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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 OpenAlex
Adel Alhalawani, Declan J. Curran, Daniel Boyd, 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

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.

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 score0.046
Threshold uncertainty score0.243

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 head0.012
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