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Record W4390703372 · doi:10.1242/jcs.261791

Cell Scientist to Watch – Maria Ioannou

2024· article· en· W4390703372 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Cell Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsBiologySTED microscopyEndocytic cycleNeuroscienceCellSuperresolution

Abstract

fetched live from OpenAlex

ABSTRACT Maria Ioannou is an Assistant Professor in the Department of Physiology at the University of Alberta, Canada. Maria is a passionate microscopist and uses live-cell imaging and super-resolution microscopy to study lipid homeostasis in neurons and glial cells. After a PhD at McGill University, Montreal, Canada, studying the mechanisms of endocytic trafficking, she moved to the Janelia Research Campus, Ashburn, USA, for her postdoc to investigate lipid trafficking in the brain. Inspired by her findings, in 2019 she established her lab expanding on this work to better understand how and why lipids are transported from neurons to glia. We caught up with Maria over Zoom to find out more about her research, her love of microscopy and her recent return to the ice hockey arena.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0190.013

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 head0.004
GPT teacher head0.285
Teacher spread0.281 · 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
Published2024
Admission routes1
Has abstractyes

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