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Record W4242525848 · doi:10.1504/ijsurfse.2019.097912

Surface-modified substrates for the Langmuir-Blodgett deposition of patterned ultra-thin and highly oriented collagen coatings

2019· article· en· W4242525848 on OpenAlexaff
Karina Ambrock, Bernd Grohe, Silvia Mittler

Bibliographic record

VenueInternational Journal of Surface Science and Engineering · 2019
Typearticle
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceLangmuir–Blodgett filmSubstrate (aquarium)Deposition (geology)Composite materialChemical engineeringNanotechnologyMonolayer

Abstract

fetched live from OpenAlex

As a pre-study for highly oriented collagen coatings on implants (with irregular surfaces and shapes), the Langmuir-Blodgett (LB) technology, a low-cost and straightforward approach, was pioneered. The effects of physicochemical (hydrophilic/hydrophobic) patterns and 3D-mechanical barriers present on substrate surfaces are studied in terms of the dynamics of collagen flow during LB film deposition and the formation of highly oriented coatings. Due to the large internal cohesion of collagen films, only large 3D-obstacles deflect the flow of collagen and lead to film rupture, suggesting that objects (screw-threaded dental implants) with small topographic features should be easily and evenly coatable. Moreover, hydrophilic/hydrophobic/collagen patterned substrate surfaces were fabricated, by partly removing coated collagen. These substrates are outstanding for timely studies that need identical conditions but different surface properties side by side. Crystallisation of barium oxalate was carried out as a proof-of-principle.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.044
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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.

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

Citations3
Published2019
Admission routes1
Has abstractyes

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