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Record W2214494545 · doi:10.1016/j.sbi.2015.07.002

Validating maps from single particle electron cryomicroscopy

2015· review· en· W2214494545 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Opinion in Structural Biology · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersMedical Research CouncilCanadian Institutes of Health ResearchWellcome TrustFrancis Crick InstituteCanada Research ChairsCancer Research UK
KeywordsCryo-electron microscopyResolution (logic)Consistency (knowledge bases)Particle (ecology)Computer scienceTilt (camera)Single particle analysisData miningAlgorithmArtificial intelligencePhysicsMathematicsGeometry

Abstract

fetched live from OpenAlex

Progress in single particle cryo-EM, most recently due to the introduction of direct detector devices, has made the high-resolution structure determination of biological assemblies smaller than 500kDa more routine, but has also increased attention on the need for tools to demonstrate the validity of single particle maps. Although map validation is a continuing subject of research, some consensus has been reached on procedures that reduce model bias and over-fitting during map refinement as well as specific tests that demonstrate map validity. Tilt-pair analysis may be used as a method for demonstrating the consistency at low resolution of a map with image data. For higher-resolution maps, new procedures for more robust resolution assessment and for validating the refinement of atomic coordinate models into single particle maps have been developed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.072
GPT teacher head0.458
Teacher spread0.386 · 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