DETECTION AND IDENTIFICATION OF<i>Legionella</i>SPECIES FROM GROUNDWATERS
Bibliographic record
Abstract
Legionellae are opportunistic bacterial pathogens causing Legionnaires' disease and Pontiac fever and are ubiquitous in surface waters and in infrastructure to contain or distribute water, including pipes, cooling towers, and whirlpool spas. Infection in community-acquired and nosocomial outbreaks is by exposure to contaminated aerosols. Little is known about the presence of legionellae in groundwater. This study used samples from various locations in the United States and Canada to determine if legionellae could be isolated from water and biofilms derived from groundwaters not known to be under the direct influence of surface water. Of the 114 total samples of water and biofilm tested, 29.1% and 28.2% were positive for Legionella by cultivation and polymerase chain reaction (PCR), respectively. Legionellae were found in both warm and colder groundwaters, with more isolates from samples incubated at 30 degrees C than the 35 degrees C conventional temperature for Legionella isolation. The concentration of Legionella found in the water samples ranged from 10(2) to 10(5) CFU/L and up to 1.2 x 10(2) CFU/cm(2) in the biofilm. The species of Legionella identified included both known pathogenic species and species that have not yet been identified as human pathogens. Millions of people in Canada, and around the world, rely on groundwater as their source for drinking. This study shows that legionellae are widespread in groundwater and have the potential to seed derived water supplies and biofilms in public distribution systems. This further widens the known sphere of Legionella colonization and the implications of its presence for public health.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".