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Record W3111642148 · doi:10.15585/mmwr.mm6950e2

The Advisory Committee on Immunization Practices’ Interim Recommendation for Use of Pfizer-BioNTech COVID-19 Vaccine — United States, December 2020

2020· article· en· W3111642148 on OpenAlexfundno aff
Sara E. Oliver, Julia W. Gargano, Mona Marin, Megan Wallace, Kathryn Curran, Mary E. Chamberland, Nancy McClung, Doug Campos‐Outcalt, Rebecca L. Morgan, Sarah Mbaeyi, José R. Romero, H. Keipp Talbot, Grace M. Lee, Beth P. Bell, Kathleen Dooling

Bibliographic record

VenueMMWR Morbidity and Mortality Weekly Report · 2020
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
FundersWake Forest School of MedicineResearch Institute, Nationwide Children's HospitalUniversity of California, Los AngelesBiomedical Advanced Research and Development AuthorityCenters for Disease Control and PreventionPublic Health AgencyNorthwell HealthMarshfield Clinic Research InstituteNationwide Children's HospitalU.S. Department of DefenseMinnesota Department of HealthGeorge Washington UniversityStrongSaint Louis UniversityKaiser PermanenteEmory UniversityAmerican Pharmacists AssociationCouncil of State and Territorial EpidemiologistsPublic Health Agency of CanadaNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsMedicineInterimAdvisory committeeCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakImmunizationVirologyFamily medicineImmunologyPathologyLawManagementDiseaseAntibody

Abstract

fetched live from OpenAlex

The recommendation for the Pfizer-BioNTech COVID-19 vaccine should be implemented in conjunction with ACIP's interim recommendation for allocating initial supplies of COVID-19 vaccines (2). The ACIP recommendation for the use of the Pfizer-BioNTech COVID-19 vaccine under EUA is interim and will be updated as additional information becomes available.

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)0.030
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.067
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.081
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0120.015
Insufficient payload (model declined to judge)0.0670.056

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 head0.213
GPT teacher head0.431
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 designNot applicable
Domainnot available
GenreOther

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

Citations562
Published2020
Admission routes1
Has abstractyes

Explore more

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