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Alan Hall - Bibliography from Alan Hall. 19 May 1952 — 3 May 2015

2024· article· en· W6958123106 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsnot available
Fundersnot available
KeywordsMedalGold medalGeorge (robot)Editorial boardPortrait

Abstract

fetched live from OpenAlex

Alan Hall was born in a mining town in Yorkshire in 1952. He studied chemistry at Oxford and then, after starting his PhD in biochemistry in Oxford, he completed it at Harvard in the USA, where he made important discoveries about the evolution of antibiotic resistance in bacteria. Following postdoctoral studies in the UK and Switzerland, he set up his independent research in London at the Institute of Cancer Research, where he began his work which opened up the field of study of the Ras-homologous family of small GTPase proteins. Alan made seminal discoveries in this field, which revolutionized cell biology in the UK and internationally. Alan's work made connections between cell migration, cancer and cell signalling and provided a mechanistic understanding of how many cell processes work at the molecular level. Alan helped to found the Laboratory for Molecular Cell Biology in London and became the director in 2001. In 2006 he moved to the Memorial Sloan Kettering Cancer Center in New York as chair of Cell Biology. He was awarded the Feldberg Foundation Prize in 1993, the Novartis Medal (UK Biochemical Society) and the Louis Jeantet Prize for Medicine in 2005, as well as the Canada Gairdner Prize in 2006. He was elected as a European Molecular Biology Organization member in 1994, as a Fellow of the Royal Society in 1999 and Fellow of the Academy of Medical Sciences in 2004.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.725
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0380.001

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 head0.025
GPT teacher head0.285
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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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