Incorporating a Generic Model of Subcutaneous Insulin Absorption into the AIDA v4 Diabetes Simulator
Bibliographic record
Abstract
INTRODUCTION: AIDA v4 is an interactive educational diabetes simulator that has been made available, for over a decade, without charge via the Internet. The software is currently freely accessible at http://www.2aida.org. This report sets out a collaborative development plan to enhance the program with a new model of subcutaneous insulin absorption, which permits the simulation of rapidly acting and very long-acting insulin analogues, as well as insulin injection doses larger than 40 units. METHODS: A novel, generic, physiological subcutaneous insulin absorption model is overviewed and a methodology is proposed by which this can be substituted in place of the previously adopted insulin absorption model utilized within AIDA v4.3a. Apart from this substitution it is proposed to retain the existing model of the glucoregulatory system currently used in AIDA v4.3a. RESULTS: Initial simulation results based on bench testing of this approach using MATLAB are presented for the exogenous insulin flow profile (I(ex)) following subcutaneous injections of a rapidly acting insulin analogue, a short-acting (regular) insulin preparation, intermediate-acting insulins (both Semilente and neutral protamine Hagedorn types), and a very long-acting insulin analogue. DISCUSSION: It is proposed to implement this collaborative development plan-first by bench testing the approach in MATLAB and then by integrating the generic subcutaneous insulin absorption I(ex) model into the AIDA simulator in Pascal. The aim is to provide enhanced functionality and educational simulations of regimens utilizing novel insulin analogues, as well as injections larger than 40 units of insulin.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".