Do aluminium concentrations in drinking water inhibit cultivation of Escherichia coli?
Bibliographic record
Abstract
In spite of reliance on Escherichia coli as an indicator of fecal pollution in water resources, including potable water, relatively little is known of its ecology and persistence. It is particularly important to be able to accurately detect E. coli presence and quantity in treated potable water because of potential human health effects from consumption of contaminated water. Presence of even a single E. coli in potable water can lead to significant consequences and costs for water utilities. Alum is frequently used as a coagulant in conventionally treated water, and is usually present in slight excess after treatment. We show here that E. coli can accumulate the Al3 + ions present at natural levels in potable water and in so doing become uncultivable. Thus, E. coli, and perhaps a number of other bacteria, present in potable water could readily escape detection on laboratory culture media. Chelation with Tiron of the Al3 + prior to exposure maintained the E. coli in a cultivable state. This phenomenon deserves further investigation in view of the reliance placed on E. coli as an indicator of fecal contamination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".