Heavy metal concentrations in
Bibliographic record
Abstract
Saint-Augustin Lake is an urban lake in Québec, Canada that has been subjected to long periods of direct human impact, mainly due to agricultural and urban activities, with great changes in trophic status and chemistry occurring within the last few decades. In 2009, during an examination of the lake bottom substrate, the presence of the invasive species Cipangopaludina chinensis (Reeve, 1863) was found on floor bottom sediments. The gastropods soft tissues were mineralized and analyzed by ICP-OES. The purpose of this study was to estimate concentrations of heavy metals in C. chinensis, describing the relations of these values with the sediment metal. In gastropod soft tissues the overall common trend in the heavy metal concentrations was revealed in the following order: Fe>Mn>Zn>Cu>As>Ni>Pb>Cd>Cr. Biota-sediment accumulation factors (BSAFs) have shown that C. chinensis cannot be used as a bioindicator of heavy metal pollution and exposure in the Canadian lakes where it is present. In fact, while the sediments of Saint-Augustin Lake are characterized by high metal concentrations, C. chinensis does not have high bioaccumulation factors (BSAFs <1.0). By literature comparison with other aquatic organisms in polluted ecosystems at different latitudes it was possible to affirm that the concentrations of Fe, Mn and Zn in C. chinensis tissues are considerable if compared with these sites.
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 | 0.001 |
| 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) | 0.002 | 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".