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Record W3200167997 · doi:10.1112/blms.12547

Samuel James Taylor, 1929–2020

2021· article· en· W3200167997 on OpenAlexaff
Martin T. Barlow, Ν. H. Bingham

Bibliographic record

VenueBulletin of the London Mathematical Society · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStatistical Mechanics and Entropy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsQueen (butterfly)WifeTheme (computing)HistoryDemographySociologyTheologyPhilosophy

Abstract

fetched live from OpenAlex

Samuel James Taylor (known as ‘James’) was born on 13 December 1929 in Carrickfergus, Northern Ireland. He spent most of the first eleven years of his life in Africa, tutored by his mother. James took his first degree at Queen's University, Belfast, and went on to study for a PhD in Pure Mathematics at Peterhouse College, Cambridge, with A. S. Besicovich. He was appointed a Lecturer in Birmingham in 1955 and moved to Westfield College in 1962 as a Reader and from 1964 Professor. The years 1975–1983 were spent at the University of Liverpool, followed by the University of Virginia from 1984 until 1996, when James retired and returned to the UK to settle in Sevenoaks, Kent, remaining active in research. The main theme of his life-time research involved the fine sample path properties of stochastic processes and their Hausdorff measures properties. He is survived by his wife Maureen of 64 years, his four children Richard, Charles, Jonathan, and Helen, seventeen grandchildren and six great-grandchildren.

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)0.005
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 score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0180.013

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueBulletin of the London Mathematical SocietySame topicStatistical Mechanics and EntropyFrench-language works237,207