MétaCan
Menu
Back to cohort
Record W1908900710 · doi:10.1002/mabi.201500109

Silver Nanoparticle Coated Bioactive Glasses - Composites with Dex/CMC Hydrogels: Characterization, Solubility, and In Vitro Biological Studies

2015· article· en· W1908900710 on OpenAlex
Anthony W. Wren, Pegah Hassanzadeh, Lana M. Placek, Timothy J. Keenan, Aisling Y. Coughlan, Lydia R. Boutelle, Mark R. Towler

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.

Bibliographic record

VenueMacromolecular Bioscience · 2015
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSelf-healing hydrogelsSolubilityNanoparticleCharacterization (materials science)Bioactive glassSilver nanoparticleChemistryMaterials scienceComposite materialChemical engineeringPolymer chemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Silver (Ag) coated bioactive glass particles (Ag-BG) were formulated and compared to uncoated controls (BG) in relation to glass characterization, solubility and microbiology. X-ray diffraction (XRD) confirmed a crystalline AgNP surface coating while ion release studies determined low Ag release (<2 mg/L). Cell culture studies presented increased cell viability (127 and 102%) with lower liquid extract (50 and 100 ml/ml) concentrations. Antibacterial testing of Ag-BG in E. coli, S. epidermidis and S. aureus significantly reduced bacterial cell viability by 60-90%. Composites of Ag-BG/CMC-Dex Hydrogels were formulated and characterized. Agar diffusion testing was conducted where Ag-BG/hydrogel composites produced the largest inhibition zones of 7 mm (E. coli), 5 mm (S. aureus) and 4 mm (S. epidermidis).

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)0.000
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 score0.015
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.026
GPT teacher head0.241
Teacher spread0.215 · 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