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Record W6990214826

A database in ACCESS for assessing vaccine serious adverse events

2015· article· en· W6990214826 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicvaccines and immunoinformatics approaches
Canadian institutionsnot available
Fundersnot available
KeywordsAdverse effectVaccinationHealth dataVaccine safetyMEDLINEMedDRAPatient data
DOInot available

Abstract

fetched live from OpenAlex

Roger E Thomas,1 Dave Jackson2,3 1Department of Family Medicine, G012 Health Sciences Centre, University of Calgary Medical School, Calgary, AB, Canada; 2Independent Research Consultant, Calgary, AB, Canada; 3Database Consultant, University of Calgary, Calgary, AB, Canada Purpose: To provide a free flexible database for use by any researcher for assessing reports of adverse events after vaccination. Results: A database was developed in Microsoft ACCESS to assess reports of serious adverse events after yellow fever vaccination using Brighton Collaboration criteria. The database is partly automated (if data panels contain identical data fields the data are automatically also entered into those fields). The purpose is to provide the database free for developers to add additional panels to assess other vaccines. Keywords: serious adverse events after vaccination, database, process to assess vaccine-associated events 

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.252
GPT teacher head0.539
Teacher spread0.287 · 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 teacher head, not a consensus.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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