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Record W1581689621 · doi:10.1038/nsmb.3041

NMR Exchange Format: a unified and open standard for representation of NMR restraint data

2015· letter· en· W1581689621 on OpenAlexafffund
Aleksandras Gutmanas, Paul D. Adams, Benjamin Bardiaux, Helen M. Berman, David A. Case, Rasmus H. Fogh, Peter Güntert, P. Hendrickx, Torsten Herrmann, Gerard J. Kleywegt, Naohiro Kobayashi, Oliver F. Lange, John L. Markley, G.T. Montelione, Michaël Nilges, Timothy J. Ragan, Charles D. Schwieters, Roberto Tejero, Eldon L. Ulrich, Sameer Velankar, Wim Vranken, Jonathan R. Wedell, John Westbrook, David S. Wishart, Geerten W. Vuister

Bibliographic record

VenueNature Structural & Molecular Biology · 2015
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversity of Alberta
FundersNational Bioscience Database CenterU.S. National Library of MedicineNational Institute of General Medical SciencesNational Institutes of HealthVolkswagen FoundationInstitute for Protein Research, Osaka UniversityDirectorate for Biological SciencesJapan Society for the Promotion of ScienceMedical Research CouncilTokyo Metropolitan UniversityTechnische Universität MünchenCentre National de la Recherche ScientifiqueEuropean Molecular Biology LaboratoryEuropean Bioinformatics InstituteVrije Universiteit BrusselGoethe-Universität Frankfurt am MainUniversity of AlbertaCenter for Information TechnologyRutgers, The State University of New JerseyWellcome TrustBiotechnology and Biological Sciences Research CouncilVlaams Instituut voor BiotechnologieUniversity of Wisconsin-MadisonJapan Science and Technology AgencyInnovirisUniversity of LeicesterNational Science Foundation
KeywordsRepresentation (politics)Nuclear magnetic resonance spectroscopyChemistryComputer scienceStereochemistryPolitical science

Abstract

fetched live from OpenAlex

We
\npresent
\na
\nunified,
\neasily
\nadaptable,
\nopen-­‐source
\nNMR
\nexchange
\nformat
\n(NEF)
\nfor
\nNMR
\nrestraints
\nand
\nassociated
\ndata.
\nDevelopers
\nof
\nthe
\nmajor
\nsoftware
\npackages
\nfor
\nNMR
\nstructure
\ndetermination
\nand
\nrefinement
\nhave
\nagreed
\nto
\nmake
\ntheir
\nsoftware
\nable
\nto
\nread
\nand
\nwrite
\nNEF-­‐compliant
\nfiles.
\nDetailed
\nspecifications
\ncan
\nbe
\nfound
\nat
\nhttps://github.com/NMRExchangeFormat/NEF.

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.

How this classification was reachedexpand

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), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.249
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.002
Research integrity0.0020.001
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 head0.036
GPT teacher head0.373
Teacher spread0.337 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations52
Published2015
Admission routes2
Has abstractyes

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