Toxicity and bioaccumulation kinetics of cadmium and potassium permanganate in two clades within the 𝘏𝘺𝘢𝘭𝘦𝘭𝘭𝘢 𝘢𝘻𝘵𝘦𝘤𝘢 species complex
Bibliographic record
Abstract
The freshwater amphipod 𝘏𝘺𝘢𝘭𝘦𝘭𝘭𝘢 𝘢𝘻𝘵𝘦𝘤𝘢 has been frequently used in toxicology since the 1980s due to its general sensitivity, ease of culture, and North America-wide geographic range. Over the past 20 years, molecular methods have revealed considerable genetic diversity underlying minimal phenotypic divergence among 𝘏. 𝘢𝘻𝘵𝘦𝘤𝘢 populations, which lead to the recognition of 𝘏. 𝘢𝘻𝘵𝘦𝘤𝘢 as a morphologically cryptic species complex comprised of 85 provisional species. Most Canadian and American toxicology laboratories maintain a single species (clade 8), and the Canada Centre for Inland Waters (CCIW) in Burlington, Ontario appears to be the only lab that cultures a different species (clade 1). Only recently has the impact of species-level divergence within this cryptic complex been investigated to determine the impact on toxicity and bioaccumulation. Differences in ionic requirements, bioaccumulation, and tolerance have been previously demonstrated among clades within this complex. Due to their relative prevalence among toxicology laboratories, research from our group has focused on clades 1 and 8, which were identified with genetic barcoding at the mitochondrial cytochrome 𝘤 oxidase I gene. In the present study, the saturation model was used to estimate uptake and depuration kinetics, short-term bioaccumulation, mortality, and growth inhibition responses of these two clades to cadmium and potassium permanganate. Significant differences between tolerances and bioaccumulation could not be determined in this study because of overlapping 95% confidence intervals, likely due to the low tolerance of the clades to both toxicants. Future research may benefit from comparing the acclimation capabilities of these clades. Reporting in toxicology can be improved by genetically identifying clades, particularly as accessibility to genetic sequencing continues to increase.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".