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Record W4388077294 · doi:10.1038/s41597-023-02670-6

Author Correction: Non-pharmaceutical interventions to combat COVID-19 in the Americas described through daily sub-national data

2023· erratum· en· W4388077294 on OpenAlexaff
Michael Touchton, Felícia Marie Knaul, Héctor Arreola‐Ornelas, Thalia Porteny, Óscar Méndez Carniado, Marco Antonio Faganello, Calla Hummel, Silvia Paz Otero, Jorge Insúa, Fausto Patino, Eduardo A. Undurraga, Pedro Emilio Perez‐Cruz, Mariano Sánchez-Talanquer, V. Ximena Velasco Guachalla, Jami Nelson‐Nuñez, Carew Boulding, Renzo Calderón-Anyosa, Patricia García, Valentina Vargas

Bibliographic record

VenueScientific Data · 2023
Typeerratum
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsMcGill University
FundersInstituto Tecnológico y de Estudios Superiores de MonterreyUniversity of Miami
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Psychological interventionPandemicMEDLINEGeographyData scienceMedicineVirologyComputer sciencePolitical scienceOutbreakInternal medicineNursingInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

In this article the funding from ‘the University of Miami Institute for Advanced Study of the Americas and Tecnologico de Monterrey (Challenge-Based Research Funding Program, I036-IOR005- C5-T3-T)’ was omitted. The original article has been corrected.

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)0.007
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.509
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0050.005
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.662
GPT teacher head0.574
Teacher spread0.088 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2023
Admission routes1
Has abstractyes

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