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Record W2783329252 · doi:10.5206/wurjhns.2017-18.8

Western Faculty Profile: Dr. Gregory Kelly

2017· article· en· W2783329252 on OpenAlexaffvenueabout
Zi Hao Liu

Bibliographic record

VenueWestern Undergraduate Research Journal Health and Natural Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsWestern University
Fundersnot available
KeywordsLibrary scienceSociology

Abstract

fetched live from OpenAlex

Born in Winnipeg and raised in rural Manitoba, Dr. Gregory Kelly is a Full Professor in the Department of Biology at the Western University. He completed his Honors B.Sc. and Ph.D. in Zoology at the University of Manitoba before moving to the University of Washington for his Postdoctoral research and extended stay as a Lecturer in the Department of Pharmacology with Dr. Randall Moon. With almost 25 years of teaching experience at Western University, Dr. Kelly has led many groups of students through the expeditions of Cell and Developmental Biology. In addition to his experiences within Canada, Dr. Kelly has also served as a visiting professor at many international universities, including: The University of Warmia and Mazury in Poland, Umeå University in Sweden, Osaka University in Japan, as well as the University of Bergen and TromsØ in Norway.

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)0.004
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 score0.248
Threshold uncertainty score0.830

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.2480.136

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 head0.093
GPT teacher head0.449
Teacher spread0.356 · 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
Published2017
Admission routes3
Has abstractyes

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