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Record W4386086081 · doi:10.1021/jacsau.3c00345

Emerging Trends in the Chemistry of End-to-End Depolymerization

2023· review· en· W4386086081 on OpenAlexafffund
Zhengyu Deng, Elizabeth R. Gillies

Bibliographic record

VenueJACS Au · 2023
Typereview
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsDepolymerizationPolymerEnd-to-end principleNanotechnologyContext (archaeology)ChemistryMonomerComputer scienceCombinatorial chemistryMaterials sciencePolymer scienceOrganic chemistry

Abstract

fetched live from OpenAlex

). In this article, we will introduce the key chemical concepts and foundations of the field and then provide our perspective on recent exciting developments. For example, over the past few years, new depolymerizable backbones, including polyacetals, polydisulfides, polyesters, polythioesters, and polyalkenamers, have been developed, while modern approaches to depolymerize conventional backbones such as polymethacrylates have also been introduced. Progress has also been made on the topological evolution of depolymerizable systems, including the introduction of fully depolymerizable block copolymers, hyperbranched polymers, and polymer networks. Furthermore, precision sequence-defined oligomers have been synthesized and studied for data storage and encryption. Finally, our perspectives on future opportunities and challenges in the field will be discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.005
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.038
GPT teacher head0.325
Teacher spread0.287 · 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

Citations57
Published2023
Admission routes2
Has abstractyes

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