GSK Vaccines NA RDC: Project rationale review and Key Performance Indicators selection
Bibliographic record
Abstract
GSK Vx is currently reviewing its distribution Network Strategy. The current distribution network is highly concentrated in Europe with direct shipments by air to the clients. The distribution center in Gembloux is responsible for 80% of the vaccines volume shipped to clients worldwide. This fragmented view and control of the distribution lead to a supply continuity and security risk. The new model will consist on the implementation of regional distribution centers to push the products closer to the markets. To implement the new model, a pilot project has been designed, the NA RDC. The project is to implement a distribution center in the US that will be responsible of supplying US, Canada and Mexico markets. For such a project to be endorsed, a presentation has been done to the higher management. The thesis will consist in the review of the business case that supported the management endorsement and the building of KPI associated to prove the project impact and benefits. The goal was to create a framework using literature from different fields. Vaccine distribution network and performance literature combined with decentralized vs decentralized literature has been used to create a list of attention points regarding vaccine decentralized distribution. The SCOR and SMART models have been used to ensure the quality and strategic relevance of the KPI that were built. The outcome was a list of KPI based on the review of the business case that the author conducted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.162 | 0.210 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.018 | 0.013 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.012 |
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".