MétaCan
Menu
Back to cohort
Record W3111299257 · doi:10.1002/pi.6162

<scp>Polyetheretherketone</scp> implant surface functionalization technologies and the need for a transparent quality evaluation system

2020· article· en· W3111299257 on OpenAlexaff
Dietmar Schaffarczyk, Jennifer Knaus, Gunther Peeters, Dieter Scholl, Andreas Dominik Schwitalla, Christoph Koslowski, Helmut Cölfen

Bibliographic record

VenuePolymer International · 2020
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutions123 Certification (Canada)
Fundersnot available
KeywordsOsseointegrationSurface modificationImplantMaterials scienceBiomedical engineeringDentistryNanotechnologyMechanical engineeringEngineeringMedicineSurgery

Abstract

fetched live from OpenAlex

Abstract For bone implants, osseointegration resulting in a good and fast bone–implant contact is of primary importance to secure a proper implant function and to avoid implant loosening or inflammation resulting in necessary revision surgeries causing pain to the patients and immense costs. In particular, polyetheretherketone (PEEK) is a promising implant material due to the close mechanical properties to bone, but it is entirely bio‐inert, hindering osseointegration and making surface functionalization necessary. Many different surface functionalization technologies have been reported of both physical and chemical nature. The same is true for the other prominent implant materials titanium and ceramics. Although they already have inherently better osseointegration than PEEK, they are much harder and stiffer than bone and brittle in the case of ceramics. Surface functionalization, which can be subdivided into surface coating and material modification, needs to be judged from a quality and safety viewpoint. However, a literature research resulted in the realization that no quality standard yet exists for implant surface functionalizations. This makes it difficult to near impossible to compare the safety and performance of different surface‐functionalized bone implants, clearly showing the need to establish a transparent quality evaluation system for bone implants. This perspective article gives the state of the art and then develops a quality evaluation system based on six main categories as important benchmarks for the quality of surface‐functionalized bone implant materials. A simple catalog of questions can be answered, and from the resulting scores the Safety and Performance Evidence Level (SPEL) representing the safety and quality of a given implant can be calculated as a percentage. This simple SPEL system allows an easy and transparent judgment and comparison of bone implants, ensuring the easy identification of safe and well‐performing high‐quality bone implants in the future. © 2020 The Authors. Polymer International published by John Wiley &amp; Sons Ltd on behalf of Society of Chemical Industry.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.474

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 science0.0000.000
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 head0.044
GPT teacher head0.275
Teacher spread0.231 · 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 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

Citations6
Published2020
Admission routes1
Has abstractyes

Explore more

Same venuePolymer InternationalSame topicBone Tissue Engineering MaterialsFrench-language works237,207