Protection of waterborne pathogens by higher organisms in drinking water: a review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Higher organisms are ubiquitous in surface waters, and some species can proliferate in granular filters of water treatment plants and colonize distribution systems. Meanwhile, some waterborne pathogens are known to maintain viability inside amoebae or nematodes. The well-documented case of Legionella replication within amoebae is only one example of a bacterial pathogen that can be amplified inside the vacuoles of protozoa and then benefit from the protection of a resistant structure that favours its transport and persistence through water systems. Yet the role of most zooplankton organisms (rotifers, copepods, cladocerans) in pathogen transmission through drinking water remains poorly understood, since their capacity to digest waterborne pathogens has not been well characterized to date. This review aims at (i) evaluating the scientific observations of diverse associations between superior organisms and pathogenic microorganisms in a drinking water perspective and (ii) identifying the missing data that impede the establishment of cause-and-effect relationships that would permit a better appreciation of the sanitary risk arising from such associations. Additional studies are needed to (i) document the occurrence of invertebrate-associated pathogens in relevant field conditions, such as distribution systems; (ii) assess the fate of microorganisms ingested by higher organisms in terms of viability and (or) infectivity; and (iii) study the impact of internalization by zooplankton on pathogen resistance to water disinfection processes, including advanced treatments such as UV disinfection.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it