A Study on the Correlation between Birds in the Danby Woodlot versus Grasslands.
Bibliographic record
Abstract
Meta Data: Time: Continuous- Time was recorded using a timer that was set to two minutes, and birds that flew over the transect within that time frame were recorded for that interval. Distance of bird from transect: Numerical and Continuous. Each member of the group estimated the approximate distance from the bird to the transect in meters, and the average measurement was recorded in meters. Total number of birds: Numerical and discrete. Only counted the birds that flew over the transect area. Methods: Transect tape was randomly placed within the grasslands of Danby woods, where the area was closely observed for birds. The transect tape was 30 meters long in length and the readings were taken in two minute intervals, recording the number of birds that flew over the transect within each interval. A total of five transects were done in the grasslands, and 5 transects in the woodlot. The grasslands were observed from 3:38pm- 3:50pm, and the woodlot was observed from 3:54pm-4:04pm. Study Site Description: This field study was conducted at the Danby Woodlot located at York University, Toronto, Ontario, Canada. 43.7735 N, 79.5019 W. The weather was 12 degrees Celsius , cloudy with a drizzle near the end. Windspeed 24km/hr E. Hypothesis: There will be a correlation between the abundance of trees and the number of birds seen because the trees provide shelter for the birds, so they will be spotted more in the woodlot versus the grasslands. Predictions: 1. 1.Birds that are seen will be flying in groups due to migration. 2. 2.More birds will be seen in the woodlot than grasslands 3. 3.Most of the birds observed will be Seagulls. <br><br>Group Members: Lanisha Thangeswaran, Niyousha Taati, Rija Ghani<br>
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 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 | 0.001 |
| 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) | 0.021 | 0.002 |
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; both teacher heads agree on what is shown here.
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".