Sustainability assessment of earth-retaining wall structures
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
This paper describes a sustainability assessment methodology and example to select the best sustainable option from candidate conventional gravity and cantilever wall types and steel and polymeric soil-reinforced, mechanically stabilised earth (MSE) walls of different heights. Analyses were carried out using the value integrated model for sustainable evaluations (Mives) methodology, which is based on value theory and multi-attribute assumptions. The paper identifies how indicator issues are scored, weighted and aggregated to generate final numerical scores that allow solution options to be ranked. The final scores include an adjustment based on stakeholder preferences for the relative importance of the three sustainability pillars (environmental, economic and societal/functional). The analysis results show that MSE wall solutions were most often the best option in each category compared to conventional gravity and cantilever wall solutions and, thus, most often they were the final choice when scores from each pillar were aggregated to a final score. However, when cost was weighted most highly of the three pillars, then the conventional wall solutions gave the highest (best) Mives score for walls 3 m high. If environmental issues were the most important concern of stakeholders, then the MSE solutions were the best solution, particularly for walls 5 m high and higher.
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 | 0.000 |
| 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 it