Benchmarking and target-setting for the life cycle-based environmental performance of buildings
Bibliographic record
Abstract
The purpose of this report is to provide the foundations to responsible actors for further developing their specific methods to create life cycle related benchmarks for the non-renewable primary energy demand/consumption, GHG emissions and further environmental impacts of buildings and to increase the mainstreaming of practice globally. This report covers: General principles and recommendations for the development of benchmarks and target values based on a bottom-up approach (technical and economic feasibility) and a top-down approach (science-based targets to define a safe operating space inside planetary boundaries) General principles and recommendations for the application and interpretation of benchmarks General principles and recommendations for the documentation and communication of benchmarks Recommendations for terms, definitions, system boundaries and accounting rules for buildings with an absolute zero or net zero GHG emission approach (climate neutral buildings). The specific objectives of this report are to: clarify methodological questions with respect to the development of benchmarks to aid low carbon and low environmental impacts for construction, operation and end of life. provide a consistent and transparent basis for a reporting structure for environmental benchmarks in line with international standards contribute to the interpretation and supplementation of international standards to improve their applicability and support their dissemination promote long-term and life cycle-based thinking, by encouraging the early consideration of likely future environmental impacts regarding maintenance, repair and replacement as well as of durability and adaptability of building components and the building as a whole contribute to the overall efforts of national governments and standard makers to guide construction and real estate industry on how to respond to climate change and other mega trends like depletion of natural resources
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 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".