Sustainability Assessment of the Residential Land Use in Seven Boroughs of the Island of Montreal, Canada
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
High resource utilization in the residential sector, and the associated environmental impacts, are central issues in the growth of urban regions. Land-use urban planning is a primary instrument for the proper development of cities; an important point is the consideration of the urban form’s influence on resource utilization intensity. Emergy synthesis, an energy-based methodological approach that allows the quantification and integration of both natural and human-generated flows interacting in urban environments, was used to assess sustainability of the residential land use of seven boroughs on the Island of Montreal. Natural resources, food, water, acquired goods and services, electricity and fuels were the main flows considered in the analysis. Results suggest that income, household size and distance to downtown are the variables affecting resource utilization intensity more noticeably and that allocation of green area coverage is an important parameter for controlling land use intensity. With the procedure used for calculating resource use intensity in the seven boroughs, it is possible to generate a tool to support urban planning decision-making for assessing sustainable development scenarios. Future research should consider urban green space potential for accommodating local waste treatment systems, acting as a greenhouse gas emissions sink and promoting human health.
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.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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