Bibliographic record
Abstract
Abstract Water utilities around the globe strive to provide safe and reliable drinking water supplies to the public. Based on human health and aesthetic considerations, various water quality parameters have been developed by the World Health Organization (WHO) for effective water quality monitoring and communication. The water quality parameters are listed in the Guidelines for Drinking‐water Quality, providing references to water regulatory authorities in developing water guidelines/standards that fit local circumstances. Water quality parameters can generally be divided into four aspects, including chemical, biological, radiological, and acceptability parameters. Water quality failure in water distribution systems (WDSs) can pose great threats to human health since a WDS in many cases is the last barrier providing water quality protection. In WDSs, five important pathways, including contaminant intrusion, leaching and corrosion, permeation, biofilm formation and microbial regrowth, and the formation of disinfectant byproducts (DBPs), are responsible for water quality failure. A water quality management system (WQMS) comprises operational protocols and communication mechanisms and is required as guidance on effective water quality management. A WQMS standard has also been recommended by the WHO to assist water supply stakeholders in developing localized water quality management frameworks to minimize the risk of water quality failure.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.072 | 0.012 |
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".