β-Score
Bibliographic record
Abstract
OBJECTIVE: Success after islet transplantation can be defined in terms of insulin independence, C-peptide secretion, or glycemic control. These measures are interdependent and all need to be considered in evaluating beta-cell function after islet transplantation. For the current study, a composite beta-score was developed that provides an integrated measure of beta-cell function success after islet transplantation. RESEARCH DESIGN AND METHODS: The proposed scoring system gave 2 points each for normal fasting glucose, HbA(1c), stimulated C-peptide, and absence of insulin or oral hypoglycemic agent use. No points were awarded if the fasting glucose was in the diabetic range, the HbA(1c) was >6.9%, C-peptide secretion was absent on stimulation, or daily insulin use was in excess of 0.24 units/kg. One point was given for intermediate values. The score ranged from 0 to 8 and was correlated with the glucose value 90 min after a standard mixed meal challenge (n = 218) in 57 subjects before and after islet transplantation. The score was also used to follow subjects for up to 5 years after islet transplantation. RESULTS: The beta-score correlated well with the plasma glucose level 90 min after a mixed meal challenge (r = -0.849, P < 0.001). On follow-up, the beta-score rose after the first transplant and was maintained up to 5 years, demonstrating continuing function of the transplanted beta-cells. CONCLUSIONS: The beta-score provides a simple clinical scoring system that encompasses glycemic control, diabetes therapy, and endogenous insulin secretion that correlates well with physiological measures of beta-cell function. On this basis, it is suitable as an overall measure of beta-cell transplant function. The beta-score gives an integrated measure of beta-cell function as a continuum that may be more useful than simply assessing the presence or absence of insulin independence.
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 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) | 0.001 | 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 teacher head, 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".