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Record W2916631372 · doi:10.1002/marc.201570054

Macromol. Rapid Commun. 13/2015

2015· article· en· W2916631372 on OpenAlexaff
So Young An, Seung Man Noh, Joon Hyun Nam, Jung Kwon Oh

Bibliographic record

VenueMacromolecular Rapid Communications · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsConcordia University
Fundersnot available
KeywordsSelf-healingElasticity (physics)Disulfide bondSulfideViscoelasticityPolymer chemistryMaterials sciencePolymer scienceChemical engineeringChemistryComposite materialOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Back Cover: Dual sulfide–disulfide crosslinked s–ssPxN networks are synthesized by a combination of photo-induced thiol-ene radical addition and oxidation. These networks show rapid self-healing at room temperature within 30 s to 30 min, with no need for extra heling agents. The self-healable s-ssPxN networks retain their integrity when damaged by external force and exhibit self-healing elasticity with reversible viscoelastic properties. Further details can be found in the article by S. Y. An, S. M. Noh, J. H. Nam, J. K. Oh* on page 1255.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.660
Threshold uncertainty score0.942

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.3400.191

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 head0.044
GPT teacher head0.295
Teacher spread0.251 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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