Assessment of Healthcare Waste Management Practices at Seti Provincial Hospital, Nepal
Bibliographic record
Abstract
Globally, healthcare waste (HCW) is recognized as the second most hazardous type of waste after radioactive materials. Improper management of HCW poses significant risks to healthcare workers, patients, surrounding communities, and the environment. This study aims to assess the current status of HCW generation and management at Seti Provincial Hospital in Nepal. Conducted over a 15-day period, the study evaluated the quantity and handling practices of HCW within the hospital. The waste collected was categorized into hazardous and non-hazardous types. The average HCW generation rate was found to be 0.55 kg per patient per day, with 65.98% classified as non-hazardous and 34.02% as hazardous. Findings indicate that the hospital's HCW management practices require significant improvement. To ensure sustainable and safe waste handling, the adoption of scientifically sound and environmentally responsible methods for segregation, collection, transportation, storage, and disposal is strongly recommended.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".