Spatial distribution of gamma radiation dose rates from natural radionuclides and its radiological hazards in sediments along river Iju, Ogun state Nigeria
Bibliographic record
Abstract
This study assessed the radioactivity level of Iju River sediments and its associated radiological risks exposure to human. Gamma absorbed dose rates were measured using a portable gamma spectrometer at an interval of 50 m between each point (Model No:RS-125 manufactured by Canadian Geophysical Institute). The measured absorbed gamma dose rates range from 22 to 59 nGy/h with the highest value noted in site 13. The mean activity concentrations of U-238, Th-232 and K-40 from Iju river sediments were 24.1 ± 0.4 Bq/kg, 35.2 ± 1.1 Bq/kg and 501.0 ± 11.1 Bq/kg, which were lower than the world average values of 32 and 45 for U-238 and Th-232 by 25% and 21% and higher than 412 Bq/kg for K-40 by a factor of 0.22 (22%). This highest value of K-40 found in site 6 may be due to the presence of feldspartic minerals buried in the sediments. Consequently, the radiological hazard indices were below the permissible limits except the mean value of 28 × 10−2 for excess lifetime cancer risk (ELCR) for the samples collected in site 6, which is higher than the average world value of 0.29 × 10−3 by a factor of 0.03. The regression model indicates that Th-232 attributes more radioactivity impacts on the soil sediments than the contributions of U-232 and K-40, as such, presumed to be the radionuclide parameter controlling the depositional process in the region.
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 | 0.001 |
| 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 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".