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Record W4365455996 · doi:10.1090/noti2688

Robert Israel “Bob” Jewett (1937–2022)

2023· article· en· W4365455996 on OpenAlexaboutno aff
Walter R. Bloom, Richard J. Gardner, Al Hales, Joel Spencer, Terence Tao, B. P. Weiss

Bibliographic record

VenueNotices of the American Mathematical Society · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMathematical economicsPhilosophyMathematics

Abstract

fetched live from OpenAlex

Robert Israel "Bob" Jewett was born on December 14, 1937 in Providence, Rhode Island.His father, Abraham, had emigrated from Poland/Ukraine to Canada in 1921 and then to the USA in 1923, while his mother, Mame (Mary) née Katz, was born in Providence to parents from Russia.In 1946, Bob's family, including his older sister Rosalie, moved to Venice, California, a relocation partially motivated by Bob's problems with hay fever.Bob's much younger brother Phil was born in 1948.Bob attended the local public schools and was very interested, while at Venice High School, not only in physics and mathematics, but also animals and insects.In 1955, he started college at Caltech.There was no zoology major, so he focused on physics and mathematics, eventually the latter.In 1958, he received Honorable Mention for his individual performance in the nationwide Putnam competition in mathematics, helping the Caltech team to place third in the nation.Bob also stood out as a volleyball and track and field star.Bob graduated from Caltech in 1959 and went to the University of Oregon for graduate work in mathematics.Before this move, however, he worked for the summer at Caltech's Jet Propulsion Laboratory (JPL), in the coding theory section headed by Solomon Golomb.

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)0.001
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: Other
Teacher disagreement score0.049
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0490.022

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 head0.015
GPT teacher head0.279
Teacher spread0.264 · 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
Published2023
Admission routes1
Has abstractyes

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Same venueNotices of the American Mathematical SocietySame topicHedgehog Signaling Pathway StudiesFrench-language works237,207