Physico-Chemical Characteristics of MSWs into Incinerators Before and After the COVID19 Pandemic
Bibliographic record
Abstract
For 8 years before and after COVID19 in H-gun, a small and medium-sized rural city, a quarterly survey and analysis was conducted on changes in physical and chemical characteristics of domestic waste brought into the domestic waste incinerator input. Apparent density, three-component, and elemental analysis were performed, and based on this, the calorific value of waste to be recycled was calculated. Through this, the following results were obtained about the characteristics of household waste generation in rural small and medium-sized cities before and after the COVID19 pandemic. First, since the COVID19 pandemic in the fourth quarter of 2019, the content of plastics and fibers has increased relatively, and this reason is judged to be the result of the increase in the use of plastic packaging materials and masks. Second, in the case of moisture content and combustible content before and after COVID19, a decrease in moisture content and an increase in combustible content were evident overall, except for the quarter of a specific year. Third, comparing the low calorific value before and after COVID19, it was higher than about 3,000 kcal/kg from the fourth quarter of 2019, except for 2016, after the COVID19 pandemic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".