Freshwater Diatoms as Indicators of Combined Long-Term Mining and Urban Stressors in Junction Creek (Ontario, Canada)
Bibliographic record
Abstract
Sudbury (Ontario, Canada) has a long mining history that has left the region with a distinctive legacy of environmental impacts. Several actions have been undertaken since the 1970s to rehabilitate this deteriorated environment, in both terrestrial and aquatic ecosystems. Despite a marked increase in environmental health, we show that the Junction Creek system remains under multiple stressors from present and past mining operations, and from urban-related pressures such as municipal wastewater treatment plants, golf courses and stormwater runoff. Water samples have elevated metal concentrations, with values reaching up to 1 mg·L−1 Ni, 40 μg·L−1 Zn, and 0.5 μg·L−1 Cd. The responses of diatoms to stressors were observed at the assemblage level (metal tolerant species, nutrient-loving species), and at the individual level through the presence of teratologies (abnormal diatom frustules). The cumulative criterion unit (CCU) approach was used as a proxy for metal toxicity to aquatic life and suggested elevated potential for toxicity at certain sites. Diatom teratologies were significantly less frequent at sites with CCU values <1, suggesting “background” metal concentrations as compared to sites with higher CCU values. The highest percentages of teratologies were observed at sites presenting multiple types of environmental pressures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".