Bibliographic record
Abstract
This dataset was collected September 30th 2015 at the grasslot surrounding Stong pond, behind Osgood Law School at York University, Toronto ON. The weather was clear skies at 20 °C. The experiement had a groups of 4 conducting the transects, split into teams of 2eachs to be more time efficient. One team recorded 2 transects while the other did the last one. The group observed birds abundance and distribution in their natural habitat of the grassland. The original experiment involved recording frequency of birds, species, wind speed, the distance between the bird and the transect between different habitats at a higher transect rate. Due to time constraints, the group was only able to conduct the experiment in the grassland and not in the woodlot, also 3 transects were done instead of 5. To record the wind speed, the Beaufort scale was to be originally used. Since the two teams seperatly recorded each transect, there were some irregularities between them as example, the first team recorded the gender of ducks since it was evident but the second team did not. Both teams spotted similar distribution of species.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.012 |
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".