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Record W4394321132 · doi:10.6084/m9.figshare.3085885

Review of the Clinical Studies Used for Marketing Approval of the Vaccine Bexsero®

2016· dataset· en· W4394321132 on OpenAlexaboutno aff
Jean‐Christophe Bélisle‐Pipon, Louise Ringuette

Bibliographic record

VenueFigshare · 2016
Typedataset
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessMarketingMedicine

Abstract

fetched live from OpenAlex

This dataset includes all the clinical studies used for the evaluation of the marketing approval of the vaccine Bexsero® (also known under the names of 4CMenB and rMenB + OMV NZ) filed by Novartis with U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA) or Health Canada. A total of 23 clinical studies were used in these assessments and 5 studies were required by the FDA as post-marketing monitoring. The cited clinical studies totalled about 18,367 research participants who received either the Final Vaccine Formulation (rMenB + OMV NZ), an Early Vaccine Formulation (rMenB) or other comparators.

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)0.059
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.067
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0110.015
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0670.010

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 head0.217
GPT teacher head0.442
Teacher spread0.225 · 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
GenreDataset

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
Published2016
Admission routes1
Has abstractyes

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