Bibliographic record
Abstract
Eglinton Avenue is Toronto’s east-west “metropolitan ” street. It exhibits every type of built form and streetscape to be found in our City. The fact that most of Eglinton Avenue is identified as an Avenue and designated Mixed Use Areas or Employment Areas in the Official Plan makes it a prime candidate for reurbanization and rejuvenation. The diversity of Eglinton Avenue makes it a fascinating and challenging part of the City. The Eglinton Crosstown LRT is scheduled to open for business from Weston Road to Kennedy Road in 2020. This investment by Metrolinx of more than $5 billion has created an impetus to study Eglinton Avenue and develop a long-range plan for its intensification and beautification. The Eglinton Connects Planning Study is the comprehensive planning review of Eglinton Avenue which responds to the opportunity presented by the LRT. It proposes a Plan for Eglinton Avenue that is based on a long-term Vision, a Vision of a green, beautiful linear space that supports residential living, employment, retail and public uses in a setting of community vibrancy. The Vision is to be realized through 21 recommendations, organized into three themes: Travelling, Greening and Building. The Vision and its
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.410 | 0.200 |
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".