Bibliographic record
Abstract
Data was collected at 3:00 p.m. on October 3, 2014 at the woodlot and grassland located between Chimneystack Road, York Boulevard and Keele Street, at the East end of York University, Toronto, ON. It was raining and cloudy, and the temperature was 23°C. Wind speeds ranged from 4-18 mph. The purpose to collect this data was to use distance measuring methods to estimate bird abundance at York University. Specifically, this dataset includes distance data along transect tapes for birds on a woodlot and grassland at York University. Potentially, this data could be used to compare the abundance of birds in woodlot and the abundance of birds in grassland areas. It is predicted that there would be a greater abundance of birds in the woodlot, due to the weather conditions, as birds would find shelter from the rain in the canopy of the trees. Five trials were completed in both locations. A 10 meter transect tape was randomly placed in the grassland, and bird sightings were recorded for 5 minutes while walking along the transect during each trial. Frequency of birds, or number of birds sighted, bird species, distance from transect (m) and wind speed were recorded for each sighting during each trial. This process was repeated five times in the grassland. In the woodlot, the trial length was shortened to 3 minutes, everything else remaining the same. A 10 meter transect tape was randomly placed in the woodlot, and bird sightings were recorded for 3 minutes during each trial. Frequency of birds, or number of birds sighted, bird species, distance from transect (m) and wind speed were recorded for each sighting during each trial. Bird species were determined using previous knowledge of the observer, and if there was any uncertainty about what species a bird was, then it was recorded as “unidentified”. Distances from the transect were estimates, recorded in meters. Wind speed was recorded as a number on the Beaufort scale and was estimated, as there were no actual devices monitoring the wind speed. Group members: Alexander Karakatsanis, Arlene Tran and Jenna Teixeira. Dataset collected by: Rajbir Ghuman
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.064 | 0.024 |
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".