Dissolved organic carbon modulates the effects of copper on olfactory-mediated behaviors of chinook salmon
Bibliographic record
Abstract
The modulation of Cu effects on olfactory-mediated behaviors by dissolved organic carbon (DOC) and Fe was examined in juvenile chinook salmon. Chinook were exposed to several concentrations of Cu, DOC, and Fe alone or in combination in a flow-through system for either 4 d (acute exposure) or 14 d (subchronic exposure) and tested for their ability to detect and avoid the odorant L-histidine in an avoidance/preference trough assay. In both acute and subchronic exposures, Cu inhibited the ability of fish to detect this amino acid in a concentration-dependent manner, and Cu toxicity (olfactory inhibition) decreased with increasing DOC concentration. In both acute and subchronic experiments including DOC, Cu-induced olfactory inhibition decreased in a linear fashion with increasing DOC concentration, although the modulation was lower in subchronic exposures. The protective effect of DOC on Cu olfactory inhibition was reduced only slightly in the presence of Fe, indicating that other metals can potentially affect the modulation of the olfactory inhibition of Cu through competition for DOC binding sites. The results of the present study clearly show the amelioration by DOC of the effects of Cu on juvenile chinook salmon olfaction at a behavioral level. These data further indicate that DOC concentrations should be considered when evaluating the potential impact of Cu on fish olfaction.
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 | 0.000 | 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".