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Record W2794196634 · doi:10.1002/ppap.201800002

The effect of sterilization procedures on the physiochemical properties and performance of plasma polymer films

2018· article· en· W2794196634 on OpenAlex
Sara Babaei, А. А. Касимов, Pierre‐Luc Girard‐Lauriault

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 · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSterilization (economics)Plasma polymerizationMaterials sciencePolymerChemical engineeringEthylene oxideX-ray photoelectron spectroscopyContact anglePolymerizationHydrogen sulfidePolymer chemistryComposite materialCopolymerMetallurgySulfur

Abstract

fetched live from OpenAlex

Sterilization procedures can alter the desirable characteristics brought by plasma polymerization. Different plasma‐deposited functional organic coatings are prepared by plasma co‐polymerization of binary gas mixtures constituted of a hydrocarbon (butadiene/ethylene) and a heteroatom containing gas (carbon dioxide/ammonia/hydrogen sulfide). These coatings are then treated by dry heating, autoclaving, ethylene oxide, UV, and gamma‐ray irradiation. The physio‐chemical properties and performance of the samples are evaluated by profilometry, water contact angle goniometry, XPS, and 1‐h adhesion tests with U937 cells before and after sterilization. The results reveal that the changes during these sterilization processes are dependent on the type of plasma polymer and on the sterilization method. We derive recommendations on the suitability of the sterilization methods for the different coatings.

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 score0.002
Threshold uncertainty score0.313

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 studies0.0000.001
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 head0.016
GPT teacher head0.220
Teacher spread0.204 · 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