Gardiner Expressway East Planning Study Innovative Planning Techniques
Bibliographic record
Abstract
The Gardiner Expressway in downtown Toronto is 60 years old and facing the need for significant and expensive reconstruction. The City of Toronto, partnered with Waterfront Toronto, initiated a planning study to identify the preferred infrastructure solution for the eastern section of the Gardiner Expressway. The technical work to assess infrastucture alternatives features a number of innovative analysis techniques, including: The scope of the planning study integrates an Individual Environmental Assessment for the Gardiner Expressway with an Urban Design study for the neighbourhoods adjacent to the Gardiner Expressway corridor; The transportation demand data collection program featured a survey of existing traffic patterns and speeds using Bluetooth signals from electronic devices in passing vehicles, and; The transportation modeling approach features a marriage of the existing City of Toronto EMME/2 macroscopic model and a microsimulation model of the primary study area in Paramics software. This paper will present some of the creative planning techniques adopted in the Gardiner Expressway East Planning Study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".