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Record W2116276298 · doi:10.1002/anie.201504070

Probing Invisible, Excited Protein States by Non‐Uniformly Sampled Pseudo‐4D CEST Spectroscopy

2015· article· en· W2116276298 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

VenueAngewandte Chemie International Edition · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectron Spin Resonance Studies
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsLimitingSpectroscopySpectral lineExcited stateChemistrySaturation (graph theory)Resolution (logic)Nuclear magnetic resonance spectroscopyHigh resolutionNuclear magnetic resonanceAnalytical Chemistry (journal)Computational physicsBiological systemMolecular physicsPhysicsComputer scienceAtomic physicsMathematicsArtificial intelligenceChromatography

Abstract

fetched live from OpenAlex

Chemical exchange saturation transfer (CEST) NMR spectroscopy is a powerful tool for studies of slow timescale protein dynamics. Typical experiments are based on recording a large number of 2D data sets and quantifying peak intensities in each of the resulting planes. A weakness of the method is that peaks must be resolved in 2D spectra, limiting applications to relatively small proteins. Resolution is significantly improved in 3D spectra but recording uniformly sampled data is time-prohibitive. Here we describe non-uniformly sampled HNCO-based pseudo-4D CEST that provides excellent resolution in reasonable measurement times. Data analysis is done through fitting in the time domain, without the need of reconstructing the frequency dimensions, exploiting previously measured accurate peak positions in reference spectra. The methodology is demonstrated on several protein systems, including a nascent form of superoxide dismutase that is implicated in neurodegenerative disease.

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 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 score0.049
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.269
Teacher spread0.256 · 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