Household, hotel and market waste audits for composting in Vietnam and Laos
Bibliographic record
Abstract
In Da Nang and Ha Long, Vietnam and in Vientiane, Laos, there was interest by local authorities in separating and composting waste in order to reduce environmental and health problems at the local landfills and to produce a soil conditioner for local agricultural use. To assist in the planning of composting projects, three studies were carried out to estimate waste quantities and composition. 1. A 9-day audit of waste from 45 vendors in a market in Vientiane, the capital of Laos. The total quantity of waste and the quantity in each of nine categories were estimated for each of six different types of vendors. 2. A 7-day audit of waste disposed by three hotels in the tourist area of Ha Long, Vietnam. Waste quantities were estimated in total, on a per guest basis, and in three main categories: compostables, recyclables and miscellaneous. 3. A 7-day audit of waste collected from 74 households in Da Nang, the fourth largest city in Vietnam. Waste from each household was separated into compostable and non-compostable waste. Over 60% of each waste source comprised compostable waste and this was considered significant enough to warrant further planning of composting operations.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".