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Record W3138261594 · doi:10.46747/cfp.6703185

COVID-19 vaccine fast facts

2021· article· en· W3138261594 on OpenAlexaffvenue
Michael R. Kolber, Paul Fritsch, Morgan Price, Alexander Singer, Jennifer Young, Nicolas Dugré, Sarah Bradley, Tony Nickonchuk

Bibliographic record

VenueCanadian Family Physician · 2021
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsProvincial Health Services AuthorityCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalDoug Bragg Enterprises (Canada)University of ManitobaCollege of Family Physicians of CanadaUniversity of British ColumbiaUniversity of CalgaryUniversity of Alberta HospitalUniversité de MontréalUniversity of Alberta
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)InterimSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakMedicineVirologyCoronavirusDiseaseInfectious disease (medical specialty)Political scienceOutbreakInternal medicine

Abstract

fetched live from OpenAlex

What are the benefits and risks of 3 coronavirus disease 2019 (COVID-19) vaccines? Interim results (2 large RCTs) show the relative efficacy of the Pfizer-BioNTech and Moderna vaccines (about 95%) and the AstraZeneca-Oxford vaccine (about 70%) in preventing COVID-19. Absolute benefits will vary

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)0.008
metaresearch head score (Gemma)0.051
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 score0.922
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.051
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0010.001
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0720.025

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 head0.045
GPT teacher head0.322
Teacher spread0.276 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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