Northern Kuwait Soil Evaluation in Producing Environmentally Friendly Blocks
Bibliographic record
Abstract
This paper presents the initial results of the evaluation of soil samples collected from the northern regions of Kuwait, in addition to the preliminary results of Compressed Earth Blocks (CEB) compressive strength tests for different mix designs. The performed tests and the produced blocks are part of a series of tests that evaluate the applicability of producing environmentally friendly construction blocks. The overall purpose of this study is to introduce a construction material that can be of environmental benefits to the Gulf Cooperation Council (GCC) region to reduce the construction industry impact on the CO2 emission in the region. Soil samples were collected from Boubyan Island and Sabriya area, located in northern Kuwait. Basic engineering properties of the samples were obtained, including the soil gradation, the Atterberg limits, and the Optimum Moisture Content (OMC). Subsequently, 24 mix designs of CEB were tested to evaluate their compressive strength. The results showed that increasing the percentages of the clayey/silty soil in the block mixtures reduces the compressive strength of blocks with high cement percentages. Whereas compressive strength of blocks containing low cement percentages were increased with the increase of clayey/silty soil percentages to a certain extent. The study recommends that the soil/sand ratio is limited to 1.0.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".