Detoxification Efforts in Longnose Dace (<i>Rhinichthys cataractae</i>) Exposed to Municipal and Agricultural Inputs
Bibliographic record
Abstract
Ecological impacts of contaminants on population patterns in wild fish are impacted by many contaminants that readily enter aquatic systems. Responses to toxicants by individuals in lab studies generally do not predict population level consequences in natural systems. Trace levels of contaminants are present in all major rivers in southern Alberta, Canada, with concentrations higher down-stream of anthropogenic inputs like agricultural land-use and inputs of municipal wastewater effluents. Longnose dace (Rhinichthys cataractae) were used as a sentinel species to study field-based population-level responses to contaminants. We hypothesized that biomarker activity, triggered by contaminant exposure, should increase downstream of anthropogenic inputs in two southern Alberta rivers, with corresponding relations between biomarker activity and sex ratios, after accounting for age structure. Liver detoxification (ethoxyresorufin-O-deethylase activity = EROD) measured at reference and exposed sites on each river differed significantly in only the Bow River system. Sex ratios varied more downstream of anthropogenic inputs than upstream, but the direction of sex ratio bias was inconsistent and temporally dynamic. Sex ratios correlated with liver detoxification in only the Bow River. Taken together, these results suggest that contaminants alter sex ratios in long-nose dace, but that there is variation in anthropogenic stressors among rivers.
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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".