Bibliographic record
Abstract
In this chapter, there is a discussion of the history of insulin discovery at the University of Toronto, Canada, in the early part of the twentieth century, which led to the ability to treat type 1 (juvenile onset; T1DM) diabetic patients with the hormone that their pancreas would not produce. In addition, reports in the mediaeval literature of the use of extracts of the herb Galega officinalis Linn. led in the early twentieth century to the initial discovery of metformin, then its rediscovery in France in the 1950s, and its much later approval in the USA in the middle of the 1990s. This chapter also discusses various classes of synthetic agents, based on being mimics of the natural substrate, even if not identified since they were direct inhibitors of the desired target enzyme/organelle. These included a derivative of the protein isolated from the lizard known as the Gila monster that mimicked the protein exendin-4, a component of the target(s) related to “adult onset” diabetes or type 2 diabetes mellitus (T2DM). There is also a discussion of the medical condition known as “Metabolic Syndrome”, which is one of the candidate routes to T2DM, demonstrating that slightly modified insulin coupled to other agents may well help in the treatment of that condition.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".