Production planning for medical devices with an uncertain regulatory approval date
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
The demand for medical devices such as pacemakers, defibrillators, catheters and heart valves is growing rapidly throughout the world. This demand is driven by both the “technology push” of new medical device technologies and the “demand pull” of an aging population in North America, Western Europe, and Japan. Production planning for these products is increasing in importance as demand increases, global competition intensifies and product lifecycles shorten. In all developed countries, medical devices must pass through a government approval process. An uncertain government approval date makes it difficult to create production and inventory plans for both the phase-out of an existing product and the phase-in of a replacement product. This paper presents a mathematical model for finding the optimal dates to stop production of an existing product and to start production of a new product in the presence of an uncertain approval date. The paper also presents an example and reports on an implementation in a Fortune 500 medical device firm.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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