An architecture of reclamation in the city of Sudbury: where land and water meet
Bibliographic record
Abstract
The City of Greater Sudbury is home to a unique terrain that has been shaped by many events throughout time. The culture of the place is deeply rooted in industry as well as distinctive landscape feature such as barren rock outcroppings and bounty of lakes. After a century of invasive mining activity, the landscape is being reclaimed and the city of rocks is shifting to a city of lakes. Thanks to re-greening efforts many of Sudbury’s 330 lakes have been brought back from their acidic state. However, urban development has created new challenges for lakes found within the city’s core. This thesis explores the potential for an architecture of reclamation that doesn’t impose itself on the land but aids in the rehabilitation and ecological functions of the specific site. The project is a piece within a complex ecosystem that provides stormwater management benefits, educational amenities and ecological regeneration. Within the riparian zone of Ramsey Lake, this proposal acts as a mediary for clean water environments, where land and water meet
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.002 |
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".