Influence of sediment metal spiking procedures on copper bioavailability and toxicity in the estuarine bivalve<i>Indoaustriella lamprelli</i>
Bibliographic record
Abstract
The effect of three methods for spiking sediments with Cu on the reburial behavior, mortality, and tissue Cu accumulation of a lucinid bivalve (Indoaustriella lamprelli) and the influence of the bivalve on the sediment geochemistry were investigated. Methods used to create Cu concentration gradients were direct spiking with and without pH adjustment to pH 7 and also dilution of sediment, previously spiked with Cu and adjusted to pH 7, using a low-Cu sediment (known to produce the lowest pore-water Cu concentrations). The presence of the bivalve within Cu-spiked sediment increased the flux of Cu and Mn to overlying waters at high Cu concentrations (550 microg/g). Bivalve behavioral response, metal accumulation, and mortality varied with the method by which Cu was spiked. In direct Cu-spiked sediment, the bivalves were inactive at concentrations of 550 and 1,100 microg/g, with mortality induced in sediment spiked with 1,100 microg/g (pH 6.5-7.1). Complete bivalve inactivity was observed only at 1,100 microg/g in direct Cu-spiked sediment with pH adjustment, whereas percentage reburial was reduced to 30% at 1,100 microg/g for sediment prepared by the dilution method. Relative reburial rates in the three spiked sediment types (direct << direct pH-7 < dilution) were proportional to dissolved Cu concentrations in the overlying water. Bivalve reburial, in addition to the method of Cu addition, affected tissue Cu accumulation. Inhibition of bivalve reburial decreased the amount of accumulated Cu, confounding relationships between tissue Cu and pore water, overlying water, or extractable metal fractions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.000 | 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".