State of the marine environment at Little Bay Arm, Newfoundland and Labrador, Canada, 10 years after a “do nothing” response to a mine tailings spill
Bibliographic record
Abstract
In 1989, the tailings pond dam at the site of a former copper mine near Little Bay, Newfoundland and Labrador, Canada, ruptured and tailings spilled into Little Bay Arm. At the time, no action was taken to arrest the flow of tailings or to mitigate the effects of the spill. To date, no action has been taken to repair the dam and tailings continue to flow into Little Bay Arm. As a result, the marine environment around Little Bay Arm has become contaminated with heavy metals from the tailings. However, the tailings are not the only source of heavy metals to the ecosystem. An old slag heap and what is presumably concentrated copper ore spilled during the loading of ore freighters, are also contributing to the ecosystem's metal load. Marine sediment throughout the Arm contained elevated concentrations of Cu, Ni, Zn, As, V, Co, and Mn. Beach material also contained elevated concentrations of metals with material near the slag heap being the most contaminated. At this site, Cu concentrations were in excess of 5000 mg kg(-1) dry weight, Zn greater than 3000 mg kg(-1) and Co concentrations exceeded 700 mg kg(-1). The highest concentrations of metals in biota were found near the slag heap, near the tailings dam breach, and at the site of the former concentrate loading dock. Despite elevated metal concentrations, the tailings and nearby sediment were not devoid of life. Bivalves and seaweed were abundant in the area and there were no obvious signs of tissue damage or disease in soft shell clams (Mya arenaria) living in the tailings. These clams may be suffering from chronic exposure to the tailings, however, evidence of lipid peroxidation in the clams was inconclusive.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".