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Record W2045434797 · doi:10.1002/mame.200800229

Methods to Investigate the Adhesion of Soft Nano‐Coatings on Metal Substrates – Application to Polymer‐Coated Stents

2008· article· en· W2045434797 on OpenAlex
François Lewis, Diego Mantovani

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

VenueMacromolecular Materials and Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceAdhesionCoatingPolymerSubstrate (aquarium)Composite materialNano-Polymer substrateNanotechnologyPaint adhesion testing

Abstract

fetched live from OpenAlex

Abstract Soft coatings are widely used to tailor the surface chemistry of materials without altering their bulk properties. However, the strength of adhesion between the coating and the substrate must be high enough for long‐term applications. This has become a major challenge in the medical field, especially for polymer‐coated stents, mainly due to several coating failures reported after mechanical expansion during clinical implantation. In this work, the applicability of current polymer‐metal adhesion tests to polymer‐coated stents is discussed. The small punch test was proposed as an adhesion test that allows fundamental studies on the adhesion and coating properties. This adhesion test was applied to thin fluorocarbon coatings deposited by plasma on 316L stainless steel. magnified image

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)0.000
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 score0.031
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

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 head0.223
Teacher spread0.210 · 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