MétaCan
Menu
Back to cohort
Record W3161852825 · doi:10.47326/ocsat.2021.02.28.1.0

Risk of Vaccine-Induced Thrombotic Thrombocytopenia (VITT) following the AstraZeneca/COVISHIELD Adenovirus Vector COVID-19 Vaccines

2021· report· en· W3161852825 on OpenAlexaboutno aff
Benjamin Chan, Ayodele Odutayo, Peter Jüni, Nathan M. Stall, Pavlos Bobos, Adalsteinn Brown, Allan Grill, Noah Ivers, Antonina Maltsev, Allison McGeer, Katherine J. Miller, Ullanda Niel, Fahad Razak, Beate Sander, Michelle Sholzberg, Arthur S. Slutsky, Andrew M. Morris, Menaka Pai

Bibliographic record

Venuenot available
Typereport
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)ImmunologyVirologyInternal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Published estimates of the risk of vaccine-induced thrombotic thrombocytopenia (VITT) from countries with moderate to high data quality range from 1 case per 26,500 to 1 case per 127,300 first doses of AstraZeneca/COVISHIELD administered (Table 1). The risk of VITT in Canada as of May 8, 2021 has been estimated to be approximately 1 per 55,000 doses, but several presumptive cases are still under investigation.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.084
GPT teacher head0.366
Teacher spread0.281 · 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

Citations22
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicHeparin-Induced Thrombocytopenia and ThrombosisFrench-language works237,207