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Record W1972216657 · doi:10.1002/pc.20377

Modification of silica nanoparticles and their application in UDMA dental polymeric composites

2007· article· en· W1972216657 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.

Bibliographic record

VenuePolymer Composites · 2007
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMaterials scienceComposite materialNanocompositeNanoparticleDispersion (optics)Compatibility (geochemistry)SilaneSurface modificationFiller (materials)Chemical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Abstract Advancements in nanocomposites are highly dependent on the compatibility between the organic matrix and inorganic fillers, and the dispersion level of fillers throughout the matrix. Silane coupling agents are widely used to change the chemical structure of particles' surface in order to improve their compatibility and dispersion properties of particles. SiO 2 nanoparticles were modified by ζ potential, turbidity, and relative viscosity. The results indicate that the stability and dispersion degree in organic solvents have been improved after the modification. In addition, the mechanical properties of composites with modified silica were also studied, which indicated that, after the predispersion of particles in organic media, the mechanical properties of materials could be improved, even at low filler content. POLYM. COMPOS., 28:198–207, 2007. © 2007 Society of Plastics Engineers

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 score0.032
Threshold uncertainty score0.776

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 head0.013
GPT teacher head0.237
Teacher spread0.225 · 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