Determination of in situ polychlorinated biphenyl elimination rate coefficients in the freshwater mussel biomonitor <i>Elliptio complanata</i> deployed in the huron–erie corridor, southeast Michigan, USA, and southwest Ontario, Canada
Bibliographic record
Abstract
Quantitative mussel biomonitoring studies often use laboratory-measured whole-body elimination rate coefficients (k(tot) in conjunction with concentration data from field-deployed mussels to estimate bioavailable steady-state contaminant concentrations (C(m(ss)) in aquatic systems. However, the validity of applying laboratory k(tot) values to field-deployed mussels has not been verified. The present study quantified in situ k(tot) values by the common mussel biomonitor species Elliptio complanata for a group of performance reference compound polychlorinated biphenyl (PCB) congeners (International Union of Pure and Applied Chemistry 23, 61, 109, and 173) at 11 sites along the Lake Huron-Lake Erie corridor (southeast MI, USA, and southwest ON, Canada). Predictive site-specific k(tot) versus log K(ow) relationships were derived to estimate in situ k(tot) values for the bioaccumulated environmental PCB congeners, and the resultant steady-state concentration estimates were compared against values estimated using laboratory-derived k(tot) values. In situ k(tot) values were almost always faster (1.3-10-fold) than rate coefficients determined by laboratory studies, with a mean difference +/- standard error of 3.89 +/- 0.28-fold. Consequently, control adjusted steady-state concentrations of sum PCBs in the mussels were overestimated by factors ranging from 1.30 to 3.45 across sites when using laboratory-derived k(tot) values in place of in situ k(tot) values and a field deployment period of 90 d. This error was shown to increase with increasing congener hydrophobicity, as represented by their log K(ow) values, and when shorter field deployment times are performed. To more accurately predict the steady-state concentrations of environmentally accumulated PCBs in mussels, it is recommended that future quantitative biomonitoring studies employ the reference compound approach for measuring site-specific in situ k(tot) values.
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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 | 0.000 | 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".