Bibliographic record
Abstract
Since the first successful use of insulin in 1921 to treat diabetes at Toronto General Hospital, the major advances in development of the medication itself have taken place in parallel with equally significant developments in the means of delivery. Administration of insulin remains parenteral. This article reviews the main variants in prescription-available delivery technology: vial and syringe, pen injector, needle-free injection, and continuous subcutaneous insulin infusion pumps. For each of these, the background and major milestones are covered briefly and followed by a discussion of the latest product innovations, technologies, and implementations, which are all considered in the context of the interaction with users. The article concludes by reflecting upon how the progress in the technology of diabetes management can best serve the patient. The spectacular technological advances in medication, monitoring, and delivery since 1922 have transformed the lives of millions. However, the fact that we can add sophisticated technology to delivery devices and accessories does not mean it is always the best thing for the patient. Electronic sophistication may be welcomed by a young, eager type 1 diabetes patient, while a senior citizen who discovers he has type 2 diabetes may yearn for simplicity. Technology continues to provide great solutions, but the type of solution delivered must be matched to the user if the maximum benefit is to be achieved for all.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".