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Record W2576277701 · doi:10.1002/slct.201601278

Ion‐Dependent Modulation of Self‐Healing Hydrogels

2017· article· en· W2576277701 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemistrySelect · 2017
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsSelf-healing hydrogelsMetal ions in aqueous solutionSupramolecular chemistryIonRheologyHydrogen bondMaterials scienceMetalMoleculeLigand (biochemistry)Self-healingDivalentChemistryChemical engineeringPolymer chemistryReceptorComposite materialOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Abstract A peptide based gelator has been reported that forms supramolecular hydrogels in presence of divalent metal ions through metal‐ligand interaction. These hydrogels are multi‐stimuli responsive and self‐healing in nature. The rheology studies show that the mechanical strength and healing properties are highly dependent on metal ions and mechanical strength of these hydrogels could be tune by applying appropriate metal ions. It has been found that the mechanical and healing properties also depend on the counter anion used. Furthermore, the water suppression 1 H NMR study in hydrogel state was performed to probe the hydrogen bonding interaction between gelator to gelator and gelator to water molecules in real‐time.

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.

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)0.001
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 score0.003
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.274
Teacher spread0.258 · 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