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Record W3196200553 · doi:10.1016/j.lana.2021.100043

The Prevention of Common Respiratory Virus Epidemics in 2020-21 during the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Pandemic: An Unexpected Benefit of the Implementation of Public Health Measures

2021· article· en· W3196200553 on OpenAlexaboutno aff
Vasanthi Avadhanula, Pedro A. Piedra

Bibliographic record

VenueThe Lancet Regional Health - Americas · 2021
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Respiratory systemSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)CoronavirusMedicineVirologyPublic health2019-20 coronavirus outbreakBetacoronavirusVirusSevere acute respiratory syndrome coronavirusIntensive care medicineInternal medicineOutbreakDiseaseInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread globally causing an unprecedented public health crisis. Transmission of SARS-CoV-2 occurs primarily by respiratory droplets expelled by infected persons [1]. In order to curb the transmission of SARS-CoV-2, governments across the globe have resorted to non-pharmaceutical intervention (NPI) strategies. These containment measures include imposing large-scale lockdowns, quarantining infected persons, implementing travel restrictions, and recommending personal protective measures such as hand hygiene, wearing masks and social distancing.

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)0.005
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.198
GPT teacher head0.443
Teacher spread0.246 · 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 designObservational
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

Citations15
Published2021
Admission routes1
Has abstractyes

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