Bibliographic record
Abstract
Geotechnical constructions involve consumption of a vast amount of non-renewable natural resources and energy- and carbon dioxide-intensive materials (e.g. cement and steel) that contribute significantly to global warming and climate change. This paper uses drilled shafts as an example to illustrate the importance of environmental impact assessment in the design phase of foundations. Life-cycle assessment (LCA) is used to quantify the environmental impacts of construction of single drilled shafts and groups embedded in sandy soil profiles. Parametric studies are conducted to investigate the effects of soil properties, design parameters and hauling distances of construction materials and equipment on the environmental impacts of single drilled shafts. For pile groups, different configurations, applied load, centre-to-centre spacing and thickness of pile cap are considered in the parametric study. The global warming impact and human toxicity of a typical drilled shaft are found to be 39 and 486% of annual world impact per person, respectively. Based on the study, charts and tables are developed that may be used for quick estimation of the global warming impact of drilled shafts without the use of specialised LCA software programs.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".