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Record W2341334788 · doi:10.1515/polyeng-2015-0079

The role of poly(acrylic acid) in conventional glass polyalkenoate cements

2015· article· en· W2341334788 on OpenAlexaff
Adel Alhalawani, Declan J. Curran, Daniel Boyd, Mark R. Towler

Bibliographic record

VenueJournal of Polymer Engineering · 2015
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsDalhousie UniversityToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceMolar massDispersityRheologyAcrylic acidPolyacrylic acidPolymerBiocompatibilityAcrylic resinChemical engineeringComposite materialPolymer sciencePolymer chemistryCoating

Abstract

fetched live from OpenAlex

Abstract Glass polyalkenoate cements (GPCs) have been used in dentistry for over 40 years. These novel bioactive materials are the result of a reaction between a finely ground glass (base) and a polymer (acid), usually poly(acrylic acid) (PAA), in the presence of water. This article reviews the types of PAA used as reagents (including how they vary by molar mass, molecular weight, concentration, polydispersity and content) and the way that they control the properties of the conventional GPCs (CGPCs) formulated from them. The article also considers the effect of PAA on the clinical performance of CGPCs, including biocompatibility, rheological and mechanical properties, adhesion, ion release, acid erosion and clinical durability. The review has critically evaluated the literature and clarified the role that the polyacid component of CGPCs plays in setting and maturation. This review will lead to an improved understanding of the chemistry and properties of the PAA phase which will lead to further innovation in the glass-based cements field.

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)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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

Citations45
Published2015
Admission routes1
Has abstractyes

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