MétaCan
Menu
Back to cohort
Record W2073937729 · doi:10.1039/c4tb01871k

Nanocomposited silicone hydrogels with a laser-assisted surface modification for inhibiting the growth of bacterial biofilm

2015· article· en· W2073937729 on OpenAlexafffund
Ping Yin, Guobang Huang, Wai Hei Tse, yiming bao, John D. Denstedt, Jin Zhang

Bibliographic record

VenueJournal of Materials Chemistry B · 2015
Typearticle
Languageen
FieldChemistry
TopicAerogels and thermal insulation
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiofilmSelf-healing hydrogelsSiliconeMaterials scienceSurface modificationBacterial growthSilicone hydrogelChemical engineeringNanotechnologyComposite materialPolymer chemistryBacteriaMedicineBiology

Abstract

fetched live from OpenAlex

. In addition, the relative cell viabilities of NIH/3T3 mouse fibroblast cells treated using the nanocomposited silicone hydrogels coated with/without PEG were studied. No toxic effect is imposed on the cells. Consequently, the MAPLE process is a controllable, contamination-free technique to modify the surface of silicone hydrogels. We expect that the nanocomposited silicone hydrogels with appropriate surface treatment can be applied in various wearable and implantable medical devices.

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)0.001
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 score0.001
Threshold uncertainty score0.441

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 science0.0000.000
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 head0.031
GPT teacher head0.248
Teacher spread0.218 · 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

Citations13
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Materials Chemistry BSame topicAerogels and thermal insulationFrench-language works237,207