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Record W3029485439 · doi:10.3390/jfb11020035

Sol-Gel Derived Tertiary Bioactive Glass–Ceramic Nanorods Prepared via Hydrothermal Process and Their Composites with Poly(Vinylpyrrolidone-Co-Vinylsilane)

2020· article· en· W3029485439 on OpenAlexaff
Dibakar Mondal, Andrei Zaharia, Kibret Mequanint, Amin S. Rizkalla

Bibliographic record

VenueJournal of Functional Biomaterials · 2020
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceNanorodBioactive glassChemical engineeringPolymerComposite materialHydrothermal circulationCeramicComposite numberNanotechnology

Abstract

fetched live from OpenAlex

bioactive glass particles were prepared through sol-gel chemistry followed by a base-induced hydrothermal process at 130 °C and 170 °C for various times up to 36 h. This facile, low-temperature and surfactant-free hydrothermal process has shown to be capable of producing uniform nanorods and nanowires. One-dimensional growth of nanorods and the characteristics of siloxane bridging networks were dependent on the hydrothermal temperature and time. Hardened bioactive composites were prepared from BG nanorods and cryo-milled poly(vinylpyrrolidone-co-triethoxyvinylsilane) in the presence of ammonium phosphate as potential bone graft biomaterials. Covalent crosslinking has been observed between the organic and inorganic components within these composites. The ultimate compressive strength and modulus values increased with increasing co-polymer content, reaching 27 MPa and 500 MPa respectively with 30% co-polymer incorporation. The materials degraded in a controlled non-linear manner when incubated in phosphate-buffered saline from 6 h to 14 days. Fibroblast cell attachment and spreading on the composite were not as good as the positive control surfaces and suggested that they may require protein coating in order to promote favorable cell interactions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.201
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2020
Admission routes1
Has abstractyes

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