Characterization of Density and Porosity of Rocks Samples from Ogun State of Nigeria
Bibliographic record
Abstract
Knowledge of densities of rocks is essential in petrological and geological studies, interpretation of gravity anomalies and ground water exploration.Fifty samples were collected from Abeokuta, Sagamu, Odeda, Ewekoro, Ibese Yewa North Local Government, Ijebu East Local Government and Obafemi Owode in Ogun State and dry bulk density, saturated density, porosity and particle density were determined. Results showed that Ewekoro shale has the lowest mean density of 1.35g/cm3 while Ibese, Yewa North Local Government limestone has the highest mean density of 3.9g/cm3.Porosity ranges from 0.030 to 0.640 with the granite in Odeda local government having the highest porosity and the shale in Ewekoro local government having the lowest porosity.Mean porosity for all the rocks samples in the seven Local Government Areas was 0.34. Test of significance revealed that there is significant relationship in the values of density of rock samples within the state.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".