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Record W4287155687 · doi:10.1051/jbio/2022006

La découverte de l’insuline 1921–1922 : un saut dans la recherche biomédicale

2022· article· fr· W4287155687 on OpenAlexaboutno aff
William Rostène

Bibliographic record

VenueBiologie Aujourd hui · 2022
Typearticle
Languagefr
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesMedicineArt

Abstract

fetched live from OpenAlex

Discovery of insulin. If the symptoms of diabetes have been known since Antiquity, it is at the end of the 19th century that several investigators searched for the active substance of the pancreas and endeavoured to produce extracts that lowered blood and urine glucose and decreased polyuria in pancreatectomized dogs. The breakthrough came 100 years ago when the team of Frederick Banting, Charles Best and James Collip, working in the Department of Physiology, headed by John MacLeod at the University of Toronto, managed to obtain pancreatic extracts that could be used to treat patients and rescue them from the edge of death by starvation, the only treatment then available. This achievement was quickly recognized by the Nobel Prize in Physiology or Medicine to Banting and MacLeod in 1923. The discovery has had important scientific, industrial and clinical developments still efficient nowadays.

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)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0020.014
Scholarly communication0.0060.011
Open science0.0010.003
Research integrity0.0050.014
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.147
GPT teacher head0.361
Teacher spread0.215 · 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.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2022
Admission routes1
Has abstractyes

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