Interaction of mercury and selenium in the larval stage zebrafish vertebrate model
Bibliographic record
Abstract
The compounds of mercury can be more toxic than those of any other non-radioactive heavy element. Despite this, environmental mercury pollution and human exposure to mercury are widespread, and are increasing. While the unusual ability of selenium to cancel the toxicity of mercury compounds has been known for nearly five decades, only recently have some aspects of the molecular mechanisms begun to be understood. We report herein a study of the interaction of mercury and selenium in the larval stage zebrafish, a model vertebrate system, using X-ray fluorescence imaging. Exposure of larval zebrafish to inorganic mercury shows nano-scale structures containing co-localized mercury and selenium. No such co-localization is seen with methylmercury exposure under similar conditions. Micro X-ray absorption spectra support the hypothesis that the co-localized deposits are most likely comprised of highly insoluble mixed chalcogenide HgSxSe(1-x) where x is 0.4-0.9, probably with the cubic zincblende structure.
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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) | 0.001 | 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".