Determination of the speciation and bioavailability of samarium to <i>Chlamydomonas reinhardtii</i> in the presence of natural organic matter
Bibliographic record
Abstract
Abstract As technological interest and environmental emissions of the rare earth elements increase, it is becoming more important to assess their potential environmental impact. Samarium (Sm) is a lanthanide of intermediate molar mass that is used in numerous high-technology applications including wind turbines, solar panels, and electric vehicles. The present study relates the speciation of Sm determined in the presence of natural organic matter (NOM) to its bioavailability to the unicellular green alga Chlamydomonas reinhardtii. The free ion concentration was determined using a cation exchange resin (ion exchange technique) in dynamic mode and compared with thermodynamic modeling. Short-term biouptake experiments were performed in the presence of 4 types of NOM: Suwannee River fulvic acids, Pahokee Peat fulvic acids, Suwannee River humic acids, and a Luther Marsh dissolved organic matter isolate (90–95% humic acids). It was clearly shown that even a small amount of NOM (0.5 mg C L−1) resulted in a significant decrease (10 times) in the Sm internalization fluxes. Furthermore, complexation with humic acids (and the corresponding reduction in Sm bioavailability) was stronger than that with fulvic acids. The results showed that the experimentally measured (free) Sm was a better predictor of Sm internalization than either the total concentrations or the free ion concentrations obtained using thermodynamic modeling. Environ Toxicol Chem 2018;37:1623–1631. © 2018 SETAC
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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".