Predicting the bioavailability of sediment-bound uranium to the freshwater midge (<i>Chironomus dilutus</i>) using physicochemical properties
Bibliographic record
Abstract
Abstract Assessment of uranium (U)-contaminated sediment is often hindered by the inability to accurately account for the physicochemical properties of sediment that modify U bioavailability. The present goal was to determine whether sediment-associated U bioavailability could be predicted over a wide range of conditions and sediment properties using simple regressions and a geochemical speciation model, the Windermere Humic Aqueous Model (WHAM7). Data from a U-contaminated field sediment bioaccumulation test, along with previously published bioaccumulation studies with U-spiked field and formulated sediments, were used to examine the models. Observed U concentrations in Chironomus dilutus larvae exposed to U-spiked and U-contaminated sediments correlated well (r2 &gt; 0.74, p &lt; 0.001) with the WHAM-calculated concentration of U bound to humic acid, indicating that humic acid may be a suitable surrogate for U binding sites (biotic ligands) in C. dilutus larvae. Subsequently, the concentration of U in C. dilutus was predicted with WHAM7 by numerically optimizing the equivalent mass of humic acid per gram of organism. The predicted concentrations of U in C. dilutus larvae exposed to U-spiked and U-contaminated field sediment compared well with the observed values, where one of the regression models provided a slightly better fit (mean absolute error = 18.1 mg U/kg dry wt) than WHAM7 (mean absolute error = 34.2 mg U/kg dry wt). The regression model provides a predictive capacity with a minimal number of variables, whereas WHAM7 provides additional complementary insight into the chemical variables influencing the speciation, sorption, and bioavailability of U in sediment. The present results indicate that physicochemical properties of sediment can be used to account for variability in U bioavailability as measured through bioaccumulation in chironomids exposed to U-contaminated sediments. Environ Toxicol Chem 2018;37:1146–1157. © 2017 SETAC
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".