Ceramic Water Filters as a Response Technology to Geo-Hazards
Bibliographic record
Abstract
Geo-hazards, a collective term for earthquakes, floods, windstorms, famine and drought, are intensifying with time and are obstacles to attainment of sustainable development. In particular, issues of availability of safe water are major disruptive elements causing the spread of diarrheal diseases during, and post, these geo-hazard events. Given that ceramic water filters (CWFs) have been shown to effectively remove E.-coli (and, by similar attributes, is effective in the removal of cholera), CWFs as a Point-of-Use (POU) technology are described as an effective option for the post-disaster phase of geo-hazards. As described herein, important dimensions of CWFs are provided, showing they can be stored effectively without suffering deterioration, are inexpensive, and are an easy technology to explain to users. Pertinent rationale for serious consideration of CWFs as a post-disaster POU is provided.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".