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Record W4223581822 · doi:10.1503/cmaj.1095993

Booster uptake stalling as experts debate fourth COVID shots

2022· article· en· W4223581822 on OpenAlexvenueaboutno aff
Diana Duong, Lauren Vogel

Bibliographic record

VenueCanadian Medical Association Journal · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsBooster (rocketry)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineVaccinationBooster doseLift (data mining)ImmunityComputer scienceVirologyImmunologyImmunizationInfectious disease (medical specialty)EngineeringInternal medicineOutbreakImmune systemDisease

Abstract

fetched live from OpenAlex

As Canadian provinces lift mask mandates and proof of vaccination policies, experts are worried that only 56% of adults, and far fewer children, have received three doses of a SARS-COV-2 vaccine. Meanwhile, vaccine manufacturers are warning that fourth doses may be necessary to maintain immunity.

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)0.053
metaresearch head score (Gemma)0.127
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.342
Threshold uncertainty score0.680

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.127
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0180.006
Scholarly communication0.0120.006
Open science0.0030.006
Research integrity0.0180.020
Insufficient payload (model declined to judge)0.0410.008

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 head0.061
GPT teacher head0.384
Teacher spread0.324 · 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
GenreCommentary

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

Citations3
Published2022
Admission routes2
Has abstractyes

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