MétaCan
Menu
Back to cohort

Effect of OH Content on the Bioactivity of Sol-Gel Derived Glass Foam Scaffolds

2006· article· en· W1966530761 on OpenAlexaff
Julian R. Jones, Thomas F. Kemp, Mark E. Smith

Bibliographic record

VenueKey engineering materials · 2006
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsKensington Health
FundersEngineering and Physical Sciences Research CouncilUniversity of WarwickRoyal Academy of Engineering
KeywordsSimulated body fluidApatiteMaterials scienceChemical engineeringLayer (electronics)SinteringBioactive glassComposite material

Abstract

fetched live from OpenAlex

Bioactive glass scaffolds have been developed with interconnected macropore networks, with pore diameters in excess of 500µm and apertures in excess of 100µm, by foaming sol-gel derived bioactive glasses. Bioactive glasses bond to bone by forming a hydroxycarbonate apatite (HCA) layer on their surface on contact with body fluid, which is similar to the composition of the apatite in bone. The aim of this work was to investigate the how changing the atomic structure of the glass affects HCA layer formation. Scaffolds were synthesised at 3 sintering temperatures and were characterised using 29Si and proton MAS-NMR, from which the silica network connectivity and Si-OH groups were quantified. The rate of HCA layer formation decreased as the number of Si-OH groups decreased, confirming the role of Si-OH groups in HCA layer formation.

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)0.001
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
Metaresearch0.0000.001
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 head0.009
GPT teacher head0.189
Teacher spread0.179 · 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

Citations16
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueKey engineering materialsSame topicBone Tissue Engineering MaterialsFrench-language works237,207