Important Properties of Clay Content of Lateritic Soils for Engineering Project
Bibliographic record
Abstract
Clay-sized particles have been shown to control the engineering performance of lateritic soils, while the mode of formation and mineralogical composition of parent rocks in evaluating properties peculiar to clay-sized particles are yet to be a subject of serious research. Fresh Gneiss (GN), Quartz-schist (QS) and Granite (GR) were sampled in parts of Southwestern Nigeria. Thirty samples each of disturbed and undisturbed soils were also obtained at depths of 1.0, 1.5, 2.0, 2.5 and 3.0 m from profiles over GN, QS and GR. X-ray fluorescence and X-ray diffraction were employed to determine the major oxide geochemistry and clay mineralogy respectively, while grain-size distribution, plasticity characteristics, undrained cohesion (Cu) and volume compressibility (Mv) were determined following the British Standards (BS-1337). Parent rocks petrography reveals quartz and muscovite in QS, and quartz, alkali feldspars and biotite in GN and GR. SiO2/Fe2O3+Al2O3 indicates that soils form GN and GR fall into a class different from QS. Kaolinite (52.3-75.5%) formed the dominant clay mineral in the soils with subordinate amount of illite (2.3-17.6%), while 1.9 and 0.9% of smectite occurred at 3.0 m depth in soils over GN and GR respectively. The relationship between Ip and Fe2O3 taking cognizance of parent rock factors reveals the form of iron oxide that reduces the plasticity of lateritic soils. The mode of formation and mineralogical composition of parent rocks caused variation in cohesion and compressibility characteristics of lateritic soils.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".