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Frontiers in Cryo Electron Microscopy of Complex Macromolecular Assemblies

2019· review· en· W2924863631 on OpenAlex

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

VenueAnnual Review of Biomedical Engineering · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversity of British Columbia
FundersNational Cancer InstituteNational Institutes of Health
KeywordsCryo-electron microscopyCryo-electron tomographySingle particle analysisElectron microscopeElectron tomographyStructural biologyNanotechnologyMicroscopyBiophysicsMacromoleculeMacromolecular SubstancesChemistryComputational biologyMaterials scienceBiologyCell biologyPhysicsTomographyBiochemistryTransmission electron microscopyScanning transmission electron microscopyOptics

Abstract

fetched live from OpenAlex

In recent years, cryo electron microscopy (cryo-EM) technology has been transformed with the development of better instrumentation, direct electron detectors, improved methods for specimen preparation, and improved software for data analysis. Analyses using single-particle cryo-EM methods have enabled determination of structures of proteins with sizes smaller than 100 kDa and resolutions of ∼2 Å in some cases. The use of electron tomography combined with subvolume averaging is beginning to allow the visualization of macromolecular complexes in their native environment in unprecedented detail. As a result of these advances, solutions to many intractable challenges in structural and cell biology, such as analysis of highly dynamic soluble and membrane-embedded protein complexes or partially ordered protein aggregates, are now within reach. Recent reports of structural studies of G protein-coupled receptors, spliceosomes, and fibrillar specimens illustrate the progress that has been made using cryo-EM methods, and are the main focus of this review.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.916
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.310
Teacher spread0.297 · 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