MétaCan
Menu
Back to cohort
Record W3162862260 · doi:10.1021/cen-09914-scicon6

Adulterants detected in hand sanitizers

2021· article· en· W3162862260 on OpenAlexaboutno aff
Laura Howes

Bibliographic record

VenueC&EN Global Enterprise · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsnot available
Fundersnot available
KeywordsHand sanitizerCoronavirus disease 2019 (COVID-19)Food and drug administrationBusinessAgriculture2019-20 coronavirus outbreakPandemicProduct (mathematics)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)IngredientChemistryFood scienceVirologyMedicineMathematicsGeography

Abstract

fetched live from OpenAlex

As COVID-19 case numbers grew during the pandemic, so did the market for alcohol-based hand sanitizers. With demand outstripping supply, many companies stepped up to make the product or its key ingredient, ethanol, which dismantles SARS-CoV-2, the virus that causes COVID-19. Regulatory agencies such as the US Food and Drug Administration and Health Canada also relaxed regulations in response to the pandemic so that alcohols such as technical-grade ethanol, which has higher levels of specific contaminants than the typical pharmaceutical-grade ethanol, could be used for hand sanitizers. But in a recorded talk played at ACS Spring 2021, Timothy J. Tse of the University of Saskatchewan reported that some hand sanitizers have worrying levels of impurities. Tse presented the data ( Int. J. Environ. Res. Public Health 2021, DOI: 10.3390/ijerph18073766 ), during a talk in the Division of Agricultural and Food Chemistry. Tse and colleagues Fina B. Nelson and Martin J.

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 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 score0.248
Threshold uncertainty score0.521

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 head0.006
GPT teacher head0.261
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueC&EN Global EnterpriseSame topicBacillus and Francisella bacterial researchFrench-language works237,207