Meeting the Pharmaceutical Shipping Needs in the Pee Dee Health Region
Bibliographic record
Abstract
reorganized in 2013. One of the many monumental changes that occurred in the reorganization was the reduction of the agency from eight public health regions to the current four- Pee Dee, Low Country, Upstate, and Midlands. These four regions provide public health services to South Carolina citizens through the many health department clinics located in each county in the State. Each new region now covers about one quarter of the state, presenting considerable challenges in operational coverage of such a vast geographic area. Problem Statement As the chief procurement officer for the Pee Dee Health Region, it is my responsibility to ensure that staff in the region has the supplies and services needed to perform their jobs. Since the former Public Health Region 6 expanded in the reorganization from three counties to twelve, procurement operations as a whole have undergone dramatic and sweeping changes, and continue to evolve almost daily. Due to the urgency involved, this project will focus primarily on providing essential pharmaceutical supplies to eighteen widely scattered health departments located throughout the Pee Dee Region. In the new DHEC operational structure, each region has one central pharmacy. All
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".