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Record W2510915539 · doi:10.1107/s160057671501362x

Scattering from phase-separated vesicles. I. An analytical form factor for multiple static domains

2015· article· en· W2510915539 on OpenAlexaff
Frederick A. Heberle, V. Anghel, John Katsaras

Bibliographic record

VenueJournal of Applied Crystallography · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsBrock UniversityCanadian Nuclear Laboratories
FundersBasic Energy SciencesU.S. Department of Energy
KeywordsScatteringSmall-angle scatteringMonte Carlo methodTruncation (statistics)Neutron scatteringBiological small-angle scatteringStructure factorContext (archaeology)Small-angle neutron scatteringStatistical physicsVesicleDomain (mathematical analysis)Phase (matter)Series (stratigraphy)PhysicsComputational physicsChemistryOpticsCrystallographyMathematicsMathematical analysisStatisticsQuantum mechanics

Abstract

fetched live from OpenAlex

This is the first in a series of papers considering elastic scattering from laterally heterogeneous lipid vesicles containing multiple domains. Unique among biophysical tools, small-angle neutron scattering can in principle give detailed information about the size, shape and spatial arrangement of domains. A general theory for scattering from laterally heterogeneous vesicles is presented, and the analytical form factor for static domains with arbitrary spatial configuration is derived, including a simplification for uniformly sized round domains. The validity of the model, including series truncation effects, is assessed by comparison with simulated data obtained from a Monte Carlo method. Several aspects of the analytical solution for scattering intensity are discussed in the context of small-angle neutron scattering data, including the effect of varying domain size and number, as well as solvent contrast. The analysis indicates that effects of domain formation are most pronounced when the vesicle's average scattering length density matches that of the surrounding solvent.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.304
Teacher spread0.274 · 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 designSimulation or modeling
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

Citations15
Published2015
Admission routes1
Has abstractyes

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