Evaluation of Status of Heavy Metals Pollution of Sediments in Qua-Iboe River Estuary and Associated Creeks, South-Eastern Nigeria
Bibliographic record
Abstract
Sixteen bottom sediment samples collected from Qua-Iboe River estuary and associated creeks were analyzed for Cd, Cr, Cu, Fe, Pb, Zn, Ni, pH, Organic carbon (orgC),and grain size in order to assess the current pollution status in sediment of the study area. Concentration data were processed using Pearson correlation analysis. Sediment pollution assessment was carried out using Enrichment factor, Geo-accumulation index and Modified degree of contamination. The calculated enrichment factor showed that the sediment was enriched with Cd, Zn, Cu and Pb. The results of geo-accumulation index (Igoe) indicated that sediments are unpolluted with Fe, moderately polluted with Cr, Cu, Pb, strongly polluted with Cd and extremely polluted with Ni. This was attributed mainly to oil contaminating wastes and metal scraps. The results of the modified degree of contamination (mCd) revealed that the sediment of Qua Iboe estuary and associated creeks fall between 8 ? mCd ? 16 indicating very high degree of contamination.
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 | 0.001 | 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".