Heterotrophic plate counts (HPC) in drinking water distribution systems: A comprehensive review and meta-analysis
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
ABSTRACT Heterotrophic plate count (HPC) is widely assessed in drinking water distribution systems. However, methodological standards and guidelines on the use of HPC are not clearly defined. This comprehensive review and meta-analysis aim to evaluate HPC concentration and how they relate to the characteristics and operational conditions of systems. The size of the distribution system, use of chlorine or chloramine as secondary disinfection and the carbon content of the water were considered. Among 839 MEDLINE® records, 39 met our criteria and were included in the meta-analysis. Overall, wide ranges of HPC levels were observed in drinking water distribution systems. Results from the meta-analysis show a significant difference in concentrations between systems using chlorine or chloramine as secondary disinfectant and those that are not using any form of secondary disinfection. Similarly, results demonstrate a positive correlation between HPC levels and assimilable organic carbon. Assessing the spatial and temporal variations of HPC can provide useful information about the biological stability of the water and allow for routine analyses within individual drinking water systems. Due to its limitations as a global and unique indicator of water quality, HPC should be applied as part of a multi-parameter approach for microbial growth analysis in distribution networks.
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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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