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Record W2149647205 · doi:10.1098/rsif.2012.0759

Adhesion of mussel foot proteins to different substrate surfaces

2012· article· en· W2149647205 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of The Royal Society Interface · 2012
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversity of Alberta
FundersNational Institute of Dental and Craniofacial Research
KeywordsAdhesionAdhesiveMicaCoatingNanotechnologySurface forces apparatusSubstrate (aquarium)PolystyreneMaterials scienceMusselChemistryComposite materialLayer (electronics)PolymerBiology

Abstract

fetched live from OpenAlex

Mussel foot proteins (mfps) have been investigated as a source of inspiration for the design of underwater coatings and adhesives. Recent analysis of various mfps by a surface forces apparatus (SFA) revealed that mfp-1 functions as a coating, whereas mfp-3 and mfp-5 resemble adhesive primers on mica surfaces. To further refine and elaborate the surface properties of mfps, the force-distance profiles of the interactions between thin mfp (i.e. mfp-1, mfp-3 or mfp-5) films and four different surface chemistries, namely mica, silicon dioxide, polymethylmethacrylate and polystyrene, were measured by an SFA. The results indicate that the adhesion was exquisitely dependent on the mfp tested, the substrate surface chemistry and the contact time. Such studies are essential for understanding the adhesive versatility of mfps and related/similar adhesion proteins, and for translating this versatility into a new generation of coatings and (including in vivo) adhesive materials.

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.

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 score0.016
Threshold uncertainty score0.435

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 communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.284
Teacher spread0.261 · 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