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History of Insulin

2016· other· en· W2796219446 on OpenAlexaboutno aff
Morag Dagen

Bibliographic record

VenueEncyclopedia of Life Sciences · 2016
Typeother
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsInsulinProinsulinDiabetes mellitusEndocrinologyInternal medicineGlycosuriaC-peptideHormoneEndocrine systemMedicinePancreas

Abstract

fetched live from OpenAlex

Abstract Type 1 diabetes mellitus is an endocrine disorder in which the pancreas fails to produce the peptide hormone insulin, which is necessary for the regulation of glucose metabolism. Before the advent of insulin treatment, the condition was invariably fatal. At the beginning of the twentieth century, aware of the accumulating evidence that the hyperglycaemia of diabetes mellitus could be controlled by an extract of the pancreas, Banting and Best produced the first clinically useful insulin preparation at the University of Toronto. Insulin research led to a number of important breakthroughs in biochemistry: insulin was the first protein to be sequenced, it was the first peptide hormone shown to be formed by a posttranslational transformation of an inactive precursor and it was also the first genetically engineered protein to be approved for clinical use. Key Concepts Control of blood glucose levels is vitally important for health, and these are regulated by the hormone insulin. Insulin is a peptide hormone produced by the pancreas. Insufficient insulin results in the endocrine disease, diabetes mellitus. Hyperglycaemia and glycosuria (glucose in urine) are important signs of diabetes mellitus. Insulin and C‐peptide are produced by cleavage of proinsulin, a precursor protein. Pharmaceutical insulin preparations do not currently contain C‐peptide.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.129
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1290.087

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.

Opus teacher head0.021
GPT teacher head0.265
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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