Optimizing Automated Insulin Delivery Systems for Pregnancy
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
Automated insulin delivery (AID) systems have revolutionized modern diabetes care outside of pregnancy, but none of the AID systems currently available in the U.S. are approved for use during pregnancy, none have glucose targets low enough to achieve the stricter fasting glucose targets recommended during pregnancy, and none have algorithms that were designed to respond to the amplified oscillations in glycemia that occur in pregnancy or the progressive changes in insulin resistance observed over the course of gestation. Despite these limitations, many women elect to continue using AID off label during pregnancy based on consideration of individual clinical factors and preferences. This article presents some commonly encountered challenges to off-label AID use and CGM interpretation during pregnancy, along with suggested best-practice workarounds to optimize the care of pregnant individuals with diabetes using AID.
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 | 0.000 |
| 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