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Record W1526865848 · doi:10.1002/9781118663721.ch17

Adverse Reactions to Human Papillomavirus Vaccines

2015· other· en· W1526865848 on OpenAlexaff
Lucija Tomljenovic, Christopher A. Shaw

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHuman papillomavirusHuman papillomavirus vaccineVirologyMedicineInternal medicineCervical cancerCancerGardasil

Abstract

fetched live from OpenAlex

This chapter reviews the data from numerous reports substantiating the link between adverse immune reactions and human papillomavirus (HPV) vaccines. It discusses the results from safety clinical trials on HPV vaccines. In their 2008 pre-licensure analysis of ADRs of potential autoimmune etiology in a large integrated safety database of ASO4 adjuvanted vaccines (including Cervarix), Verstraeten et al. pointed out that “It is important to note that none of these studies were set up primarily to study autoimmune disorders.” Large post-licensure epidemiological studies assessing the safety of Gardasil likewise failed to identify any significant autoimmune safety concerns. Post-vaccination adverse immune phenomena can have long latency periods. The human clinical trial data for the two HPV vaccines currently on the market reveal a troubling safety profile that requires an accurate reevaluation of the risks and benefits.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.070
GPT teacher head0.406
Teacher spread0.336 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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