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Record W3046679789 · doi:10.1002/macp.202000216

The Next 100 Years of Polymer Science

2020· article· en· W3046679789 on OpenAlexaff
Alaa S. Abd‐El‐Aziz, Markus Antonietti, Christopher Barner‐Kowollik, Wolfgang H. Binder, Alexander Böker, Cyrille Boyer, Michael R. Buchmeiser, Stephen Z. D. Cheng, Franck D’Agosto, George Floudas, Holger Frey, Giancarlo Galli, Jan Genzer, Laura Hartmann, Richard Hoogenboom, Takashi Ishizone, David L. Kaplan, Mario Leclerc, Andreas Lendlein, Bin Liu, Timothy E. Long, Sabine Ludwigs, Jean‐François Lutz, Krzysztof Matyjaszewski, Michaël A. R. Meier, Kläus Müllen, Markus Müllner, Bernhard Rieger, Thomas P. Russell, Daniel A. Savin, A. Dieter Schlüter, Ulrich S. Schubert, Sebastian Seiffert, Kirsten Severing, João B. P. Soares, Mara Staffilani, Brent S. Sumerlin, Yanming Sun, Ben Zhong Tang, Chuanbing Tang, Patrick Théato, Nicola Tirelli, Ophelia K. C. Tsui, Miriam M. Unterlass, Philipp Vana, Brigitte Voit, Sergey Vyazovkin, Christoph Weder, Ulrich Wiesner, Wai‐Yeung Wong, Chi Wu, Yusuf Yağcı, Jiayin Yuan, Guangzhao Zhang

Bibliographic record

VenueMacromolecular Chemistry and Physics · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversity of AlbertaUniversité LavalUniversity of Prince Edward Island
Fundersnot available
KeywordsPolymer sciencePolymerPolymerizationPolymer chemistryMacromoleculeChemistryNanotechnologyMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The year 2020 marks the 100th anniversary of the first article on polymerization, published by Hermann Staudinger. It is Staudinger who realized that polymers consist of long chains of covalently linked building blocks. Polymers have had a tremendous impact on the society ever since this initial publication. People live in a world that is almost impossible to imagine without synthetic polymers. But what does the future hold for polymer science? In this article, the editors and advisory board of Macromolecular Chemistry and Physics reflect on this question.

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)0.005
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0060.007
Open science0.0010.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0360.018

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 head0.020
GPT teacher head0.287
Teacher spread0.267 · 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
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

Citations108
Published2020
Admission routes1
Has abstractyes

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