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Record W2114175973 · doi:10.1039/b710321m

Engineering proteins with tailored nanomechanical properties: a single molecule approach

2007· review· en· W2114175973 on OpenAlexaff
Hongbin Li

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2007
Typereview
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsForce spectroscopyNanomechanicsElastomerNanotechnologyChemistryMoleculeAtomic force microscopyMaterials science

Abstract

fetched live from OpenAlex

Elastomeric proteins underlie the elasticity of natural adhesives, cell adhesion and muscle proteins. They also serve as structural materials with superb mechanical properties. Single molecule force spectroscopy has made it possible to directly probe the mechanical properties of elastomeric proteins at the single molecule level and revealed insights into the molecular design principles of elastomeric proteins. Combining single molecule atomic force microscopy and protein engineering techniques, it has become possible to engineer proteins with tailored nanomechanical properties. These efforts are paving the way to design artificial elastomeric proteins with well-defined nanomechanical properties for application in nanomechanics and materials sciences.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.490
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.250
Teacher spread0.231 · 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
GenreReview

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

Citations24
Published2007
Admission routes1
Has abstractyes

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