Assessing the potential environmental factors affecting cladoceran assemblage composition in arsenic-contaminated lakes near abandoned silver mines
Bibliographic record
Abstract
Silver mining has a long history in Cobalt (Ontario, Canada), and it has left a complex environmental legacy where many lakes are contaminated with arsenic-rich mine tailings. In this exploratory survey, we examined subfossil Cladocera remains in the surface sediments of 22 lakes in the abandoned mining region to assess which environmental variables may be influencing the recent assemblage structure. Further, using a “top-bottom” paleolimnological approach, we compared the recent (top) and older (bottom) assemblages from a subset of 16 lakes to determine how cladoceran composition has changed in these lakes. Our regional survey suggests that the cladoceran assemblages in the Cobalt area are primarily structured by differences in lake depth, while site-specific limnological characteristics, including those related to past mining activities, may have limited roles in shaping the recent cladoceran compositions. The top-bottom paleolimnological analysis suggests that the cladoceran assemblages have changed in most lakes around Cobalt, however the magnitude and nature of changes varied across the study sites. As with most regional biological surveys, the responses to historical mining activities were not uniform across all sites, which further emphasizes the importance of considering site-specific limnological characteristics and multiple environmental stressors when assessing the impacts of mining pollution.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".