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Record W3091985208 · doi:10.1021/acsnano.0c05937

Antimicrobial Nanomaterials and Coatings: Current Mechanisms and Future Perspectives to Control the Spread of Viruses Including SARS-CoV-2

2020· review· en· W3091985208 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

VenueACS Nano · 2020
Typereview
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of OntarioMcMaster University
KeywordsNanotechnologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)NanomaterialsCoronavirus disease 2019 (COVID-19)Mechanism (biology)Materials scienceEmerging technologiesBiochemical engineeringEngineeringMedicineInfectious disease (medical specialty)DiseasePhysics

Abstract

fetched live from OpenAlex

contaminated surfaces. We discuss the mechanism of operation and effectivity of several types of inorganic and organic materials, in the bulk and nanomaterial form, and assess the possibility of implementing these as antiviral coatings. Toxicity and environmental concerns are also discussed for the presented approaches. Finally, we present future perspectives with regards to emerging antimicrobial technologies such as omniphobic surfaces and assess their potential in suppressing surface-mediated virus transfer. Although some of these emerging technologies have not yet been tested directly as antiviral coatings, they hold great potential for designing the next generation of antiviral surfaces.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.053
GPT teacher head0.355
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