Actinomycetes in the Elbow River Basin, Alberta, Canada
Bibliographic record
Abstract
Abstract Actinomycetes can produce significant amounts of the earthy-muddy odour compounds geosmin and 2-methylisoborneol (MIB). These filamentous bacteria are found in both terrestrial and aquatic environments, and are particularly abundant in soil. They can enter freshwater systems via terrestrial runoff and subsequently cause taste and odour outbreaks in drinking water. Since it is well known that actinomycete growth and odour production is modified strongly by environmental factors such as moisture and nutrient levels, we hypothesized that watershed and stream characteristics should influence the potential odour impact of soil runoff on surface water. In this study, 1) the relationship between actinomycete abundance and characteristics such as stream discharge, turbidity and Escherichia coli levels was investigated, and 2) actinomycetes from contrasting terrestrial sources were examined for differences in their geosmin and MIB production. Actinomycetes and stream characteristics were sampled from the Elbow River, an important drinking water source for the City of Calgary (Alberta, Canada), and three tributary streams. Actinomycetes from forested regions and agricultural land were tested for taste and odour compound production. Actinomycete levels in streams were found to correlate closely with E. coli levels and to a lesser extent with turbidity, suggesting that actinomycetes are particularly abundant in runoff from terrestrial sources with fecal contamination. Most of the 18 actinomycete isolates tested were able to produce geosmin and/or MIB regardless of their terrestrial sources, suggesting that taste and odour outbreaks due to actinomycetes may be more influenced by differences in abundance than differences in source.
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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 | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 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".