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Record W3035605271 · doi:10.1107/s2052252520006855

1.8 Å resolution structure of β-galactosidase with a 200 kV CRYO ARM electron microscope

2020· article· en· W3035605271 on OpenAlexaff
Alan Merk, Takuma Fukumura, Xing Zhu, Joseph E. Darling, Reinhard Grisshammer, Jana Ognjenović, Sriram Subramaniam

Bibliographic record

VenueIUCrJ · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersNational Institutes of HealthLeidosNational Cancer InstituteFrederick National Laboratory for Cancer ResearchU.S. Department of Health and Human Services
KeywordsCryo-electron microscopyElectron microscopeResolution (logic)MicroscopeComputer scienceChemistryOpticsPhysicsArtificial intelligenceBiochemistry

Abstract

fetched live from OpenAlex

We report the determination of the structure of Escherichia coli β-galactosidase at a resolution of ∼1.8 Å using data collected on a 200 kV CRYO ARM microscope equipped with a K3 direct electron detector. The data were collected in a single 24 h session by recording images from an array of 7 × 7 holes at each stage position using the automated data collection program SerialEM. In addition to the expected features such as holes in the densities of aromatic residues, the map also shows density bumps corresponding to the locations of hydrogen atoms. The hydrogen densities are useful in assigning absolute orientations for residues such as glutamine or asparagine by removing the uncertainty in the fitting of the amide groups, and are likely to be especially relevant in the context of structure-guided drug design. These findings validate the use of electron microscopes operating at 200 kV for imaging protein complexes at atomic resolution using cryo-EM.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.276
Teacher spread0.271 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations36
Published2020
Admission routes1
Has abstractyes

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