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Trouble at t’lab

2002· book-chapter· en· W4388389612 on OpenAlexaboutno aff
Walter Gratzer

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHistorical and modern epidemiology studies
Canadian institutionsnot available
Fundersnot available
KeywordsHappinessStarvationFellHistoryMedicineArtClassicsInternal medicinePolitical scienceLawGeographyCartography

Abstract

fetched live from OpenAlex

Abstract When judged by its impact on human life and happiness, the discovery of insulin was perhaps the most momentous event in the history of modern science. Up to the third decade of the twentieth century a diagnosis of dia betesߞwhich an alert doctor could often make from the white spots of dried sugar that bespattered a male patient’s shoes or trouser bottomsߞpresaged an early and miserable death. This could be delayed only by a starvation diet, no less agonizing for most patients than the disease. The road to insulin was beset by misadventure, rancour, and deceit. The award of a Nobel Prize in 1923 to two of the principal actors, Frederick Banting (1891-1941) and John Macleod (1876-1935), inflamed several others, who felt (with some justice) that their efforts had been disparaged or forgotten. One of these was Nicolas Paulesco, a Romanian physiologist, who made the critical observation that linked diabetes to the dearth of an active component in the pancreas: he discovered that high levels of sugar in the blood and urine of dogs, rendered diabetic by extirpation of the pancreas, fell when the animals were injected with pancreatic extracts. Paulesco’s work was interrupted for four years by the Austro-Hungarian invasion of his country before the end of the First World War, and by the time he returned to the problem Banting, Macleod, Best, and Collip in Toronto were closing in on their quarry.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.548
Threshold uncertainty score0.644

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0090.006
Open science0.0020.006
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.5480.338

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 head0.120
GPT teacher head0.311
Teacher spread0.190 · 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
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
Published2002
Admission routes1
Has abstractyes

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