Arsenic bioaccumulation and biotransformation in aquatic organisms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Arsenic exists universally in freshwater and marine environments, threatening the survival of aquatic organisms and human health. To elucidate arsenic bioaccumulation and biotransformation processes in aquatic organisms, this review evaluates the dissolved uptake, dietary assimilation, biotransformation, and elimination of arsenic in aquatic organisms and discusses the major factors influencing these processes. Environmental factors such as phosphorus concentration, pH, salinity, and dissolved organic matter influence arsenic absorption from aquatic systems, whereas ingestion rate, gut passage time, and gut environment affect the assimilation of arsenic from foodstuffs. Arsenic bioaccumulation and biotransformation mechanisms differ depending on specific arsenic species and the involved aquatic organism. Although some enzymes engaged in arsenic biotransformation are known, deciphering the complicated synthesis and degradation pathway of arsenobetaine remains a challenge. The elimination of arsenic involves many processes, such as fecal excretion, renal elimination, molting, and reproductive processes. This review facilitates our understanding of the environmental behavior and biological fate of arsenic and contributes to regulation of the environmental risk posed by arsenic pollution.
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.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.001 |
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 it