Lake trophic status and bioaccumulation of polychlorinated biphenyls in benthic organisms: a comparison between littoral and profundal invertebrates
Bibliographic record
Abstract
We investigated the influence of lake trophic status on accumulation of polychlorinated biphenyls (PCBs) in littoral and profundal invertebrates from 19 lakes in southern Sweden. The PCB concentration in profundal chironomids (Chironomus sp.) was negatively correlated with lake trophy but the concentration in littoral crayfish (Pacifasticus leniusculus) was unrelated to shifting nutrient regimes. PCB concentrations in chironomids were negatively correlated, while crayfish did not correlate with lake total phosphorus. Two findings indicate that different processes determine bioaccumulation in littoral and profundal invertebrates: (i) a lack of correlation between PCB concentrations in crayfish and chironomids within lakes and (ii) some differences in congener distribution in the two species. We suggest a possible explanation in that chironomids are directly exposed to settling material from the pelagic zone, while crayfish are omnivorous and feed mainly in the littoral zone. A intensive investigation on one pond population could not reveal any individual factors, such as lipid content, size, or sex, influencing bioaccumulation of PCBs in crayfish.
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 | 0.000 |
| 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) | 0.001 | 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".