Development of stabilised soils for construction applications
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
Lateritic soils from Papua New Guinea were stabilised with various percentages of rice husk ash (RHA), finely ground natural lime, cement and their combinations. The influence of stabilisers and their combinations was evaluated through Atterberg limits, standard Proctor compaction, unconfined compressive strength, splitting tensile strength, modulus of elasticity and California bearing ratio (CBR) tests. The durability of 38 stabilised soil mixtures was also investigated by studying the influence of water immersion on strength, water sorptivity and drying shrinkage. Correlations between compressive strength, modulus of elasticity and CBR were also established. Theoretical analysis of pavements incorporating subgrades improved by stabilised lateritic soils under traffic loads showed technical benefits in comparison with conventional flexible pavements without improved subgrades. Suitable stabilised soil mixtures using RHA, lime, cement and their combinations which can be used for the construction of road pavements, airfields, earth dams and low-cost housing are proposed. The use of locally available soils, RHA and lime in the production of stabilised soils for such applications can provide sustainability for the local construction industry.
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