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Record W3025566890 · doi:10.1177/1093526620923459

Kurt Aterman, MUDR, MB, BCh BAO HONS, DCH, MRCP, PhD, DSc, FRCPath: “A Small Man With a Very Large Cerebrum and a Soul to Match”

2020· article· en· W3025566890 on OpenAlexaffabout
James R. Wright

Bibliographic record

VenuePediatric and Developmental Pathology · 2020
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsCalgary Laboratory ServicesAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsHomelandNazismCzechRefugeeIrishClassicsSoulWorld War IIMedicineHistoryPoliticsLawGermanTheologyPolitical science

Abstract

fetched live from OpenAlex

Kurt Aterman was raised in the Czech-Polish portions of the former Austro-Hungarian Empire during World War I and the interwar period. After completing medical school and beginning postgraduate pediatrics training in Prague, this Jewish Czech physician fled to England as a refugee when the Nazis occupied his homeland in 1939. He repeated/completed medical training in Northern Ireland and London, working briefly as a pediatrician. Next, he served in the Royal Army Medical Corp in India, working as a pathologist. After the war and additional pathology training, he spent the next decade as an experimental pathologist in Birmingham, England. After completing a fellowship with Edith Potter in Chicago, Aterman spent the next 2 decades as a pediatric-perinatal pathologist, primarily working in Halifax, Canada. Fluent in many European languages, he finished his career as a medical historian. Aterman published extensively in all 3 arenas; many of his pediatric pathology papers were massive encyclopedic review articles, accurately recounting ideas from historical times. Aterman was a classical European scholar and his papers reflected this. Aterman was one of the founding members of the Pediatric Pathology Club, the predecessor of the Society for Pediatric Pathology. This highly successful refugee's writings are important and memorable.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.299
Teacher spread0.260 · 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 teacher head, not a consensus.

Study designObservational
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

Citations2
Published2020
Admission routes2
Has abstractyes

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