Banting and Best: The Extraordinary Discovery of Insulin
Bibliographic record
Abstract
Diabetes was a feared disease that most certainly led to death before insulin discovery. During the first two decades of the 20th century, several researchers tested pancreatic extracts, but most of them caused toxic reactions impeding human use. On May 1921, Banting, a young surgeon, and Best, a master’s student, started testing the hypothesis that, by ligating the pancreatic ducts to induce atrophy of the exocrine pancreas and minimizing the effect of digestive enzymes, it would be possible to isolate the internal secretion of the pancreas. The research took place at the Department of Physiology of the University of Toronto under supervision of the notorious physiologist John MacLeod. Banting and Best felt several difficulties depancreatising dogs and a couple of weeks after the experiments had begun most of the dogs initially allocated to the project had succumbed to perioperative complications. When they had depancreatised dogs available, they moved to the next phase of the project and prepared pancreatic extracts from ligated atrophied pancreas. These extracts effectively reduced glycaemia on dogs. However, duct ligation was so time and animal consuming, that Banting and Best looked for alternatives and developed a method of extraction without the ligation procedure from fresh pancreata, which were readily available. These extracts were shown to be equally effective. Meanwhile, Collip, a biochemist of the University of Alberta, joined the group and developed a method for purifying insulin, which allowed its widespread human use. On 11 January 1922, Leonard Thomson, a 14–year–old boy with type 1 diabetes, received the first subcutaneous injections of Banting and Best’s extracts. On October 1923, the Nobel Prize in Physiology or Medicine was awarded to Banting and Macleod for the discovery of insulin. In disagreement with the Karolinska Nobel Committee, Banting shared his prize with Best and MacLeod shared his prize with Collip.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".