Field Evaluation of Long-Term Performance and Use of Biosand Filters in Posoltega, Nicaragua
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract An evaluation was conducted in 2007 on biosand filters that were installed in Posoltega, Nicaragua in 1999 and 2004.The objectives were to characterize the condition and use of filters eight and three years after installation, determine filter performance of those filters still in use, and identify determinants of successful long-term use and performance. Methods consisted of household identification, user questionnaires, and water quality testing. Of the 234 filters installed, only 24 were found to still be in use. Average log reductions were 1.73 (98%) for total coliforms, 1.36 (96%) for Escherichia Coli, and 0.91 (88%) for turbidity. Statistically significant effects were detected for the magnitude of the contamination of source water, the peak hydraulic loading rate, and the standing depth of water over the filter media. Questionnaire results indicated user training on filter maintenance could improve the peak hydraulic loading rate and hence filter performance. The low rate of sustained use (10%) is an indication of failed implementation, and is attributable to structural failure, particularly cracking of the concrete filters from 2004. Nonetheless, this evaluation demonstrated the biosand filter technology to be robust since those filters still in use were performing as expected three and eight years postimplementation.
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.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it