COMMON TERMS USED IN DRINKING WATER GUIDELINES MAY BE AN IMPEDIMENT FOR RADIOLOGICAL PROTECTION
Bibliographic record
Abstract
Clean water is essential to life as health and well-being depend on it. Around the world, many countries and territories as well as various international organisations have established drinking water guidelines as benchmarks for water quality. Guidelines make it possible for drinking water to be tested at various points along its journey from the source of water to the consumer's tap to determine whether it is safe to drink. Guideline values are often seen as a reference point. The World Health Organization (WHO) Guidelines for Drinking-Water Quality(1) are often used as the international reference for the establishment of national or regional regulations and standards for water safety. The WHO drinking water guidelines address microbial, chemical, radiological as well as aesthetic parameters to cover all aspects of water quality. Infectious diseases caused by pathogenic bacteria, viruses, protozoa and helminths are the most common and widespread health risk associated with drinking water. Pathogens can cause acute and also chronic health effects, and, in some cases, exposure to a single organism may be enough to cause an illness. Chemical contaminants may cause adverse health effects as a consequence of prolonged (long-term) exposure. In terms of health risk assessment for radionuclides, the radiation dose criterion established in the guidelines is only a small fraction (typically <5 %) of the background radiation level people are exposed to naturally, and only long-term exposure to radiological contaminants at elevated levels (significantly higher than normal background radiation levels) could lead to a detectable increase in the risk of developing cancer. The carcinogenic risks presented by radionuclides in drinking water are of a stochastic nature and can only be observed at a population level after long-term exposure to elevated concentrations in the environment (for non-emergency situations).
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 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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".