Bibliographic record
Abstract
This data was collected near the Lumsden Ave. entrance to Taylor Creek Trail in East York, Toronto. The area being surveyed was 5 or more metres away from the trail path. The area was then broken into twenty, roughly 1x1 metre, quadrats which were arranged linearly and going into the shrubbery, perpendicular to the beaten trail path. Within each quadrat the species richness was measured. This means that the number of species present was counted. Species were identified using the smartphone app called “Picture This” and also the book, Newcomb’s Wildflower Field Guide. The species frequency was also measured by estimating the percent cover provided by each species that were present. And finally ground cover was measured by approximating what percentage of the ground was covered by vegetation in general. Our ground cover values are not the sum of species cover as one would assume. This is because with species cover, we’re including vertical cover, but with ground cover, we’re including only cover along the floor. This pilot was conducted over a period of two days in two independent plots but close-in-proximity to each other. The first day’s recordings are labelled Plot A. The second day’s recordings, in a slightly different but still regionally close location are under Plot B. Next to each “Plot” (second column) there are “Quadrat” numbers (third column). Dataset columns: - Date – Date on which pilot was conducted - Plot – Which of the two possible test sites the specific quadrats being measured were present in. - Quadrat – 1x1 metre square segments of the plot - Researcher – Person taking measurements - Location – Where the plots were located - Species_richness – Number of species were present in each plot - Species_cover – Percent cover per species - Total_cover – Percentage of quadrat floor that is covered by vegetation
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.166 | 0.156 |
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".