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Record W2738873167 · doi:10.1002/mame.201700162

Tough and Enzyme‐Degradable Hydrogels

2017· article· en· W2738873167 on OpenAlexafffund
Ginger Chen, Shadi Taghavi, Dale M. Marecak, Brian G. Amsden

Bibliographic record

VenueMacromolecular Materials and Engineering · 2017
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsQueen's University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaResearch and Innovation FoundationCanada Foundation for Innovation
KeywordsSelf-healing hydrogelsMaterials scienceEthylene glycolCollagenaseToughnessPEG ratioTrimethylene carbonateChemical engineeringPolymer chemistryComposite materialPolymerChemistryEnzymePolymerizationBiochemistry

Abstract

fetched live from OpenAlex

Abstract Mechanically robust hydrogels that degrade only via cell action have potential as scaffolds for the generation of load‐bearing soft connective tissue. This study demonstrates that terminally acrylated 4‐arm‐poly(ethylene glycol)‐ block ‐oligo(trimethylene carbonate) (4a‐PEG‐(TMC) n ) can be readily reacted with a collagenase‐degradable bis ‐cysteine peptide to form hydrogels. The inclusion of the TMC blocks renders the hydrogels mechanically tough when tested under compression, with modulus and toughness values within the range of those of articular cartilage. Moreover, the hydrogels formed are resistant to degradation by hydrolysis in the absence of collagenase but degrade via surface erosion in the presence of collagenase. The strategy employed to form these hydrogels is readily tailored to create a variety of tough, enzyme‐degradable hydrogels of varying mechanical and degradation properties.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.201
Teacher spread0.189 · 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 teacher head, 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

Citations4
Published2017
Admission routes2
Has abstractyes

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