Life-cycle sustainability assessment of geotechnical site investigation
Bibliographic record
Abstract
The life-cycle impacts of site characterization, an important component of most geotechnical engineering projects, are typically not considered in practice nor have they been studied in detail. A life-cycle sustainability assessment (LCSA) was performed to evaluate the environmental and economic impacts of several common site investigation methods. The potential impacts of these methods were computed to provide normalized metrics for the mobilization, drilling, sampling and (or) testing, and borehole sealing phases of the life cycle. These environmental impact and cost metrics were then applied to a “typical” 30 m exploration to compare different site investigation methods. Next, the metrics were used to assess the impacts of small and midsized industry investigation programs to investigate how impacts scale with project size. Scenario analyses were then performed on the midsized project to consider how different mobilization choices, grouting materials, and exploration methods influence total impacts. Collectively, this study provides a reference and framework that allows practitioners to assess environmental impacts in parallel with cost when designing site investigation scopes of work.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".