Guidelines for design decision-makers
Bibliographic record
Abstract
The purpose of this report is to provide support to the design decisions-makers during the design process. For each of the defined design step decision the important topics to consider were identified, the key stakeholders are declared and the purpose of LCA at the selected design step is defined. The report covers: The definition of the design steps, the definition of the tasks in each design step and an overview of the relevant milestones for performing LCA; An overview of the systematic building decomposition methods and the appropriate levels at each design step; An overview of the tools that can be used for LCA and a selection process for choosing the right LCA tool. A special emphasize is given to the topic of Building Information Modelling (BIM), how the BIM tools can facilitate the LCA assessment and what information should be implemented in the BIM model; Strategies on how to reduce the design-related uncertainties; An overview of the visualization of the LCA results and which are appropriate in the selected design steps.
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 | 0.042 | 0.079 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.011 | 0.007 |
| Research integrity | 0.016 | 0.009 |
| Insufficient payload (model declined to judge) | 0.075 | 0.077 |
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".