The relative sensitivity of four benthic invertebrates to metals in spiked-sediment exposures and application to contaminated field sediment
Bibliographic record
Abstract
The relative sensitivity of four benthic invertebrates (Hyalella azteca, Chironomus riparius, Hexagenia spp., and Tubifex tubifex) was determined for Cd, Cu, and Ni in water-only and in spiked-sediment exposures. Survival (median lethal concentrations [LC50s] and the concentrations estimated to be lethal to 25% of test organisms [LC25s]), and endpoints for growth and reproduction (mean inhibitory concentrations [IC25s]) were compared. The sensitivities differed depending on the species and metal, although some trends emerged. In water-only exposures, H. azteca is the most sensitive species to cadmium and nickel, with mean LC50s of 0.013 and 3.6 mg/L, respectively; C. riparius is the most sensitive species to copper, with a mean LC50 of 0.043 mg/L. In the spiked-sediment exposures, the order in decreasing sensitivity to copper is Hyalella = Hexagenia < Chironomus < Tubifex for survival and growth/reproduction. For cadmium, the order in decreasing sensitivity is Hyalella = Chironomus < Hexagenia < Tubifex, and for nickel is Hyalella << Hexagenia < Chironomus < Tubifex. Chironomus riparius and Hexagenia spp. survival can be used to distinguish between toxicity caused by different metals. Species test responses in field-collected sediment(Collingwood Harbour, ON, Canada) were examined in an attempt to determine the causative agent of toxicity throughout, using the established species sensitivities. Sediment toxicity was categorized first by comparing species responses to those established for a reference database. Test responses in the field-collected sediment do not support causality by Cu, a suspected toxicant based on comparison of sediment chemistry with sediment quality guidelines.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".