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Record W1981159786 · doi:10.1126/science.1124964

New Tools Provide New Insights in NMR Studies of Protein Dynamics

2006· review· en· W1981159786 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

VenueScience · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsProtein dynamicsFlexibility (engineering)Nuclear magnetic resonance spectroscopyProtein functionFunction (biology)Dynamics (music)Molecular dynamicsBiological systemProtein structureComputer sciencePhysicsNuclear magnetic resonanceChemistryComputational chemistryBiologyMathematicsBiochemistry

Abstract

fetched live from OpenAlex

There is growing evidence that structural flexibility plays a central role in the function of protein molecules. Many of the experimental data come from nuclear magnetic resonance (NMR) spectroscopy, a technique that allows internal motions to be probed with exquisite time and spatial resolution. Recent methodological advancements in NMR have extended our ability to characterize protein dynamics and promise to shed new light on the mechanisms by which these molecules function. Here, we present a brief overview of some of the new methods, together with applications that illustrate the level of detail at which protein motions can now be observed.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.333
Teacher spread0.301 · 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