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Record W4383961227 · doi:10.31399/asm.amp.2020-08.p040

Development and Validation of High-Performance SARS-CoV-2 Antiviral Coatings for High-Touch Surfaces

2020· article· en· W4383961227 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAM&P Technical Articles · 2020
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsMcGill UniversityHatch (Canada)Jewish General HospitalNational Research Council Canada
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Pandemic2019-20 coronavirus outbreakGas dynamic cold sprayComponent (thermodynamics)Materials scienceMicrostructureComputer scienceManufacturing engineeringMetallurgyCoatingNanotechnologyEngineeringVirology

Abstract

fetched live from OpenAlex

Abstract A joint Canadian project aims to curb the COVID-19 pandemic and future epidemics with cold sprayed, copper-based coatings. The objectives are: (1) to tailor the microstructure and surface state of Cu/Cu alloy cold spray coatings to maximize the antiviral activity and provide an economically viable solution that can be rapidly upscaled and industrialized; (2) to identify the most relevant high-touch surface components based on a systematic data-driven analysis and simulation of public infrastructure usage; and (3) to demonstrate viable production capability with real component demonstrators to be installed in public transport facilities for in situ testing.

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 score0.037
Threshold uncertainty score0.585

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 head0.026
GPT teacher head0.248
Teacher spread0.222 · 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