The role of complexation and competition in the biouptake of europium by a unicellular alga
Bibliographic record
Abstract
Short-term (60 min) europium (Eu) biouptake fluxes by the freshwater green alga Chlamydomonas reinhardtii were investigated in the presence and absence of ligands (e.g., malic acid and citric acid) and a second rare earth metal, samarium (Sm). Data were interpreted in the context of the biotic ligand model, which uses experimentally determined stability constants to take into account the competition and complexation of the metal of interest. In the absence of ligands or competitors, Eu biouptake was well described by a Michaelis-Menten equation with the maximal uptake flux (Jmax ) and Michaelis-Menten constant (Km ) of Jmax = 1.7 × 10(-14) mol cm(-2) s(-1) and Km = 10(-7.0) M (corresponding to an affinity constant of 10(7.0) M(-1) ). Biouptake of Eu (or Sm) decreased as the concentration of a competing rare earth element (i.e., Sm or Eu) increased, as predicted by the biotic ligand model. On the other hand, when hydrophilic complexes were formed with citric and malic acid, Eu biouptake was much greater than predicted on the basis of free ion concentrations alone. Overall, the results showed that for C. reinhardtii the rare earth elements were likely to share a common biouptake pathway; biouptake of one rare earth element was reduced when another was present, and rare earth element complexes were bioavailable.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".