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Record W1996196630 · doi:10.1021/la702382d

Young's Moduli of Surface-Bound Liposomes by Atomic Force Microscopy Force Measurements

2008· article· en· W1996196630 on OpenAlexaff
Heïdi Brochu, Patrick Vermette

Bibliographic record

VenueLangmuir · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHertzLiposomeModuliAtomic force microscopyWork (physics)Kelvin probe force microscopeChemistryCompression (physics)Elastic modulusMaterials scienceMechanicsComposite materialMolecular physicsNanotechnologyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Mechanical properties of layers of intact liposomes attached by specific interactions on solid surfaces were studied by atomic force microscopy (AFM) force measurements. Force-distance measurements using colloidal probe tips were obtained over liposome layers and used to calculate Young's moduli by using the Hertz contact theory. A classical Hertz model and a modified Hertz one have been used to extract Young's moduli from AFM force curves. The modified model, proposed by Dimitriadis, is correcting for the finite sample thickness since Hertz's classical model is assuming that the sample is infinitely thick. Values for Young's moduli of 40 and 8 kPa have been obtained using the Hertz model for one and three layers of intact liposomes, respectively. Young's moduli of approximately 3 kPa have been obtained using the corrected Hertz model for both one and three layers of surface-bound liposomes. Compression work performed by the colloidal probe to compress these liposome layers has also been calculated.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.272
Teacher spread0.255 · 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

Citations47
Published2008
Admission routes1
Has abstractyes

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