Investigation into microbial methymercury production in Kejimkujik National Park, Nova Scotia, Canada
Bibliographic record
Abstract
In the mid 1990's, it was noticed that the loon population in Kejimkujik National Park was decreasing. Subsequent research determined that the loons had high levels of methylmercury, which was affecting their behavior and reproduction. It has been reported that the amount of methylmercury in biota in Kejimkujik National Park is at levels considered unsafe to wildlife. In order to ascertain the importance of sulfate- reducing bacteria to mercury methylation in Kejimkujik National Park, we studied Big Dam East and Big Dam West lakes and Thomas Meadow Brook, which runs into Big Dam West. The aim of this study was to first of all determine the bacterial productivity of these watersheds and then try and ascertain the amount of bioavailable mercury present using bioluminescent sensors. Finally, the most probable number (MPN) technique was used in order to estimate the number of sulfate-reducing bacteria in the water and sediment. The microbial productivity of the system was within normal ranges for these types of lakes. Test results of mud from Thomas Meadow Brook show a high rate of mercury methylation and methane formation, while peat samples from Thomas Meadow Brook show very little mercury methylation and methane formation. The results from the biosensors and the MPN were inconclusive.
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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".