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Record W2166747074 · doi:10.3390/jfb3020432

Bioactive and Biodegradable Nanocomposites and Hybrid Biomaterials for Bone Regeneration

2012· article· en· W2166747074 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

VenueJournal of Functional Biomaterials · 2012
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsNanocompositeMaterials scienceRegeneration (biology)ScaffoldBioactive glassPolyesterNanotechnologyBiodegradable polymerBiomaterialTissue engineeringHybrid materialPolymerBiomedical engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

Strategies for bone tissue engineering and regeneration rely on bioactive scaffolds to mimic the natural extracellular matrix and act as templates onto which cells attach, multiply, migrate and function. Of particular interest are nanocomposites and organic-inorganic (O/I) hybrid biomaterials based on selective combinations of biodegradable polymers and bioactive inorganic materials. In this paper, we review the current state of bioactive and biodegradable nanocomposite and O/I hybrid biomaterials and their applications in bone regeneration. We focus specifically on nanocomposites based on nano-sized hydroxyapatite (HA) and bioactive glass (BG) fillers in combination with biodegradable polyesters and their hybrid counterparts. Topics include 3D scaffold design, materials that are widely used in bone regeneration, and recent trends in next generation biomaterials. We conclude with a perspective on the future application of nanocomposites and O/I hybrid biomaterials for regeneration of bone.

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 score0.006
Threshold uncertainty score0.748

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 head0.015
GPT teacher head0.210
Teacher spread0.195 · 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