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Antibacterial Coatings Based on Chitosan for Pharmaceutical and Biomedical Applications

2018· review· en· W2788294418 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

VenueCurrent Pharmaceutical Design · 2018
Typereview
Languageen
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilFonds de recherche du Québec – Nature et technologiesConselho Nacional de Desenvolvimento Científico e TecnológicoUniversité Laval
KeywordsBiocompatible materialChitosanBiopolymerNanotechnologyBiochemical engineeringMaterials scienceChemistryBiomedical engineeringMedicineEngineeringPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

The risk of bacterial colonization of abiotic surfaces of biomedical devices poses important challenges for the pharmaceutical and biomaterials science fields. In this scenario, antibacterial coatings have been developed, using a number of different molecules and materials. Among them, chitosan is a non-cytotoxic, biocompatible biopolymer with an inherent antimicrobial activity that has been already used in a wide variety of healthcare and industrial applications. Herein, chitosan-based antibacterial coatings are critically surveyed, with a special emphasis on their production methods, pharmaceutical and biomedical applications, along with their pros and cons, and finally highlighting the key challenges to be faced and future perspectives in this field.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.191
GPT teacher head0.447
Teacher spread0.256 · 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