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Record W4381430262 · doi:10.1098/rsbm.2023.0007

John Herbert Beynon. 29 December 1923—24 August 2015

2023· article· en· W4381430262 on OpenAlexaff
Robert K. Boyd

Bibliographic record

VenueBiographical Memoirs of Fellows of the Royal Society · 2023
Typearticle
Languageen
FieldChemistry
TopicFullerene Chemistry and Applications
Canadian institutionsNational Research Council Canada
FundersSwansea UniversityUniversity of WarwickDirectorate for Biological SciencesPurdue University
KeywordsHonourCompendiumLibrary scienceWelshClassicsEngineeringOperations researchManagementChemistryArt historySociologyHistoryLawPolitical scienceComputer scienceArchaeology

Abstract

fetched live from OpenAlex

Abstract John Herbert Beynon was born in a Welsh mining village in 1923, graduated BSc (Hons, physics) at 19, then worked on weapons research for the war effort in World War Two. In 1947 he started a 22-year career at Imperial Chemical Industries (ICI) in Manchester, where, with his technician Albert Williams, he revolutionized mass spectrometry from a physics method to an essential technique for organic chemistry. In 1960 he completed his landmark book Mass spectrometry and its applications to organic chemistry, which was reprinted by the American Society for Mass Spectrometry as a ‘Classic Book’. He continued his creative work in 1969–1974 at Purdue University. In 1974 he started his Royal Society Research Professorship at Swansea University, his alma mater. Collaborations here with a long string of students, postdoc, visiting professors and scientists from many countries resulted in about 65% of his list of 395 peer-reviewed publications. His unexpected retirement led to a compendium of 32 articles in his honour. He then initiated and edited a new journal, Rapid Communications in Mass Spectrometry.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.246
Teacher spread0.232 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

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