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Record W2137656062 · doi:10.1002/jbm.a.35385

Poly(ethylene glycol)‐or silicone‐modified hyaluronan for contact lens wetting agent applications

2014· article· en· W2137656062 on OpenAlexaff
Stefan M. Paterson, Lina Liu, Michael A. Brook, Heather Sheardown

Bibliographic record

VenueJournal of Biomedical Materials Research Part A · 2014
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceContact angleEthylene glycolPolyethylene glycolWettingContact lensPolymer chemistrySelf-healing hydrogelsMonomerSiliconeBiopolymerChemical engineeringPolymerAdsorptionOrganic chemistryComposite materialChemistry

Abstract

fetched live from OpenAlex

Hyaluronan (HA) is a hydrophilic biopolymer that has been explored as a wetting agent in contact lens applications. In this study, HA was modified with siloxy or polyethylene glycol moieties using click chemistry to make it more soluble in monomer solutions used to synthesize model contact lens materials; unmodified HA was not soluble in the same monomer solutions. The water contents of the silicone hydrogels were not increased by the presence of modified HA, nor was there a decrease in the surface contact angle. However, modified HA did lead to a reduction in lysozyme adsorption in some cases. The leaching rate of HA modified with polyethylene glycol from a 78:22 DMA:TRIS(OH) hydrogel was significantly slower than for unmodified HA.

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)0.005
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.092
GPT teacher head0.395
Teacher spread0.303 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

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