Reverse Supply Chain and Pharmaceutical Waste Collection Management Utilizing Location-Routing Model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Nowadays, the increased amount and variety of waste, and the health risks caused by them are considered among the substantial issues of human societies today. Pharmaceutical wastes are among the most dangerous polluting wastes of the environment in the world. They include expired products and unused medicines. This study aims to investigate pharmaceutical waste collection management utilizing the location-routing model in a reverse supply chain. To do so, pharmaceutical waste from pharmacies and hospitals is collected and then transfer to collection centers, where waste classification and future decisions are planned. This process is done in two stages, the first includes pharmacies and hospitals, and collection centers, and the second stage includes collection centers, disposal centers, and airports. In the first stage, pharmaceutical waste is collected, and in the second level, this waste is either safely disposed of or recycled, or medicines that can be reused are sent to third-world countries. Finally, by creating an optimization model, the transportation costs, the construction cost of collection centers, disposal costs, and the cost of producing carbon dioxide will be minimized. Reducing carbon dioxide production helps make this chain greener.
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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 | 0.001 |
| 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 it