Occurrence of Legionella in groundwater: an ecological study
Bibliographic record
Abstract
The natural habitat of Legionella is the water environment. Little is known about their presence in groundwater in spite of the fact that many millions around the globe regularly rely on groundwaters. This pilot study was aimed at evaluating the occurrence of Legionella in groundwater samples (water and biofilms) collected from various sites. Water and biofilm samples from selected groundwater sources were examined for Legionella using culture media (selective and non-selective) and a semi-nested PCR assay. Innovative approaches such as immunomagnetic separation (IMS) in combination with cultivation and flow cytometry were also evaluated. The findings available thus far show that (a) Legionella could be readily recovered from groundwater samples by cultivation even though their numbers showed considerable variations, (b) surprisingly, the PCR methodology was not yet as sensitive as cultivation and (c) flow cytometry was not directly applicable on natural samples because of debris and the high number of heterotrophic associated microflora from which some members were likely to cross-react with the monoclonal antibody used for separation procedures (IMS).
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 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".