MétaCan
Menu
Back to cohort
Record W2157530469 · doi:10.1039/b811366c

NMR chemical shift data and ab initio shielding calculations: emerging tools for protein structure determination

2009· review· en· W2157530469 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueChemical Society Reviews · 2009
Typereview
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsnot available
FundersRijksuniversiteit GroningenUniversity of Calgary
KeywordsChemical shiftAb initioElectromagnetic shieldingChemistryComputational chemistryNuclear magnetic resonance spectroscopyMolecular dynamicsAb initio quantum chemistry methodsChemical physicsMoleculePhysical chemistryPhysicsOrganic chemistryQuantum mechanics

Abstract

fetched live from OpenAlex

In this tutorial review, we discuss the utilization of chemical shift information as well as ab initio calculations of nuclear shieldings for protein structure determination. Both the empirical and computational aspects of the chemical shift are reviewed and the role of molecular dynamics and the accuracy of different computational methods are discussed. It is anticipated that incorporating theoretical information on chemical shifts will increase the accuracy of protein structures, in the solid and liquid state alike, and extend the applicability of NMR spectroscopy to ever larger systems.

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)0.001
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 score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.119
GPT teacher head0.407
Teacher spread0.287 · 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