The data was then transformed into an excel sheet and uploaded on “FIgshare.com”. Hypothesis There is a correlation between the distance the individuals are from the pond and the percentage vegetation (vegetation density). Prediction The quadrats that were randomly thrown closer to the pond will have a higher vegetation percentage than the ones thrown further away from the pond. Meta-data Trial number: the number of trials that the quadrat was randomly thrown to collect the data which was 25 times therefore n=25 trials. Canadian Goldenrod (yellow) Heath Ester (white), Butter and Eggs, Common Thistle (thorn), Late Purple Aster, small tree: Plants species found in York Universities grassland fields. Please refer to a plant atlas for more information about these plant species. Number of plant species: The different types of plant species that were seen in the quadrat box. Total number of plant individuals: The total number of plants in the square quadrat were counted. This included all species of plants in general and included any type of plant. i.e. how many plants in general in the box. Vegetation percentage (vegetation density): The percentage of plants compared to grass in the square quadrat. In other words, the ratio of plants to grass in the quadrat. Grass percentage (grass density): The percentage of grass compared to plants in the square quadrat. In other words, the ratio of grass to plants in the quadrat.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.020 |
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".