Anadromous fish as biomarkers for the combined impact of marine and freshwater heavy metal pollution
Bibliographic record
Abstract
Rivers along the eastern seaboard of the United States and Canada are becoming increasingly contaminated with heavy metals. This includes the Tusket River (Nova Scotia, Canada) which empties into the Gulf of Maine, near the Bay of Fundy. Whether anadromous fish such as alewife (Alosa pseudoharengus), exposed both to marine and freshwater contaminants, are accumulating these heavy metals and experiencing any changes in their morphology was explored in this study. Adult (4-6 years of age) Tusket River alewife (n = 38) were harvested and had external examinations including morphometrics (fork length, weight). Biopsies were taken and structural abnormalities noted. Morphometric data was compared to historical alewife reference data from 1985. Biopsies of muscle, liver and kidney had heavy metal profiles assessed. Major findings of this study include detectable levels (µg/g wet weight) of a number of heavy metals and concerning maximum concentrations achieved of arsenic (liver: 14 µg/g), cadmium (kidney: 2.6 µg/g), mercury (liver: 0.26 µg/g), magnesium (muscle: 460 µg/g), selenium (kidney: 4.0 µg/g) and zinc (liver: 38.0 µg/g). As well, reduced body weight for length and in 87% of fish, presence of spine curvatures (3-24°) not visible externally were noted. This study is the first detailed report in alewife of key tissue heavy metals, some at levels of concern, reductions in weight for length and spine abnormalities. These findings validate concerns regarding potential impacts of deteriorating conditions of rivers and their surrounding waters such as the Gulf of Maine on anadromous fish species.
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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 | 0.001 | 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".