Thermal inactivation analysis of water-related pathogens in domestic hot water systems
Bibliographic record
Abstract
This study aims to investigate whether hot water systems supplied with harvested rainwater present an increased risk to health over hot water systems supplied with potable mains water. It reviews previous studies investigating the health effects of utilising rainwater within domestic systems. The main risk to public health of mains-supplied hot water systems is the operation, maintenance, age, location and temperature of the system. Rainwater-harvesting systems contain an inherent water treatment train consisting of flocculation, settlement, sorption and bioreaction, and stored rainwater quality improves as metal and chemical contaminants settle to form sludge. Laboratory experiments were conducted using a variety of water-related bacteria to determine the time required to reduce a bacterial population by 90% at a given temperature. The results of this study show that after 5 min of exposure at 60 and 55°C, respectively, Salmonella, Pseudomonas aeruginosa and total viable count at 22 and 37°C concentrations were reduced to zero. Irish standards require hot water systems to be maintained at temperatures at or above 60°C. The conclusion from this pilot study is that hot water systems supplied with harvested rainwater do not present an increased risk to health over hot water systems fed with mains water.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".