Puzzling About Partial Glucagon Responses to Hypoglycemia in Intrahepatic Islet Recipients: Missing Pieces
Bibliographic record
Abstract
Fifteen years ago, Shapiro et al. (1), at the University of Alberta in Edmonton, Canada, published an article in the New England Journal of Medicine that caused great excitement. They reported that seven consecutive recipients with type 1 diabetes who had received intrahepatic infusions of human islet allografts maintained normal levels of HbA1c for more than 1 year after transplant (4.4–14.9 months) without insulin treatment (1). They attributed their success to the infusion of a large total number of islets and the avoidance of glucocorticoid use for immunosuppression. The number of islet infusions depended on whether or not success was achieved with the preceding infusion. The average total mass of islets used was 11,547 ± 1,604 islet equivalents/kg body weight (approximately 80% of that believed to be in a normal human pancreas). Glucocorticoids were avoided because of their known toxic effect on β-cells. Posttransplant C-peptide levels were stimulated twofold by mixed-meal tolerance tests. A subsequent publication by this group in 2002 reported that success appeared to be continuing as evidenced by sophisticated measures of β-cell function (2). However, by the fifth year of follow-up, these first blushes of prolonged success began to lose their glow. In 2005, Ryan et al. (3) reported that of 65 recipients, approximately 10% maintained insulin independence, 10% …
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".