Urban Estuary:A Successful Application of Landscape Urbanism in Toronto's Lower Don Lands
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Toronto's Lower Don Land is located in the intersection between Toronto Waterfront and mouth of Don River,a former port just east of downtown.With the rapid development of Toronto,more and more new immigrants are trying to move in;this area is facing an unpredictable pressure of future development.How to utilize the theory of landscape urbanism to resolve the conflict between abandoned and development has been a great challenge for Toronto Waterfront Conservation Agency(TWCA).This paper is focusing on explaining the application of landscape urbanism on fast growing situations.Via the introduction and analysis of the winning proposalUrban Estuaryin Low Don Lands Design Competition in 2007,the author aims to find out useful lessons that Chinese cities could learn from the western experiences.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 it