Silver uptake by the green alga <i>Chlamydomonas reinhardtii</i> in relation to chemical speciation: Influence of chloride
Bibliographic record
Abstract
Abstract Short-term (<1 h) silver uptake by the green alga Chlamydomonas reinhardtii was measured in the laboratory in defined inorganic media over a range of silver and chloride concentrations. For a low, fixed, free Ag+ concentration (e.g., 8 nM), silver uptake increases markedly (up to ∼4×) as a function of the chloride concentration (5 μM→4 mM Cl−); the free-ion model would have predicted a constant silver uptake rate. No evidence could be found for the passive diffusion of the neutral AgCl0 complex or for the facilitated uptake of the anionic AgCl−2 complex. The enhanced uptake observed in the presence of chloride is related to the very high silver uptake rates demonstrated by the test alga, which lead to diffusion limitation in the boundary layer surrounding the algal cell. In such a situation, metal accumulation is proportional to the total metal concentration (i.e., to the concentration gradient between the bulk solution and the algal surface). At higher silver concentrations (e.g., ≥ 10−7 M), diffusion in the phycosphere is no longer rate limiting, the chloride stimulation disappears, and silver uptake is sensitive to the free-ion concentration. However, such a high concentration of silver is not likely to be encountered in the environment, even in wastewater effluents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".