Synthesis and characterization of metal sulfide clusters for toxicological studies
Bibliographic record
Abstract
Zinc sulfide clusters were synthesized and characterized at low micromolar concentrations to assess the effect of metal-sulfide ligands on metal toxicity to aquatic organisms in oxic environments. Recommended preparation times are greater than 2 h initial reaction of equimolar sodium sulfide and zinc nitrate, followed by oxic aeration for 3 d. Ionic strength, pH, and anoxic stabilization time were found to be relatively unimportant in controlling the final yield. Adsorptive losses of zinc sulfide (ZnS) clusters to surfaces, however, were significant for a variety of vessel materials and membrane filters. Ionic strength and pH were found to be important factors controlling the extent of adsorptive losses with minimal loss for pHs greater than 9 and for soft waters. The Ag(I), Cu(II), and Hg(II) as metal sulfides completely suppress the analysis of sulfide, whereas Pb(II), Mn(II), and Co(II) partially suppress the analysis of sulfide by the methylene blue technique. Ultraviolet and fluorescence spectra are shown for synthesized ZnS clusters.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".