Mechanisms of Nickel Toxicity in the Highly Sensitive Embryos of the Sea Urchin <i>Evechinus chloroticus</i>, and the Modifying Effects of Natural Organic Matter
Bibliographic record
Abstract
A 96 h toxicity test showed that the embryos of the New Zealand sea urchin (Evechinus chloroticus) are the most sensitive of all studied marine species to waterborne nickel (Ni), with the EC50 for the development of fully formed pluteus larvae found to be 14 μg L(-1). Failure to develop a standard larval shape suggested skeletal impairment. Whole body ions (Na, Mg) increased with Ni exposure and calcium influx was depressed. The effects of natural organic matter (NOM) on Ni accumulation and toxicity were also examined in three different seawater sources (nearshore, offshore, and near the outlet of a "brown water" stream). At low dissolved organic carbon (DOC) concentrations the brown water NOM was protective against Ni toxicity, however at higher DOC concentrations it exacerbated developmental toxicity in the presence of Ni. These results show that sea urchin development is highly sensitive to Ni via a mechanism that involves ionoregulatory disturbance, and that Ni toxicity is influenced by environmental factors such as NOM. These data will be critical for the development of water quality guidelines for Ni in the marine environment.
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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".