Comparison of using two LCA software programs to assess the environmental impacts of two institutional buildings
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
The current trends in climate change have captured the attention of stakeholders across multiple industries, including the building sector. With the introduction of innovative building materials such as mass timber products (MTPs), it has become essential to evaluate their environmental performance. In response, a variety of life cycle assessment (LCA) software programs are available to meet this need. However, it is crucial to understand how different LCA software and databases might influence the results. This study was aimed at exploring the impact of two widely used LCA software programs, SimaPro and Athena Impact Estimator, on LCA results. Two buildings were employed to conduct this study, a traditional institutional building and a mass timber building currently under construction. By comparing the numerical outputs from both software programs, it was discovered that while both could reach similar conclusions regarding the environmental impacts of a building, their use is limited to comparative purposes only. The software programs produced distinct numerical values in their outputs and attributed the sources of impacts differently, indicating they cannot be used interchangeably. However, either SimaPro or Athena Impact Estimator was suitable for estimating the global warming potential of a building during stages A1 to A3.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it