How Ground Improvement Contributes to the Green Building Movement
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
Owing to the tremendous efforts of the United States Green Building Council (USGBC) and the development of the LEED rating system, a mechanism has been created to evaluate construction projects from a “green building” standpoint. Using a free, foundation industry-specific carbon calculator tool for this study, the carbon footprint of a theoretical project was evaluated for four separate foundation options on the given site, using consumption data from real projects. Two methods of ground improvement, dynamic compaction and aggregate piers were the first two options considered, the third option was driven pile foundations, and the final option was a full removal of the unsuitable fill material and replacement with imported structural fill. Results of the study indicated that under the assumed conditions, ground improvement programs can have a carbon footprint on the order of 2 to 6% of the footprint associated with full removal of the fill material to send to a landfill. As such, this paper recommends that further evaluation be given towards establishing a new LEED credit related to geotechnical construction issues, or at minimum, establishing a carbon footprint reduction scorecard that could be incorporated into the existing LEED infrastructure.
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 | 0.001 | 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