Sustainable Design Of A Residential- Mixed Use Mid-Rise In The Junction Triangle Neighbourhood
Bibliographic record
Abstract
The purpose of this thesis is to design and present building strategies for housing that demonstrate efficient well-integrated continuity between human, nature, and technology for a high – mid-density building in a populated urban environment on a main avenue in Toronto’s Bloor Street south and the West Toronto rail path. The building design incorporates sustainable strategies such as Passive cooling methods, energy generation, Rainwater harvesting, CO2 consumption, Vertical Integration of vegetation, Natural ventilation, Daylight penetration and constructed wasteland for rainwater treatment. The objective is to achieve a better state of mental and physical health for the occupants and their neighbourhood. The thesis proposes these design strategies without the constraint of financial viability in this day and age, so as to promote such methods and mentality in forthcoming constructions. \nThe thesis asks, how can Architects participate in reforming our society with today’s ever-changing needs? What are those most pressing issues? How can architecture tackle these issues from its own standpoint? The thesis takes the stand that Global warming and mental health are the primary contemporary issues in developed countries, subsequently, in developing countries, global warming will have the highest devastating effects on the most fragile and vulnerable settlements. In order to steer the planet away from an ecosystem collapse and to reconstruct that environment, we need to address humanity’s manipulation of the environment and change the makeup of the physical spaces we occupy. The purpose of this thesis is to research by design in the specific setting of Bloor St South meets West Toronto rail path so as to find the best possible solution regarding overall health and sustainability.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".