MétaCan
Menu
Back to cohort
Record W2081118958 · doi:10.5402/2012/520307

Hydration Water Freezing in Single Supported Lipid Bilayers

2012· article· en· W2081118958 on OpenAlexafffund
Laura Toppozini, Clare L. Armstrong, Martin D. Kaye, Madhusudan Tyagi, T. Jenkins, Maikel C. Rheinstädter

Bibliographic record

VenueISRN Biophysics · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsNational Research Council CanadaMcMaster University
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsLipid bilayerNeutron scatteringMolecular dynamicsScatteringMembraneChemistryChemical physicsCoupling (piping)Materials scienceCrystallographyOptics

Abstract

fetched live from OpenAlex

We present a high-temperature and high-energy resolution neutron scattering investigation of hydration water freezing in single supported lipid bilayers. Single supported lipid bilayers provide a well-defined biological interface to study hydration water dynamics and coupling to membrane degrees of freedom. Nanosecond molecular motions of membrane and hydration water were studied in the temperature range 240 K < T < 290 K in slow heating and cooling cycles using coherent and incoherent elastic neutron scattering on a backscattering spectrometer. Several freezing and melting transitions were observed. From the length scale dependence of the elastic scattering, these transitions could be assigned to freezing and melting of hydration water dynamics, diffusive lipid, and lipid acyl-tail dynamics. Coupling was investigated by comparing the different freezing and melting temperatures. While it is often speculated that membrane and hydration water dynamics are strongly coupled, we find that membrane and hydration water dynamics are at least partially decoupled in single bilayers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.238
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueISRN BiophysicsSame topicLipid Membrane Structure and BehaviorFrench-language works237,207