Sensory and Behavioral Responses of a Model Fish to Oil Sands Process-Affected Water with and without Treatment
Bibliographic record
Abstract
If oil sands process-affected water (OSPW) is to be returned to the environment, a desire is that it not adversely affect aquatic life. We investigated whether a relevant model fish (rainbow trout, Oncorhynchus mykiss) could detect OSPW using its olfactory sense (smell) and whether exposure to it would result in behavioral changes. We also investigated whether ozonation of OSPW, which lowers the concentration of organic compounds attributed with toxicity (naphthenic acids), would ameliorate any observed adverse effects. We found that OSPW, regardless of ozonation, evoked olfactory tissue responses similar to those expected of natural odorants, suggesting that fish could smell OSPW. In 30 min OSPW exposures, olfactory responses to a food odorant and a pheromone were reduced to a similar degree by OSPW, again regardless of ozonation. However, olfactory responses returned within minutes of exposure cessation. In contrast, in longer (7 d) exposures, olfactory responses remained impaired, but not in fish that had received ozone-treated OSPW. In the behavioral assay, fish avoided an introduced plume of OSPW, and this response was not affected by ozonation. Taken together, our data suggest that fish smell OSPW, that they may use this sense to mount an avoidance response, and that, if they cannot avoid it, their sensory responses may be impaired, unless the OSPW has received some remediation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".