Distribution of polycyclic aromatic hydrocarbons in Woji Creek, in the Niger Delta
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
Abstract This is the first study related to PAHs distribution in the Woji Creek (Nigeria), that points out potential contaminant sources. The study involved sampling of water and sediment from five stations along the creek monthly (from August to October in 2018). Samples collected were analysed for the concentration of sixteen Polycyclic Aromatic Hydrocarbons (PAHs) using an Agilent 7890B Gas Chromatograph (GC-MS). Eleven (11) PAHs were identified in the water samples with five (5) below detectable limits (Naphthalene, Phenanthrene, Pyrene, Indeno (1, 2, 3, -cd) pyrene and Benzo [(g), (h), (i)] perylene). Results from the surface water showed that in the month of September, the concentration ranged from 6.029 ppm in S4 to 28.331 ppm in S5. October recorded a PAHs concentration ranging between 6.094 ppm at S1 and 29.257 ppm at S5. In the sediment highest concentration of PAHs was recorded in S5; 1809.08 ppm in August, 1810.05 ppm in September and 1821.5 ppm in October. The concentrations of PAHs in sediment were significantly greater than those in the water. In both sediment and water samples, the highest concentrations of total PAHs were recorded in station 5 and the lowest in station 4. The composition of PAH in water identified the dominance of 2 and 3 rings (Low Molecular Weight (LMW) PAHs) over 4, 5 and 6 rings (High Molecular Weight (HMW) PAHs). In the sediment samples analysed, LMW PAHs (2–3 rings) made up about 30% of the composition, while HMW PAHs (4–6 rings) made up about 70% of PAHs member groups. Cross plots showed that the PAHs could have come from petroleum and combustion.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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