MétaCan
Menu
Back to cohort
Record W4310549931 · doi:10.1242/bio.059701

First person – Kelli Fenelon

2022· article· en· W4310549931 on OpenAlexaboutno aff

Bibliographic record

VenueBiology Open · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyLibrary scienceComputer science

Abstract

fetched live from OpenAlex

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Biology Open, helping researchers promote themselves alongside their papers. Kelli Fenelon is first author on ‘ Transgenic force sensors and software to measure force transmission across the mammalian nuclear envelope in vivo’, published in BiO. Kelli conducted the research described in this article while a PhD Student in Sevan Hopyan's lab at the University of Toronto, Canada. Kelli is now a postdoc in the lab of Theodora Koromila at The University of Texas at Arlington, USA, investigating the intersection of developmental biology and mechanobiology.

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)0.008
metaresearch head score (Gemma)0.045
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 score0.119
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0120.004
Scholarly communication0.0070.007
Open science0.0010.005
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.1190.060

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 head0.030
GPT teacher head0.284
Teacher spread0.253 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueBiology OpenSame topicCellular Mechanics and InteractionsFrench-language works237,207