Toxicity of sediments from lead–zinc mining areas to juvenile freshwater mussels (<i>Lampsilis siliquoidea</i>) compared to standard test organisms
Bibliographic record
Abstract
Sediment toxicity tests compared chronic effects on survival, growth, and biomass of juvenile freshwater mussels (28-d exposures with Lampsilis siliquoidea) to the responses of standard test organisms-amphipods (28-d exposures with Hyalella azteca) and midges (10-d exposures with Chironomus dilutus)-in sediments from 2 lead-zinc mining areas: the Tri-State Mining District and Southeast Missouri Mining District. Mussel tests were conducted in sediments sieved to <0.25 mm to facilitate recovery of juvenile mussels (2-4 mo old). Sediments were contaminated primarily with lead, zinc, and cadmium, with greater zinc and cadmium concentrations in Tri-State sediments and greater lead concentrations in southeast Missouri sediments. The frequency of highly toxic responses (reduced 10% or more relative to reference sites) in Tri-State sediments was greatest for amphipod survival (25% of samples), midge biomass (20%), and mussel survival (14%). In southeast Missouri sediments, the frequency of highly toxic samples was greatest for mussel biomass (25%) and amphipod biomass (13%). Thresholds for metal toxicity to mussels, expressed as hazard quotients based on probable effect concentrations, were lower for southeast Missouri sediments than for Tri-State sediments. Southeast Missouri sites with toxic sediments had 2 or fewer live mussel taxa in a concurrent mussel population survey, compared with 7 to 26 taxa at reference sites. These results demonstrate that sediment toxicity tests with juvenile mussels can be conducted reliably by modifying existing standard methods; that the sensitivity of mussels to metals can be similar to or greater than standard test organisms; and that responses of mussels in laboratory toxicity tests are consistent with effects on wild mussel populations.
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 | 0.000 | 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".