Polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans in sediments from two Ethiopian Rift Valley Lakes
Bibliographic record
Abstract
The aim of our study was to evaluate surficial sediments from two selected Ethiopian Rift Valley aquatic environments – Lake Awassa and Koka Reservoir, for the occurrence of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). The total concentration of target compounds resulted several times higher in the lake (270.39 pg/g dry weight than in the reservoir (63.17 pg/g d.w.). Similarly, concentrations measured as WHO-Toxic Equivalent (WHO-TEQ) were 23.78 pg TEQ/g d.w. and 4.03 pg TEQ/g d.w., respectively. Obtained results, in reference to the Canadian Sediment Quality Guidelines, exceed the limit of 0.85 pg TEQ/g d.w. in both lake and reservoir, as well as probable effect level (PEL) of 21.5 pg TEQ/g d.w. in lake sediment, and thus represent high pollution levels of analyzed samples.
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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 | 0.001 | 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".