Economic feasibility analysis of a medical mask closed-loop supply chain: A Canadian case study
Bibliographic record
Abstract
The world is being exposed to a global health crisis due to covid-19. This situation is generating an unprecedented \nincrease in the use of single-use medical materials, notably procedural facemasks. This study focuses on the design and \nplanning of a closed-loop supply chain (SC) for dealing with end-of-life procedural facemasks. An optimization model to \nefficiently collect and recycle used procedural facemasks is proposed. The main benefits are the correct disposal of \ncontaminated products and component recycling. The considered SC network includes virgin raw material, suppliers, \nfacemask manufacturing centers, warehouses, distribution centers, business clients, collection centers, dismantling and \nrecycling centers, and finally, clients for the recycled components. Decisions to be made include material flows in the \nnetwork, supplier and facility (collection and recycling centers) selection in order to maximize the profit of the SC. A realistic \ncase study is created based on real data gathered from different industrial partners in the Montreal region. Various \nscenarios are analyzed to identify the conditions under which the SC is profitable.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".