An Introduction to Platelet Inventory and Ordering Problems
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
Abstract Platelets are blood cells that initiate the hemostatic plug that causes blood clot formation. Patients receiving intense chemotherapy or suffering massive bleeding complications require platelet transfusions for the prevention of a potentially fatal hemorrhage. A stable, readily available inventory of platelets is required for the safe and effective delivery of health care. Since platelets must be kept warm to remain viable, they are subject to bacterial contamination, and thus have a shelf life of between five and seven days. Since platelets have a very limited shelf life and are expensive to collect and produce, outdates are an important practical concern for hospitals and blood system operators. Thus, the platelet inventory problem revolves around identifying policies for ordering and holding platelets such that unit availability is maximized, while ensuring that outdates are minimized. In this paper we define the platelet inventory problem, survey the existing literature, and provide a discussion of solution approaches.
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.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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 it