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Record W2322604326 · doi:10.1002/ppap.201500211

Atmospheric Pressure Plasma Polymer of Ethyl Lactate: In Vitro Degradation and Cell Viability Studies

2016· article· en· W2322604326 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

VenuePlasma Processes and Polymers · 2016
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsMcGill UniversityHôpital Saint-François d'AssiseUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDegradation (telecommunications)Dielectric barrier dischargePolymerAtmospheric-pressure plasmaX-ray photoelectron spectroscopyPolymer degradationEthyl lactateChemical engineeringDeposition (geology)Materials scienceAqueous solutionChemistryPlasmaOrganic chemistryDielectricSolvent

Abstract

fetched live from OpenAlex

Ethyl lactate is injected into a dielectric barrier discharge (DBD) to build up a degradable plasma polymer (PP) to be used as a drug delivery system. Plasma power, deposition time, and type of carrier gas (Ar, N2) are correlated to the coating in vitro degradation rate. PPs are characterized by AFM, SEM, IR spectroscopy, XPS, and SEC, while surface profilometry is used to monitor the degradation kinetics. PPs deposited under N2 are mainly composed of hydrophilic functionalities, which explain their fast degradation upon exposure to an aqueous environment. In contrast, PPs synthesized under Ar lead to a slower degradation rate due to their hydrocarbon structure containing some hydrolyzable moieties. The potential of the PPs for vascular applications is verified through cell viability experiments.

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)0.000
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 score0.345
Threshold uncertainty score0.456

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 communication0.0000.000
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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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