MétaCan
Menu
Back to cohort
Record W1987125946 · doi:10.1136/bmj.329.7474.1105

Sir Donald Campbell

2004· article· en· W1987125946 on OpenAlexaboutno aff
Alison Telfer

Bibliographic record

VenueBMJ · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceData scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Anaesthetist who was at the forefront of introducing intensive care units Sir Donald Campbell was a pioneer in many aspects of anaesthesia, particularly the introduction of intensive care units.After his resident posts he left for Canada for training.He worked in Edmonton and in Lethbridge, Alberta, and after three years, in 1956, he returned to Glasgow and began his long association with anaesthesia in the west of Scotland.He was appointed lecturer in the university department of anaesthetics at Glasgow Royal Infirmary in 1960, transferring the following year to the health service department as a consultant, a post that he held for the next 15 years.While in Canada he developed an interest in anaesthesia for heart surgery and he also noted the early development of intensive care units, which were associated with the concept of progressive patient care.With much lobbying and political skill he succeeded in persuading his surgical colleagues at the Royal Infirmary that this was the best way forward for their patients.The respira-tory intensive care unit was opened in 1966 and Professor Campbell was its first director.At the same time he pursued his research interests in several areas, mainly involving the development of more sophisticated ventilators, the pharmacology of new analgesic drugs, and the effects of smoke inhalation on the lungs.

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)0.002
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0460.019

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 head0.056
GPT teacher head0.263
Teacher spread0.207 · 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
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueBMJSame topicMedical History and InnovationsFrench-language works237,207