Development of an accessible analytical model for small-volume feces composting
Bibliographic record
Abstract
ABSTRACT Developing small-volume composting systems can help improve sustainable sanitation and waste management at a household scale in constrained environments. In this work, an accessible analytical model that describes the container-based composting process is presented. The model focuses on the compost temperature as the main process parameter and was validated with an initial experiment and then used as a simulation tool for scaling a compost reactor with a mixture of feces and sawdust commonly found in dry toilets. Following literature thresholds for pathogen inactivation, the compost in the second experiment surpassed the required temperatures of 55 °C for more than 3 days. This work demonstrates that pathogen-inactivation temperatures can be achieved for a self-heating, container-based compost system at a household scale with a minimal experimental setup. Furthermore, the process can be described with an accessible analytical model that ensures ease of replication even in constrained environments.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".