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Record W3022398816 · doi:10.1101/2020.05.03.075366

Through-grid wicking enables high-speed cryoEM specimen preparation

2020· preprint· en· W3022398816 on OpenAlex
Yong Zi Tan, John L. Rubinstein

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsGridMaterials scienceVitrificationProcess (computing)Membrane filterFiberComposite materialComputer scienceFilter (signal processing)Glass fiberChemical engineeringMembraneChemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Blotting times for conventional cryoEM specimen preparation complicate time-resolved studies and lead to some specimens adopting preferred orientations or denaturing at the air-water interface. We show that solution sprayed onto one side of a holey cryoEM grid can be wicked through the grid by a glass fiber filter held against the opposite side, often called the ‘back’ of the grid, producing a film suitable for vitrification. This process can be completed in tens of milliseconds. We combined ultrasonic specimen application and through-grid wicking in a high-speed specimen preparation device that we name ‘Back-it-up’, or BIU. The high liquid-absorption capacity of the glass fiber compared to self-wicking grids appears to make the method relatively insensitive to the amount of sample applied. Consequently, through-grid wicking produces large areas of ice suitable for cryoEM for both soluble and detergent-solubilized protein complexes. The device’s speed increases the number of views for a specimen that suffers from preferred orientations.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.277
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