Efficacy of a solar still in destroying virus and indicator bacteria in water for human consumption
Bibliographic record
Abstract
Abstract Natural water distillation can destroy and/or inactivate microorganisms that are sensitive to heat and ultraviolet radiation (UV). This method is currently used to provide fresh water in ships and in the desalination of brackish water. For the development of this research, a pilot-scale solar still was built and installed in the southern region of Brazil, in order to assess its efficiency in water disinfection, which was based on the most probable number (MPN) of total coliforms and Escherichia coli, in addition to the DNA copy number of human adenovirus type 5 (HAdV-5) in raw, undistilled samples and in treated distilled water. Results showed that the distillation process removed 100% of total coliform and Escherichia coli and 4.5 log (99.997%) of HAdV-5, which meets the microbiological standards for drinking water according to national Brazilian regulations, as well as USEPA and HEALTH CANADA requirements.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.008 |
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".