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Record W4384924715 · doi:10.1002/marc.202300261

Synergistic Approaches in the Design and Applications of UCST Polymers

2023· review· en· W4384924715 on OpenAlexafffund
Yi Nan, Chuanzhuang Zhao, Guillaume Beaudoin-Bussières, X. X. Zhu

Bibliographic record

VenueMacromolecular Rapid Communications · 2023
Typereview
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsUniversité de Montréal
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsUpper critical solution temperaturePolymerPolymer scienceMaterials scienceNanotechnologyCopolymerComposite material

Abstract

fetched live from OpenAlex

This review summarizes recent progress in the synergistic design strategy for thermoresponsive polymers possessing an upper critical solution temperature (UCST) in aqueous systems. To achieve precise control of the responsive behavior of the UCST polymers, their molecular design can benefit from a synergistic effect of hydrogen bonding with other interactions or modification of the chemical structures. The combination of UCST behavior with other stimuli-responsive properties of the polymers may yield new functional materials with potential applications such as sensors, actuators, and controlled release devices. The advances in this area provide insight or inspiration into the understanding and design of functional UCST polymers for a wide range of applications.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.135
GPT teacher head0.326
Teacher spread0.191 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations43
Published2023
Admission routes2
Has abstractyes

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