Sustainable energy? A feasibility study for Eastside, Birmingham, UK
Bibliographic record
Abstract
Eastside, a 130 ha brownfield site located to the eastern side of Birmingham's city centre, is undergoing social, economic and environmental changes, driven mainly through public and private investment estimated to be worth £6 billion. The regeneration programme is well under way and it aims to turn a once deprived inner-city area into the regions first ‘sustainability quarter’ Achieving a sustainable quarter, in terms of energy, will require reductions to be made in energy demands compared to typical practice, for example through more thermally efficient buildings and utilisation of low-energy technologies. In addition it will require these demands to be met through renewable technologies rather than fossil fuels. This paper presents estimates for the total energy demands from the various developments planned within Eastside assuming typical and good-practice scenarios. The paper then assesses the feasibility of introducing various renewable energy supply technologies and combined heat and power (CHP) technologies in order to meet these demands. Finally the paper presents a simplified costing scheme for assessing the potential of renewable technologies to secure energy supplies while limiting carbon emissions. The renewable technologies are compared directly, aiming at providing an independent viewpoint for decision makers when considering which technologies to adopt. While the study focuses on Eastside, the lessons learned from this study are vitally important for redevelopment programmes being undertaken elsewhere.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".