Effects of Continuous Copper Exposure and Calcium on the Olfactory Response of Fathead Minnows
Bibliographic record
Abstract
The current gill-based Biotic Ligand Model (gbBLM) is an acute-toxicity model used to predict site-specific safe copper (Cu) concentrations. Recent effort to develop a chronic BLM has focused on the olfactory epithelium. To further this effort, the current study looked at the effect of varying Cu concentration and exposure duration on Cu-induced olfactory dysfunction, and whether calcium (Ca) protected against Cu-induced impairment as it does at the gill. Fathead minnows (Pimephales promelas) were treated with five Cu concentrations for varying exposure durations in hard and soft water. A neurophysiological technique, electro-olfactography (EOG), was employed to determine the level of olfactory dysfunction. At the low, ecologically relevant Cu concentrations tested there was significant inhibition of EOG function; however, over time there was at least a partial recovery of olfactory function, despite the continuous Cu exposure. Calcium did not appear to protect against Cu-induced olfactory dysfunction; and even alone, Ca appeared to interfere with the olfactory response to the amino acid L-arginine. Safe copper concentrations as predicted by the gbBLM, chemosensory-based BLMs, the USEPA BLM, and hardness-adjustment equations based on the exposure waters were not entirely protective against olfactory dysfunction.
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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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".