Case Study of Particle-Related UV Shielding of Microorganisms When Disinfecting Unfiltered Surface Water
Bibliographic record
Abstract
Abstract The goal of this case study was to provide pilot-scale information about the ability of ultraviolet (UV) light to disinfect unfiltered surface water. A pilot-scale (0.25 L/s) UV reactor with low-pressure UV lamps was installed on raw water entering an aqueduct from the Pardee Reservoir at the East Bay Municipal District, California. A pilot monitoring system also collected hourly particle count (2 to 100 m), turbidity, and ultraviolet transmittance (UVT) measurements for 14 months. Grab microbial samples were collected and analyzed for indigenous total coliforms and total aerobic spores (TAS) both before and after UV disinfection, to correlate survival of the organisms across the UV reactor to water quality characteristics. Concentrations of indigenous coliforms and TAS ranged up to 163 and 1,383 per 100 mL respectively, before UV exposure. The data showed that the ability of UV to disinfect coliforms was essentially unaffected by the presence of particles (up to 703>10 m per mL and 1.3 nephelometric turbidity unit [NTU]) in the unfiltered surface water. In 13 of 14 samples, no coliforms were detected in the UV treated water. Log-linear inactivation of TAS up to 2.5-log suggests that at least 99.6% of the TAS were not protected from UV disinfection by particles.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".