Bibliographic record
Abstract
More than 80 years ago, the discovery of insulin in Canada was a landmark event that changed the face of diabetes treatment. Insulin gave life to people with type 1 diabetes mellitus (T1 DM) who, until then, succumbed to their disease. Presently, millions of people use insulin for the treatment of T1 and T2 DM. Over the years, insulin preparations have evolved from the initial animal insulins that were crude and contaminated with split prod-ucts, impurities, and other pancreatic hormones, to the more purified animal insulins, the biosynthetic human insulins and, most recently, insulin analogues. The latter technology has resulted in the creation of rapid and long-acting analogues that provide optimal meal and basal insulins, respectively. A review of the characteristics of the long-acting insulin analogues, with a focus on glargine and detemir, is the subject of this issue of Endocrinology Rounds. Insulin glargine is available in Canada under the trade name, Lantus, while insulin detemir (Levemir), although released in Europe last fall, is not yet available in Canada. Characteristics of ideal basal insulin The ideal basal insulin should provide a sustained peakless action profile when injected
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".