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Structure of Silk using Solid-State NMR

2008· reference-entry· en· W1593845142 on OpenAlexaff
Carl A. Michal

Bibliographic record

VenueEncyclopedia of Magnetic Resonance · 2008
Typereference-entry
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSILKSpider silkPolymer scienceSolid-state nuclear magnetic resonanceCrystallinityMaterials scienceSynthetic fiberBombyx moriFiberChemistryComposite materialNuclear magnetic resonancePhysics

Abstract

fetched live from OpenAlex

Silks are natural protein fibers produced by insects and spiders. The mechanical properties of silks span a wide range, and include combinations, for example, strength and extensibility, that are difficult to achieve in synthetic polymers. A variety of solid-state NMR techniques have played a crucial role in the understanding of the structure and microscopic basis of the properties of silks. Isotropic chemical shifts measured with CP/MAS reflect the secondary structure of the protein backbones. Two-dimensional correlation spectroscopy experiments have allowed more direct measurement of backbone conformations, and measurements of anisotropic interactions such as chemical shift anisotropies, and dipolar and quadrupolar couplings have allowed measurement of molecular orientation in oriented fiber samples. The silks that have been most thoroughly studied with NMR, domesticated silkworm (Bombyx mori) cocoon silk and spider dragline silks, are semicrystalline fibers containing oriented β-sheet crystallites. The noncrystalline regions in these silks are much less well ordered, but in at least some cases do appear to have preferred structures. To date, only a handful of different silks from the enormous variety of silk-producing organisms in nature have been studied with NMR in any detail.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.623
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.261
Teacher spread0.246 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2008
Admission routes1
Has abstractyes

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