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Record W2525953524 · doi:10.1002/jbm.b.33784

Morphological examination of highly porous polylactic acid/<scp>B</scp>ioglass<sup>®</sup> scaffolds produced via nonsolvent induced phase separation

2016· article· en· W2525953524 on OpenAlexafffund
Ehsan Rezabeigi, Paula M. Wood‐Adams, R. A. L. Drew

Bibliographic record

VenueJournal of Biomedical Materials Research Part B Applied Biomaterials · 2016
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolylactic acidPorosityMaterials scienceChemical engineeringPhase (matter)ChemistryComposite materialPolymer chemistryChromatographyPolymerOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

particles via nonsolvent induced phase separation at -23°C with no sacrificial phases involved. Before the incorporation of the bioglass with PLA, the particles are surface modified with a silane coupling agent which effectively diminishes agglomeration between them leading to a better dispersion of bioactive particles throughout the scaffold. Interestingly, the incorporation route (via solvent dichloromethane or nonsolvent hexane) of the surface modified particles in the foaming process has the greatest impact on porosity, crystallinity, and morphology of the scaffolds. The composite scaffolds with a morphology consisting of both mesopores and large macropores, which is potentially beneficial for bone regeneration applications, are examined further. SEM images show that the surface modified bioglass particles take-up a unique configuration within the mesoporous structure of these scaffolds ensuring that the particles are well interlocked but not completely covered by PLA such that they can be in contact with physiological fluids. The results of preliminary in vitro tests confirm that this PLA/bioglass configuration promotes the interaction of the bioactive phase with physiological fluids. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 2433-2442, 2017.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.320
Teacher spread0.280 · 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.

Study designBench or experimental
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

Citations20
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Biomedical Materials Research Part B Applied BiomaterialsSame topicBone Tissue Engineering MaterialsFrench-language works237,207