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Record W2119633096 · doi:10.1002/smll.200801186

Improving Biocompatibility of Implantable Metals by Nanoscale Modification of Surfaces: An Overview of Strategies, Fabrication Methods, and Challenges

2009· review· en· W2119633096 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSmall · 2009
Typereview
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsMcGill UniversityPlasmionique (Canada)Université de MontréalHydro-QuébecInstitut National de la Recherche Scientifique
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanadian Institutes of Health ResearchCanadian Bureau for International Education
KeywordsBiocompatibilityNanotechnologyMaterials scienceFabricationNanoscopic scaleSurface modificationMetallurgyChemical engineeringEngineeringMedicine

Abstract

fetched live from OpenAlex

The human body is an intricate biochemical-mechanical system, with an exceedingly precise hierarchical organization in which all components work together in harmony across a wide range of dimensions. Many fundamental biological processes take place at surfaces and interfaces (e.g., cell-matrix interactions), and these occur on the nanoscale. For this reason, current health-related research is actively following a biomimetic approach in learning how to create new biocompatible materials with nanostructured features. The ultimate aim is to reproduce and enhance the natural nanoscale elements present in the human body and to thereby develop new materials with improved biological activities. Progress in this area requires a multidisciplinary effort at the interface of biology, physics, and chemistry. In this Review, the major techniques that have been adopted to yield novel nanostructured versions of familiar biomaterials, focusing particularly on metals, are presented and the way in which nanometric surface cues can beneficially guide biological processes, exerting influence on cellular behavior, is illustrated.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.171
GPT teacher head0.363
Teacher spread0.193 · 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