Trace elements and organochlorine pollutants in selected fish species from Lake Phewa, Nepal
Bibliographic record
Abstract
Lake water and fish livers and gills of sahar (Tor putitora), spiny eel (Mastacembelus armatus), African magur (Clarias gariepinus), and tilapia (Oreochromis niloticus) from Lake Phewa, Nepal, were assessed for the concentrations of trace metals/elements and persistent organic pollutants. The lake water was neutral with low ionic and metallic concentrations as compared to high-altitude lakes of Nepal. The four elements Cu, Zn, Se, and Cd had highest concentrations in livers, indicating uptake from diet, whereas four other metallic elements Cr, Mn, Ni, and Pb had highest concentrations in gills, indicating uptake from lake water. O. niloticus tended to have most of trace metals in the liver at higher concentrations than the other species but significant differences among the different species were found only for Mn, Ni, and Zn in the gills. A pilot study on the concentrations of persistent organic pollutants in muscle revealed that dichlorodiphenyltrichloroethane and related compounds were the dominant organochlorine pesticides, having highest concentrations in C. gariepinus and lowest in O. niloticus.
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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 | 0.000 | 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".