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Upon Synthesis of Poly(N-isopropylacrylamide-co-2-dimethyl-aminoethyl methacrylate-co-itaconic acid) Copolymers as Matrix Ensuring Intramolecular Strategies for Further Coupling Applications

2014· article· en· W1990324431 on OpenAlexvenueno aff
Aurica P. Chiriac, Loredana E. Niţă, Iordana Neamţu, Vera Bălan, Alina Diaconu

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsnot available
FundersUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si InovariiAutoritatea Natională pentru Cercetare Stiintifică
KeywordsItaconic acidAmmonium persulfateMaterials sciencePolymer chemistryPolymerCopolymerMethacrylateThermal stabilityRadical polymerizationPolymerizationChemical engineeringComposite material

Abstract

fetched live from OpenAlex

The study presents a set of copolymers synthesis based on N-isopropylacrylamide, 2-dimethylaminoethyl methacrylate and itaconic acid comonomers found in different gravimetric ratio, acquired through polymerization in water in the presence of ammonium persulfate as radical initiator. The purpose was to prepare polymeric structure with dual sensitivity to temperature and pH respectively, and able as well to ensure intramolecular strategies for coupling applications of inorganic or bioactive compounds. The polymers composition was confirmed by FTIR and 1H-NMR spectra. The thermal stability of the polymeric compounds was evaluated, and SEM investigations of the polymer morphology are also presented. The polymers dispersions were characterized from the viewpoint of their hydrodynamic radius, zeta potential and conductivity.

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)0.000
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 score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.024
GPT teacher head0.361
Teacher spread0.336 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venueJournal of Research Updates in Polymer ScienceSame topicHydrogels: synthesis, properties, applicationsFrench-language works237,207