Study design and methods of the Wells and Enteric disease Transmission (WET) Trial: a randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: The burden of disease attributed to drinking water from private wells is not well characterised. The Wells and Enteric disease Transmission trial is the first randomised controlled trial to estimate the burden of disease that can be attributed to the consumption of untreated private well water. To estimate the attributable incidence of gastrointestinal illness (GI) associated with private well water, we will test if the household treatment of well water by ultraviolet light (active UV device) versus sham (inactive UV device) decreases the incidence of GI in children under 5 years of age. METHODS AND ANALYSIS: The trial will enrol (on a rolling basis) 908 families in Pennsylvania, USA, that rely on private wells and have a child 3 years old or younger. Participating families are randomised to either an active whole-house UV device or a sham device. During follow-up, families will respond to weekly text messages to report the presence of signs and symptoms of gastrointestinal or respiratory illness and will be directed to an illness questionnaire when signs/symptoms are present. These data will be used to compare the incidence of waterborne illness between the two study groups. A randomly selected subcohort submits untreated well water samples and biological specimens (stool and saliva) from the participating child in both the presence and absence of signs/symptoms. Samples are analysed for the presence of common waterborne pathogens (stool and water) or immunoconversion to these pathogens (saliva). ETHICS: Approval has been obtained from Temple University's Institutional Review Board (Protocol 25665). The results of the trial will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04826991.
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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 | 0.023 | 0.029 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.050 | 0.007 |
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".