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Record W7132263587

Development and validation of high-performance SARS-CoV-2 antiviral coatings for high-touch critical surfaces

2020· article· en· W7132263587 on OpenAlexafffundvenueabout
Éric Irissou, Buno Guerreiro, Maniya Aghasibeig, Chen Liang, Saina Beitari, Stephen Yue, Hanqing Che, Amir Hossein Nobari, Luc Pouliot, Fernanda Caio, Sylvain Desaulniers, Murray Pearson, Kevin Seow, Jean‐François Boulet

Bibliographic record

VenueNPARC · 2020
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsHatch (Canada)Nanoacademic TechnologiesMcGill UniversityNational Circus SchoolJewish General HospitalNational Research Council Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTimelinePandemicGovernment (linguistics)Coronavirus disease 2019 (COVID-19)Transmission (telecommunications)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
DOInot available

Abstract

fetched live from OpenAlex

A joint Canadian project aims to curb the COVID-19 pandemic and future epidemics with cold sprayed, copper-based coatings. In this digital-first article from Advanced Materials & Processes, ASM International’s flagship magazine, a team from industry, academia, and government in Canada outline their research, plan, and timeline for the widespread adoption of antiviral coatings that could limit the transmission of viruses on high-touch 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.028
GPT teacher head0.246
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2020
Admission routes4
Has abstractyes

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